AI Best Practice Guides

Artificial intelligence Best Practice Guides are designed to help business leaders understand critical information about applying artificial intelligence applications successfully. Search our full set of executive guide reports below:

Making AI Projects Easier to Manage

Making AI Projects Easier to Manage – and More Like IT Projects

Increasingly, technology and business leaders look to AI project managers to make the execution (and success) of their AI projects more predictable. Executives and decision makers want AI projects to mature so they are more like the software development projects that have been with us for a generation. But, any AI project manager hoping to deliver on those expectations knows that success in AI projects requires an end-to-end thinking rarely found today.

Emerj AI Framing Scale

Achieving Sustainable AI Adoption with the AI Framing Scale

How AI project leaders provide the best chance at sustainable success in AI adoption?

The answer is simple: Frankly communicate both near-term and long-term value, and help leadership understand the importance of seeing measurable results, and the value of building a stronger AI foundation for future projects.

Incubating AI Projects - The Crucial Phase Between Pilot and Deployment

Incubating AI Projects – The Crucial Phase Between Pilot and Deployment

Artificial intelligence projects are more like R&D than they are like traditional IT. It is experimentation as much as it is adoption, and this difference is one of many reasons that AI projects take longer to integrate, and often hit bottlenecks that prevent them from being used in production.

What Makes AI Projects Different from IT Projects

What Makes AI Projects Different from IT Projects

One of the biggest hurdles to AI adoption and integration is a lack of proper expectations about applying AI in an existing business. Executives and their teams often go into the process blind because so few companies have learned these important lessons and challenges and because even fewer have successfully adopted AI in a way that delivers ROI.

Three Ways to Leverage Industry Expertise for an AI Career

Three Ways to Leverage Industry Expertise for an AI Career – A Guide for Non-Technical Leaders

As artificial intelligence makes its way into more industries and workflows, more and more non-technical team members will be charged with leading AI projects. The next wave of AI catalysts will be familiar with AI at a conceptual level (read: executive AI fluency), but will mostly be expert in bridging AI's capabilities to important business workflows and objectives.

Bridging Business Needs and Data Assets

Bridging Business Needs and Data Assets – Emerj AI Leader Insight

In the vast land of opportunities that AI creates, how do we select the projects that will generate ROI? Do we gain inspiration from reading AI use-cases relevant to our industries? Do we search through our own lists of existing priorities and hope the applications for AI will become clear?

Going from Pilot to Deployment with AI

Going from Pilot to Deployment with AI – 4 Factors to Consider

While overt AI "flops" are less common than they were three years ago, the pattern of failure for AI projects is still much the same.

Near-Term Value vs. AI Transformation - Emerj’s AI Project Quadrant

Near-Term Value vs. AI Transformation – Emerj’s AI Project Quadrant

You can invest in AI maturity and future capability - or you can have "quick wins" with surface-level AI applications that have relatively short-term, narrow ROI.

Selecting Early AI Projects with Emerj's Bullseye Model

Enterprise AI Project Selection – Emerj’s “Bullseye” Model

Picking first AI projects is challenging - and leadership is right to be wary of making the wrong investment. The challenge lies in both (a) identifying the right projects, and (b) ranking and determining the right ones.

Finding the Enterprise Fit for AI

Finding the Enterprise Fit for AI – Emerj AI Leader Insight

In the classic business book Good to Great, author Jim Collins talks about the different approaches for technology adoption between high-performing and average companies. Collins' research indicated that high performers tend to adopt technology as an accelerant to an existing, working strategy - while underperformers tended to adopt technology in an attempt to jumpstart a change in direction or strategy that they haven't yet undertaken.

How to Build an Enterprise AI Roadmap

How to Build an Enterprise AI Roadmap – A Four-Step Process

The firms that will gain a genuine advantage from AI deploy the technology in a way that achieves short-term ROI, alignment to a long-term vision, and conscious development of AI maturity - including skills, data infrastructure, and more.

The 7 Steps of the Data Science Lifecycle

The 7 Steps of the Data Science Lifecycle – Applying AI in Business

AI is not IT- and adopting artificial intelligence is almost nothing like adopting traditional software solutions.

The 3 Phases of Enterprise AI Deployment

The 3 Phases of Enterprise AI Deployment

Making AI work has a lot to do with "getting things right" even before a project starts, including:

Creating an AI Transformation Vision

Creating an AI Transformation Vision – Achieving Long-Term Advantage with AI

Artificial intelligence deployments are fraught with technical and tactical elements that have to be executed well in order to see a return on investment: The data must be accessible, cross-functional AI teams have to work together, and even after an AI pilot seems promising - it often needs to be integrated into legacy systems to be deployed successfully.

Building AI Maturity in the Enterprise

Building AI Maturity in the Enterprise – A Guide for Consultants and Enterprise Leaders

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

The 4 Horsemen of the AI-pocalypse

The 4 Horsemen of the AI-pocalypse – Why Enterprises Fail to Adopt AI

This is a contributed article by Ian Wilson, Founder at Strategy 4 AI - learn more about Ian's online AI strategy courses here. Ian is also the former Head of AI for HSBC, one of the largest financial institutions in the world. To inquire about contributed articles from outside experts, contact [email protected].
As the use of AI to support business operations moves through its maturity cycle we have passed a number of key milestones along the way. However, following a pattern reminiscent of previous emerging technology introductions, organizations initially hired experts only to balk when they used blasphemous words like "infrastructure," "industrialize" or "strategy" rather than soothing words like "use case," "quick win" or "easy ROI." 
Unfortunately, instead of sacrificing their misaligned expectations, many businesses sacrificed their experts... 
Fast forward a couple of years and many of those businesses, having attempted to cut corners and seeing mainly failure, now have a visceral understanding of what their experts were advising and are looking, with more experienced eyes, at how to move forward from this point.
However, many businesses are still making avoidable mistaken assumptions when it comes to the use of AI Capabilities to support business objectives. I like to call the most egregious of these assumptions The 4 Horsemen of the AI-Pocolypse:

_The Enterprise AI Catalyst Manifesto 950×540

The AI Catalyst Manifesto – Education as the Key to Enterprise AI Transformation

Artificial intelligence isn't making its way into enterprise deployments easily. Despite a relatively widespread understanding that AI is an inevitable force for winning market share and serving customers, by name estimates some 80-90% of AI projects fail.

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Setting the Right AI Expectations – A Key for Turning Pilots into Deployments

Setting expectations.

In our ongoing poll of new Emerj Plus members indicates that in addition to "accessing more AI use-cases" and "measuring AI ROI," our members consistently tell us that they join in order to "set expectations for AI projects" - especially with leadership.

7 Critical Factors for Developing an AI Strategy

7 Critical Factors for Developing an AI Strategy

Many books could be written on the subject of AI strategy, and we've seen that "strategy" means something different from one enterprise to the next. This article is a brief overview of the common steps in creating an AI strategy - in roughly the order that the steps are usually executed.

Discovering AI Opportunities Starts with the Right Team 950x540

Discovering AI Opportunities Starts with the Right Team

Vetting AI opportunities implies a hodge-podge of contextual knowledge that are almost never to be found together in a single expert, including (but not limited to) an understanding of:

Picking a First AI Project - A 3-Step Guide for Leaders 950x540

Picking a First AI Project – A 3-Step Guide for Leaders

Artificial intelligence is poised to change every industry - and to create trillions in economic value over the coming decades.

An Enterprise Innovation Leader's Guide to Successful AI Adoption

An Enterprise Innovation Leader’s Guide to Successful AI Adoption

This article was a request from one of our Catalyst Advisory Program members. The Catalyst Advisory Program is an application-only business growth coaching program  for AI consultants and AI service providers. The program helps AI consulting and services leaders win more deals and deliver more client value. Members receive one-to-one advisory, group coaching, and proprietary Catalyst AI best-practice frameworks. Learn more or apply at: emerj.com/catalyst.

Critical Capabilities - The Prerequisites to Successful AI Deployment

Critical Capabilities – The Prerequisites to AI Deployment in Business

Over the last four years, interviewing hundreds of AI researchers and AI enterprise leaders, we've consistently heard the same frustrations about AI adoption said time and time again.
"Culture is hard to change."
"Leadership doesn't know what they're trying to accomplish."
"Nobody knows what to do with these data scientists we've hired."
etc...
In our one-to-one work with enterprise clients, we've taken the most prevalent, recurring challenges to AI deployment and put them together into a framework of "prerequisites" to AI deployment.

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Predicting the ROI of AI – Pitfalls to AI Adoption in the Enterprise (Part 3 of 3)

In the final installment of the "Pitfalls to AI Adoption" series, we talk about predicting the ROI of AI. There are a lot of misconceptions running rampant around the ability to gauge the return on investment of artificial intelligence. In this article, we talk about what can and can't be done when it comes to investing in artificial intelligence and predicting what the return might be.

AI Integration Challenges - Pitfalls to AI Adoption

AI Integration Challenges – Pitfalls to AI Adoption in the Enterprise (Part 2 of 3)

In this second installment of the "Pitfalls to AI Adoption in the Enterprise" series, we're going to talk about underestimating the integration needs of artificial intelligence and machine learning.

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Avoid AI Novelty – Pitfalls to AI Adoption in the Enterprise (Part 1 of 3)

What's harder than training an algorithm to detect images or automate a process? Collecting and cleaning the data in the first place.

Buying and Adoption Readiness for AI (AI Zeitgeist 5)

Buying and Adoption Readiness for AI (AI Zeitgeist 5 of 7)

This article is part 5 of a 7-part series called “AI Zeitgeist,” where we’ll be mapping out the details of AI adoption over the next 10 years and explore the critical changes in the AI ecosystem that business leaders need to understand.

Where Can Artificial Intelligence be Used in Business? - An Executive Guide

Where Can Artificial Intelligence be Used in Business? – An Executive Guide

Most of the time when we have requests for speaking engagements here at Emerj, they're from business leaders. At the time this article was published, I just came back from a presentation at National Defense University in Washington DC. Presenting there was unique in many regards. Obviously, the use cases for tanks and submarines are quite different than they are for drug development or selling more products off retail shelves.

Ben Levy Emerj

Should My Startup be Using Machine Learning and AI?

Almost all young companies and companies in the start-up ecosystem today would like to talk about how they leverage AI or machine learning. In most cases, this is to make their product sound special and exciting. However, the fact is most young companies do not have the resources or the talent needed to leverage artificial intelligence in a way that would add to their value proposition.

1

Enterprise Adoption of Artificial Intelligence – When it Does and Doesn’t Make Sense

Chances are you have already been bombarded on social media or in your inbox about all these “revolutionary AI” this and “game-changer AI” that.

How to Apply Machine Learning to Business Problems 3

How to Apply Machine Learning to Business Problems

It's easy to see the massive rise in popularity for venture investment, conferences, and business-related queries for "machine learning" since 2012 - but most technology executives often have trouble identifying where their business might actually apply machine learning (ML) to business problems.

Creating an AI Transformation Vision

Creating an AI Transformation Vision – Achieving Long-Term Advantage with AI

Artificial intelligence deployments are fraught with technical and tactical elements that have to be executed well in order to see a return on investment: The data must be accessible, cross-functional AI teams have to work together, and even after an AI pilot seems promising - it often needs to be integrated into legacy systems to be deployed successfully.

Establishing Measurable ROI Benchmarks for AI Projects

Establishing Measurable ROI Benchmarks for AI Projects – A 5-Step Process

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/plus.

The Three Kinds of AI ROI - Emerj's Trinity Model 950x540

The Three Kinds of AI ROI – Emerj’s Trinity Model

AI vendors and enterprise buyers struggle to get on the same page about the return on investment (ROI) of AI solutions.

How to Succeed with AI Projects - Lead with Strategy

How to Succeed with AI Projects – Lead with Strategy

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

The ROI of Machine Learning - 3 Strategies for Measurable Results

The ROI of Machine Learning – 3 Strategies for Measurable Results

Many business leaders make the mistake of believing that AI and machine learning are like regular IT, but this could not be further from the truth. In large part, this is because, unlike simple software solutions for discreet business problems, it can be very difficult to measure the ROI of machine learning.

Near-Term AI Trends and the ROI of AI – An Overview 950×540

Near-Term AI Trends – A Guide for Mid-Size Business Leaders

What is the state of AI in business today - and what do mid-market business leaders need to know about AI now?

3 Ways to Build a Competitive AI Advantage

3 Ways to Build a Competitive AI Advantage – An Executive Guide

Companies looking to apply AI are looking for a competitive advantage in their industry, something that will give them an edge in the market and help them grow. However, not every AI application can give a company a competitive advantage. Many AI applications are simply going to become the new normal.

Personalizing Product Recommendations 
at Walmart@2x-min

Personalizing Product Recommendations at Walmart – with Dr. Charles Martin

The en masse shift to online shopping that transpired during and post-COVID appears as if it's destined to last. According to the Brookings Institute, one third of US adults have used delivery apps to order from a restaurant or store in the last year. 

Seven Non-Technical Enterprise AI Career Paths@2x-min

Seven Non-Technical Enterprise AI Career Paths

Relying entirely on consultants or vendors is not a viable strategy - as AI adoption inherently involves new capabilities to be built up within the company, both technical and non-technical. The only reason a company would put AI technical development and implementation entirely in the hands of a vendor is ignorance of how AI works.

Getting Past the IT Barrier to AI Adoption

Getting Past the IT Barrier to AI Adoption – Strategies of the Most Successful Vendors

AI adoption involves more than educating stakeholder groups (SMEs, IT, leadership) on the technical nuances of AI. It involves navigating human motives and incentives.

AI Knowledge Retention in the Enterprise - Making the Most of Lessons Learned 950x540

AI Knowledge Retention in the Enterprise – Making the Most of Lessons Learned

Novice AI project leaders measure projects entirely by (unrealistic) near-term financial benchmarks.

_The Enterprise AI Catalyst Manifesto 950×540

The AI Catalyst Manifesto – Education as the Key to Enterprise AI Transformation

Artificial intelligence isn't making its way into enterprise deployments easily. Despite a relatively widespread understanding that AI is an inevitable force for winning market share and serving customers, by name estimates some 80-90% of AI projects fail.

Discovering AI Opportunities Starts with the Right Team 950x540

Discovering AI Opportunities Starts with the Right Team

Vetting AI opportunities implies a hodge-podge of contextual knowledge that are almost never to be found together in a single expert, including (but not limited to) an understanding of:

An Enterprise Innovation Leader's Guide to Successful AI Adoption

An Enterprise Innovation Leader’s Guide to Successful AI Adoption

This article was a request from one of our Catalyst Advisory Program members. The Catalyst Advisory Program is an application-only business growth coaching program  for AI consultants and AI service providers. The program helps AI consulting and services leaders win more deals and deliver more client value. Members receive one-to-one advisory, group coaching, and proprietary Catalyst AI best-practice frameworks. Learn more or apply at: emerj.com/catalyst.

Selling AI Services to Smaller Enterprises - Leading with Education 950x540

Offering AI Services to Smaller Enterprises – Lead with Education

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

Executive AI Fluency

Executive AI Fluency – Ending the Cycle of Failed AI Proof-of-Concept Projects

Despite the billions of dollars being poured into AI startups and applications - it is common knowledge that most enterprise AI initiatives fail.

The AI Product Manager - A Key Role for the Future of AI Deployment

The AI Product Manager – A Key Role for the Future of AI Deployment

In the 1990's, Ben Horrowitz described a product manager as follows:
"A good product manager is the CEO of a product."
That definition isn't always a perfect fit, but it can be a good way of summarizing the responsibilities of a product manager; they are wholly in charge of bringing an in-house product from inception to generating an ROI. 

Retraining and Reskilling for AI

Retraining and Reskilling for AI – The State of AI Job Loss Today

One of the many concerns that business leaders have around automation is how they're going to adapt their workforce to new technology. The digital age has brought a rapid shift in the skillsets employees need to go about their jobs effectively, leaving little time for business leaders to come up with strategies for how to reskill and retrain their employees, prevent their companies from drawing disdain from the public, and how to compete with their peers.

Critical Capabilities - The Prerequisites to Successful AI Deployment

Critical Capabilities – The Prerequisites to AI Deployment in Business

Over the last four years, interviewing hundreds of AI researchers and AI enterprise leaders, we've consistently heard the same frustrations about AI adoption said time and time again.
"Culture is hard to change."
"Leadership doesn't know what they're trying to accomplish."
"Nobody knows what to do with these data scientists we've hired."
etc...
In our one-to-one work with enterprise clients, we've taken the most prevalent, recurring challenges to AI deployment and put them together into a framework of "prerequisites" to AI deployment.

A Pathway to Career Acceleration

A Pathway to Career Acceleration – Getting Started with AI

In this article, I'll showcase 6 examples of nontechnical professionals who used their business and subject-matter expertise (not their coding ability) to have more exciting careers in AI, and I respond directly a number of questions and comments from Emerj subscribers about AI knowledge for career advancement.

AI Knowledge as a Career Accelerator 2 950x540

AI Frameworks for Success – Bring Value to Any AI Initiative as a Non-Technical Professional

This is the second article in our "AI for Career Acceleration" series - be sure to read the first installment (and watch the video on that page).

AI Knowledge as a Career Accelerator 1 950x540

The AI Career Gap – AI Knowledge as a Career Accelerator

Last month we ran a podcast series on the AI in Industry podcast on the theme of “Advancing Your Career in the Era of AI”, with a focus on how non-technical professionals can become more valuable in the market, and can become involved in AI projects and initiatives, without ever learning to code.
I received twice as much feedback on this series as any other series we’ve ever run on the podcast - which surprised me.
It surprised me because I think about everything on Emerj.com as being useful for nontechnical professionals. We’ve built our editorial calendar and our products around the needs of nontechnical professionals who want to make the most of their careers, but this recent series spoke to that topic directly.
But hitting directly on the theme of “Advancing Your Career in the Era of AI” clearly hit a cord.
For that reason, I’ve decided to release a three-part video and article series on that same topic, breaking down the lessons that were most important for me - and sharing a bit of my own story going from small-town martial arts instructor to international AI speaker and strategist.
Before getting into the small-town martial arts instructor part, I’d like the share a pivotal Silicon Valley conversation that changed the course of my career:

Should I Go to an AI Event - How to Decide Which Events to Attend

Should I Go to an AI Event? How to Decide Which Events to Attend

Should I attend an artificial intelligence event or not?

What event should I go to?

Should I go to this event?

Feature Engineering for Applying AI in Business

Feature Engineering for Applying AI in Business – An Executive Guide

We talk a lot about the concept of connective tissue here at Emerj, the fact that a company that wants to apply AI not only needs to have access to data, not only needs to hire normally very expensive artificial intelligence talent, but also has to have the connective tissue of related subject-matter experts who can work with that talent.

Applying AI in Business - The Critical Role of Subject-Matter Experts

Applying AI in Business – The Critical Role of Subject-Matter Experts

We have discussed the importance of having the right talent in place when it comes to AI adoption in enterprise quite thoroughly here at Emerj. The scarcity of data science talent and its price point are one of the main reasons small businesses are not likely to adopt AI successfully at this time.

Successful

What Successful AI Vendors Do – An Executive Brief

For a tech subsector on everyone's proverbial lips' at the moment, things can hardly be described as 'easygoing' for the AI vendor startup market in 2023.

AI Delivery Partners - How Consultants Contract AI Talent Before Hiring

AI Delivery Partners – How Consultants Contract AI Talent Before Hiring

Most early stage AI consulting firms don’t have the budget to hire expensive machine learning talent. For non-technical founders who can’t do the ML engineering themselves, this means getting creative when it comes to AI project delivery.

Emerj AI Framing Scale

Achieving Sustainable AI Adoption with the AI Framing Scale

How AI project leaders provide the best chance at sustainable success in AI adoption?

The answer is simple: Frankly communicate both near-term and long-term value, and help leadership understand the importance of seeing measurable results, and the value of building a stronger AI foundation for future projects.

The B2B AI Growth Loop

The “Growth Loop” – A Deliberate Go-to-Market Approach for AI Firms

Most AI product firms are founded and grown in a similar way.

It usually goes something like this:

Five Non-Technical AI Business Models 950x540

Five Non-Technical AI Services Business Models

When most professionals think about “AI consulting” they tend to think about technical machine learning services, like: Building our data infrastructure, crafting and testing new algorithms, interesting AI systems into existing IT infrastructure.

Building Your AI Product Development Roadmap - Recommendations for Startups and Enterprise Leaders

Building Your AI Product Development Roadmap – Recommendations for Startups and Enterprise Leaders (Part 3 of 3)

This article is the third in a series part in a series about AI product development.

In the first installment in this series, we covered how to develop AI product ideas with both near-term adopt-ability and long-term potential.

Ranking AI Product or Service Ideas - Determine the Best Product to Build

Ranking AI Product or Service Ideas – Determine the Best Product to Build (Part 2 of 3)

So you've decided you want to take an AI product or service to market.

Before you sell anything - you'll have to decide what kind of product or service to develop.

AI Product Development_ Winning in the Near-Term and Long-Term

Developing AI Products: Winning in the Near-Term and Long-Term (Part 1 of 3)

Whether you're a startup or an enterprise, developing AI products is challenging.

Not only do you have to wrestle with the challenges of finding a use-case that where AI can actually deliver value into an enterprise workflow, but you also have UI concerns, and - often - much higher demands to monitor algorithmic drift and other technical issues.

The Role of thought Leadership in Marketing AI Products and Services

The Role of Thought Leadership in Marketing AI Products and Services

In this article, I'll explore some of our lessons learned in getting the value of AI products or services to stick with enterprise buyers.

How to Build an Enterprise AI Roadmap

How to Build an Enterprise AI Roadmap – A Four-Step Process

The firms that will gain a genuine advantage from AI deploy the technology in a way that achieves short-term ROI, alignment to a long-term vision, and conscious development of AI maturity - including skills, data infrastructure, and more.

Developing the Market Message for an AI Product or Service - Separating "Attraction" and "Positioning" Themes

Developing the Market Message for an AI Product or Service – Finding a “Core Message” That Works

Over the last three years, Emerj has had the privilege to work on hundreds of individual thought leadership and lead generation campaigns for AI companies around the world - via our Creative Services arm.

Developing AI Products or Services - Selecting Your Niche

Developing AI Products or Services – Four Ways to Select a Niche

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

Comparing 5 AI Business Models - Part 2 950x540

Comparing 5 AI Business Models – Part 2 – Pros and Cons from Vendor Perspective

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

Comparing 5 AI Business Models - Part 1 950x540

Comparing 5 AI Business Models – Part 1 – Transformation or Near-Term Value?

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

The Four Keys to to Selling AI Services to the Enterprise

The Four Keys to Selling AI Services to the Enterprise

While AI vendor companies proliferate in every sector, enterprises need much more than advanced technologies to actually adopt and deploy AI. AI services and consulting firms are expanding to fill the gap - offering services that enterprises often don't have the in-house talent for, including:

Enterprise AI Buyers

Who Buys AI? Common Roles and Titles of Enterprise AI Buyers

This article was a request from one of our Catalyst members.

The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more and apply emerj.com/catalyst.

Selling AI Services to Smaller Enterprises - Leading with Education 950x540

Offering AI Services to Smaller Enterprises – Lead with Education

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

AI Vendor Selection

Three Phases of AI Vendor Selection for the Enterprise 

When we're called into an enterprise for our AI Opportunity Landscape research, it's common for me to discover that the reason we've been called in is that the company has (a) already spent millions with vendors they didn't see results with, or (b) they have 3-4 AI pilots underway with very little traction.

Identify Enterprise Firms Most Likely to Spend on AI Projects

Identify Enterprise Firms Most Likely to Spend on AI Projects

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

The 3 Elements of a Successful AI Business Case

The Three Elements of a Successful AI Business Case

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

How to Succeed with AI Projects - Lead with Strategy

How to Succeed with AI Projects – Lead with Strategy

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

3 Content Marketing Principles for AI Products and Services

3 Content Marketing Principles for AI Products and Services

Content marketing encompasses many ways to advertise and attract new potential customers. At Emerj, we've worked on hundreds of campaigns for AI-related products and services, and what we've learned is that content marketing for AI vendors boils down to two things:

How to Convert More Leads for AI Products and Services

How to Convert More Leads for AI Products and Services

Companies often emphasize artificial intelligence on their homepage or on services pages. While AI is currently an important topic, a simple mention of it on a website’s homepage will not get potential customers interested. Instead, it is more important to focus on the direct needs of the stakeholders who find an AI vendor website and their online properties in order to get them closer to a sale. 

Go-to-Market Strategy for an AI Product - From Insight to Action Plan (Part 3 of 3)

Go-to-Market Strategy for an AI Product – From Insight to Action Plan (Part 3 of 3)

Welcome to part three of this three-part series on go-to-market strategy for an artificial intelligence product or service. In part one we talked about what kind of insights you want to get out of a go-to-market strategy. In part two we talked about how those insights are gleaned.

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Go-to-Market Strategy for an AI Product – Building the Strategy (Part 2 of 3)

In part one of this series, we talked about what insights to get out of a go-to-market strategy project. In this second installment, we're going to be diving into how to get those insights.

Go-to-Market Strategy for an AI Product - What to Discover (Part 1 of 3)

Go-to-Market Strategy for an AI Product – What to Discover (Part 1 of 3)

When clients come to us for custom research projects, sometimes it's because it's a big firm that's looking to make acquisitions or it's a company that's looking for some kind of competitive intelligence. They're looking at who else is offering things like them and how they can position themselves against those other competitors in the market.

Spot Fake AI Companies Quickly - Look out for the Fake AI Rebrand

Spot Fake AI Companies Quickly – Look Out for the Fake AI Rebrand

We've seen a lot of what we call "fake AI rebrands" in the last 18 months, and I suspect that as long as AI is a buzzword, we will only see more and more of this. Business leaders are going to have to keep their eyes peeled for these kinds of companies in their midst.

"Psuedo-AI" and When It's Okay for Humans to be Behind the AI

Pseudo-AI – When “AI” is Really a Human, but That Might be Okay

One of the biggest problems facing business executives when it comes to adopting AI is determining whether a company is truly leveraging AI or simply using the term as a marketing strategy. We have discussed rules of thumb for assessing the authenticity of AI companies in previous articles based on insights derived from hundreds of interviews with industry experts and AI researchers over time.

How to Tell if an AI Company is Lying About Using AI

7 Ways to Tell if an AI Company is Lying About Using AI

A few months ago, we spoke about three rules of thumb for assessing companies and trying to figure out if they are really doing AI or just using it for marketing purposes in our How to Cut Through the Artificial Intelligence Hype piece. Since it was so popular, I was inspired to write this follow-up.

How to Cut Through the Artificial Intelligence Hype - Three Simple "Rules of Thumb"

How to Cut Through the Artificial Intelligence Hype – Three Simple “Rules of Thumb”

Artificial intelligence and machine learning are hot terms right now, and many companies are eager to talk about how their products rely on these cutting edge technologies. Established companies and startups want to explain how AI is a critical part of their business.

7 Critical Factors for Developing an AI Strategy

7 Critical Factors for Developing an AI Strategy

Many books could be written on the subject of AI strategy, and we've seen that "strategy" means something different from one enterprise to the next. This article is a brief overview of the common steps in creating an AI strategy - in roughly the order that the steps are usually executed.

How AI Champions Can Thrive Amidst COVID-19 Disruption 950x540

How AI Champions Can Thrive Amidst COVID-19 Disruption

Amidst the uncertainty of COVID19, our polls and surveys of enterprise leaders have show two trends to be consistent:

Picking a First AI Project - A 3-Step Guide for Leaders 950x540

Picking a First AI Project – A 3-Step Guide for Leaders

Artificial intelligence is poised to change every industry - and to create trillions in economic value over the coming decades.

The Survival of AI Startups in the COVID Crisis

The Survival of AI Startups in the COVID Crisis – and Implications for Business

At Emerj, for over three years, we've been tracking the development of artificial intelligence startups and solution providers across industries, speaking to founders and team members and communicating with the enterprise leaders and buyers who depend on this ecosystem of AI solutions. 

How the Coronavirus Will Change AI Innovation in Insurance

How the Coronavirus Will Change AI Innovation in Insurance

The insurance industry is being disrupted like it hasn't in decades. Unlike other events like Hurricane Sandy or even the 2008 financial crisis, the coronavirus is impacting essentially every corner of the world and more or less every industry.

AI Strategy in the Coronavirus Era - a Business Leader's Guide

AI Strategy in the Coronavirus Era – a Business Leader’s Guide

In the last two articles in this 3-part series, we discussed how AI priorities will shift in response to the coronavirus pandemic, as well as how companies can further leverage the advantages they have (and can create) to overcome the challenges they are facing in this uncertain time. 

AI Advantages and Challenges in the Coronavirus Era

AI Advantages and Challenges in the Coronavirus Era

At Emerj, our research involves tracking AI and innovation across industries, dialing into where AI is driving ROI, which we do through our AI Opportunity Landscape research. In these hard times, we're expecting many AI startups to fade away and many technology priorities within large enterprises to completely shift to be more in line with what we're going to be articulating in this article. 

New AI Priorities in the COVID19 Era 950x540

New Artificial Intelligence Priorities in the COVID-19 Era

The COVID19 outbreak has changed the world faster than anyone could have imagined.

Forced isolation has shifted meetings and activities to go on through web collaboration tools.

Insurance AI Use-Cases 
and Trends@2x

Insurance Use Cases and Trends – An Executive Guide

Insurers have been long aware of the perfect storm of converging market trends pointing to the permanency of digital disruption and change. Yet, the industry – especially the big players – always seemed to move their collective house further away from the shoreline. 

Successful

What Successful AI Vendors Do – An Executive Brief

For a tech subsector on everyone's proverbial lips' at the moment, things can hardly be described as 'easygoing' for the AI vendor startup market in 2023.

Artificial Intelligence at DHL@2x-min

Artificial Intelligence at DHL – Two Applications at the World’s Largest Logistics Company

DHL is a German logistics company that offers parcel delivery, express mail, freight forwarding, and third-party logistics. Its parent company is Deutsche Post (‘DPDHL’), the world’s largest logistics enterprise, operating in over 220 countries and employing more than 510,000 people worldwide. 

The Importance of NLP in Insurance@2x-min

The Importance of NLP in Insurance – with Gero Gunkel of Zurich Insurance

Although not often regarded as a technological first-mover, the insurance industry has recently seen robust, even rapid, adoption and deployment of AI capabilities, particularly in those related to natural language processing (NLP). 

Bringing Intelligence to Manufacturing and Maintenance@2x-min

Bringing Intelligence to Manufacturing and Maintenance – with Peter Tu of GE Research

A paradigm shift is happening in the manufacturing industry. Advancement in big data and machine learning is changing traditional manufacturing processes into the era of intelligent manufacturing. The concept of what gets called "industry 4.0" encourages the use of smart sensors, devices, and machines – going beyond the motives of collecting data about production. 

The Importance of Real-Time Telemetric Data in Manufacturing@2x-min

The Importance of Real-Time Telemetric Data in Manufacturing – with Remi Duquette of Maya HTT

The manufacturing industry has changed in recent years. Humans on the shop floor have always used their senses and experience to anticipate machine failure before it occurs. Now, AI can be used in conjunction with human expertise.

Emerj.com – 001 – AI at ExxonMobil-min

Artificial Intelligence at ExxonMobil – Two Applications at the Largest Western Oil Company

ExxonMobil is the largest investor-owned company in the world and the largest oil company by revenue in the Western world.

Personalizing Product Recommendations 
at Walmart@2x-min

Personalizing Product Recommendations at Walmart – with Dr. Charles Martin

The en masse shift to online shopping that transpired during and post-COVID appears as if it's destined to last. According to the Brookings Institute, one third of US adults have used delivery apps to order from a restaurant or store in the last year. 

Seven Non-Technical Enterprise AI Career Paths@2x-min

Seven Non-Technical Enterprise AI Career Paths

Relying entirely on consultants or vendors is not a viable strategy - as AI adoption inherently involves new capabilities to be built up within the company, both technical and non-technical. The only reason a company would put AI technical development and implementation entirely in the hands of a vendor is ignorance of how AI works.

AI Use Cases for Trust Automation in Insurance@2x-min

AI Use Cases for Trust Automation in Insurance – with Christian van Leeuwen of FRISS

Insurance is a growing arena for AI adoption and in many cases, automation is leading the way to streamline customer experiences and the organizational pipelines behind them along the entire customer journey.

What AI Means for Financial Services in a Post-COVID World@2x-min

Early AI Adoption: How to Avoid Classic Mistakes – With David Carmona of Microsoft

The main difficulty in starting with AI is knowing exactly where to begin. As we will elaborate in this article, there are many exaggerated and misleading claims about the various types of AI technology. Moreover, some executives are too trigger-happy, wanting or needing to integrate AI into their enterprise sans a foundational education or understanding of the challenges. 

Building an AI Strategy Step-by-Step@2x

Building an AI Strategy, Step-by-Step – with Dr. Shane Zabel of Raytheon

What does developing an AI strategy look like? Most executives openly embrace the technology and the automation possibilities within their organization. They may just need a bit of help getting started.

What GPT-3 and AI Generated Text Means for the Future of Written Content@2x

What GPT-3 and AI-Generated Text Means for the Future of Written Content – with Peter Welinder of OpenAI

It is not hyperbolic to state that the autoregressive language model known as GPT-3 (short for ‘Generative Pre-trained Transformer 3’) is an unparalleled evolutionary step in content creation. In fact, the potential outputs the model can produce are so advanced that many academics have cited GPT-3 as Exhibit A in calling universities to reconsider what constitutes academic plagiarism. 

Using Decision Augmentation for Client Retention@2x

Using Decision Augmentation for Client Retention – with Emily Bremner of Signal AI

Actionable, decision-augmenting data can be obtained internally or externally. Of course, external data is a far richer and more diverse source, as it comprises every other piece of digital information outside of the four walls of an enterprise. 

Making AI Projects Easier to Manage

Making AI Projects Easier to Manage – and More Like IT Projects

Increasingly, technology and business leaders look to AI project managers to make the execution (and success) of their AI projects more predictable. Executives and decision makers want AI projects to mature so they are more like the software development projects that have been with us for a generation. But, any AI project manager hoping to deliver on those expectations knows that success in AI projects requires an end-to-end thinking rarely found today.

AI Delivery Partners - How Consultants Contract AI Talent Before Hiring

AI Delivery Partners – How Consultants Contract AI Talent Before Hiring

Most early stage AI consulting firms don’t have the budget to hire expensive machine learning talent. For non-technical founders who can’t do the ML engineering themselves, this means getting creative when it comes to AI project delivery.

Emerj AI Framing Scale

Achieving Sustainable AI Adoption with the AI Framing Scale

How AI project leaders provide the best chance at sustainable success in AI adoption?

The answer is simple: Frankly communicate both near-term and long-term value, and help leadership understand the importance of seeing measurable results, and the value of building a stronger AI foundation for future projects.

Incubating AI Projects - The Crucial Phase Between Pilot and Deployment

Incubating AI Projects – The Crucial Phase Between Pilot and Deployment

Artificial intelligence projects are more like R&D than they are like traditional IT. It is experimentation as much as it is adoption, and this difference is one of many reasons that AI projects take longer to integrate, and often hit bottlenecks that prevent them from being used in production.

The B2B AI Growth Loop

The “Growth Loop” – A Deliberate Go-to-Market Approach for AI Firms

Most AI product firms are founded and grown in a similar way.

It usually goes something like this:

What Makes AI Projects Different from IT Projects

What Makes AI Projects Different from IT Projects

One of the biggest hurdles to AI adoption and integration is a lack of proper expectations about applying AI in an existing business. Executives and their teams often go into the process blind because so few companies have learned these important lessons and challenges and because even fewer have successfully adopted AI in a way that delivers ROI.

Document Search and Discovery in Banking - An Analysis of the Field

An Analysis of AI-Powered Document Search Capabilities in Banking

The financial services industry is buried in paperwork, and the NLP use-cases in banking and insurance grow every year.

Three Ways to Leverage Industry Expertise for an AI Career

Three Ways to Leverage Industry Expertise for an AI Career – A Guide for Non-Technical Leaders

As artificial intelligence makes its way into more industries and workflows, more and more non-technical team members will be charged with leading AI projects. The next wave of AI catalysts will be familiar with AI at a conceptual level (read: executive AI fluency), but will mostly be expert in bridging AI's capabilities to important business workflows and objectives.

Five Non-Technical AI Business Models 950x540

Five Non-Technical AI Services Business Models

When most professionals think about “AI consulting” they tend to think about technical machine learning services, like: Building our data infrastructure, crafting and testing new algorithms, interesting AI systems into existing IT infrastructure.

Bridging Business Needs and Data Assets

Bridging Business Needs and Data Assets – Emerj AI Leader Insight

In the vast land of opportunities that AI creates, how do we select the projects that will generate ROI? Do we gain inspiration from reading AI use-cases relevant to our industries? Do we search through our own lists of existing priorities and hope the applications for AI will become clear?

Getting Past the IT Barrier to AI Adoption

Getting Past the IT Barrier to AI Adoption – Strategies of the Most Successful Vendors

AI adoption involves more than educating stakeholder groups (SMEs, IT, leadership) on the technical nuances of AI. It involves navigating human motives and incentives.

Going from Pilot to Deployment with AI

Going from Pilot to Deployment with AI – 4 Factors to Consider

While overt AI "flops" are less common than they were three years ago, the pattern of failure for AI projects is still much the same.

Near-Term Value vs. AI Transformation - Emerj’s AI Project Quadrant

Near-Term Value vs. AI Transformation – Emerj’s AI Project Quadrant

You can invest in AI maturity and future capability - or you can have "quick wins" with surface-level AI applications that have relatively short-term, narrow ROI.

Selecting Early AI Projects with Emerj's Bullseye Model

Enterprise AI Project Selection – Emerj’s “Bullseye” Model

Picking first AI projects is challenging - and leadership is right to be wary of making the wrong investment. The challenge lies in both (a) identifying the right projects, and (b) ranking and determining the right ones.

Building Your AI Product Development Roadmap - Recommendations for Startups and Enterprise Leaders

Building Your AI Product Development Roadmap – Recommendations for Startups and Enterprise Leaders (Part 3 of 3)

This article is the third in a series part in a series about AI product development.

In the first installment in this series, we covered how to develop AI product ideas with both near-term adopt-ability and long-term potential.

Ranking AI Product or Service Ideas - Determine the Best Product to Build

Ranking AI Product or Service Ideas – Determine the Best Product to Build (Part 2 of 3)

So you've decided you want to take an AI product or service to market.

Before you sell anything - you'll have to decide what kind of product or service to develop.

AI Product Development_ Winning in the Near-Term and Long-Term

Developing AI Products: Winning in the Near-Term and Long-Term (Part 1 of 3)

Whether you're a startup or an enterprise, developing AI products is challenging.

Not only do you have to wrestle with the challenges of finding a use-case that where AI can actually deliver value into an enterprise workflow, but you also have UI concerns, and - often - much higher demands to monitor algorithmic drift and other technical issues.

The Role of thought Leadership in Marketing AI Products and Services

The Role of Thought Leadership in Marketing AI Products and Services

In this article, I'll explore some of our lessons learned in getting the value of AI products or services to stick with enterprise buyers.

Finding the Enterprise Fit for AI

Finding the Enterprise Fit for AI – Emerj AI Leader Insight

In the classic business book Good to Great, author Jim Collins talks about the different approaches for technology adoption between high-performing and average companies. Collins' research indicated that high performers tend to adopt technology as an accelerant to an existing, working strategy - while underperformers tended to adopt technology in an attempt to jumpstart a change in direction or strategy that they haven't yet undertaken.

The Range of AI Capabilities in Document Search and Discovery

The Range of AI Capabilities in Document Search and Discovery

Over the last three years of AI Opportunity Landscape research, we've examined many broad capabilities across the AI ecosystem, from computer vision to conversational interfaces to anomaly detection and beyond. Some of our earliest client research work focused on back-office automation - mostly in financial services and healthcare - and it brought us face-to-face with an array of vendors, use-cases, and opportunities for applying AI for document search and discovery.

AI Knowledge Retention in the Enterprise - Making the Most of Lessons Learned 950x540

AI Knowledge Retention in the Enterprise – Making the Most of Lessons Learned

Novice AI project leaders measure projects entirely by (unrealistic) near-term financial benchmarks.

How to Build an Enterprise AI Roadmap

How to Build an Enterprise AI Roadmap – A Four-Step Process

The firms that will gain a genuine advantage from AI deploy the technology in a way that achieves short-term ROI, alignment to a long-term vision, and conscious development of AI maturity - including skills, data infrastructure, and more.

The 7 Steps of the Data Science Lifecycle

The 7 Steps of the Data Science Lifecycle – Applying AI in Business

AI is not IT- and adopting artificial intelligence is almost nothing like adopting traditional software solutions.

The 3 Phases of Enterprise AI Deployment

The 3 Phases of Enterprise AI Deployment

Making AI work has a lot to do with "getting things right" even before a project starts, including:

Developing the Market Message for an AI Product or Service - Separating "Attraction" and "Positioning" Themes

Developing the Market Message for an AI Product or Service – Finding a “Core Message” That Works

Over the last three years, Emerj has had the privilege to work on hundreds of individual thought leadership and lead generation campaigns for AI companies around the world - via our Creative Services arm.

Industries Leading in AI Adoption

Industries Leading in AI Adoption – eCommerce, FinTech, Online Media

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

Creating an AI Transformation Vision

Creating an AI Transformation Vision – Achieving Long-Term Advantage with AI

Artificial intelligence deployments are fraught with technical and tactical elements that have to be executed well in order to see a return on investment: The data must be accessible, cross-functional AI teams have to work together, and even after an AI pilot seems promising - it often needs to be integrated into legacy systems to be deployed successfully.

Building AI Maturity in the Enterprise

Building AI Maturity in the Enterprise – A Guide for Consultants and Enterprise Leaders

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

The 4 Horsemen of the AI-pocalypse

The 4 Horsemen of the AI-pocalypse – Why Enterprises Fail to Adopt AI

This is a contributed article by Ian Wilson, Founder at Strategy 4 AI - learn more about Ian's online AI strategy courses here. Ian is also the former Head of AI for HSBC, one of the largest financial institutions in the world. To inquire about contributed articles from outside experts, contact [email protected].
As the use of AI to support business operations moves through its maturity cycle we have passed a number of key milestones along the way. However, following a pattern reminiscent of previous emerging technology introductions, organizations initially hired experts only to balk when they used blasphemous words like "infrastructure," "industrialize" or "strategy" rather than soothing words like "use case," "quick win" or "easy ROI." 
Unfortunately, instead of sacrificing their misaligned expectations, many businesses sacrificed their experts... 
Fast forward a couple of years and many of those businesses, having attempted to cut corners and seeing mainly failure, now have a visceral understanding of what their experts were advising and are looking, with more experienced eyes, at how to move forward from this point.
However, many businesses are still making avoidable mistaken assumptions when it comes to the use of AI Capabilities to support business objectives. I like to call the most egregious of these assumptions The 4 Horsemen of the AI-Pocolypse:

The 3 Most Popular AI Application Types Across Industries

The 3 Most Popular AI Application Types Across Industries

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

_The Enterprise AI Catalyst Manifesto 950×540

The AI Catalyst Manifesto – Education as the Key to Enterprise AI Transformation

Artificial intelligence isn't making its way into enterprise deployments easily. Despite a relatively widespread understanding that AI is an inevitable force for winning market share and serving customers, by name estimates some 80-90% of AI projects fail.

Setting the Right AI Expectations 950x540

Setting the Right AI Expectations – A Key for Turning Pilots into Deployments

Setting expectations.

In our ongoing poll of new Emerj Plus members indicates that in addition to "accessing more AI use-cases" and "measuring AI ROI," our members consistently tell us that they join in order to "set expectations for AI projects" - especially with leadership.

7 Critical Factors for Developing an AI Strategy

7 Critical Factors for Developing an AI Strategy

Many books could be written on the subject of AI strategy, and we've seen that "strategy" means something different from one enterprise to the next. This article is a brief overview of the common steps in creating an AI strategy - in roughly the order that the steps are usually executed.

Developing AI Products or Services - Selecting Your Niche

Developing AI Products or Services – Four Ways to Select a Niche

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

How AI Champions Can Thrive Amidst COVID-19 Disruption 950x540

How AI Champions Can Thrive Amidst COVID-19 Disruption

Amidst the uncertainty of COVID19, our polls and surveys of enterprise leaders have show two trends to be consistent:

Establishing Measurable ROI Benchmarks for AI Projects

Establishing Measurable ROI Benchmarks for AI Projects – A 5-Step Process

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/plus.

Discovering AI Opportunities Starts with the Right Team 950x540

Discovering AI Opportunities Starts with the Right Team

Vetting AI opportunities implies a hodge-podge of contextual knowledge that are almost never to be found together in a single expert, including (but not limited to) an understanding of:

Comparing 5 AI Business Models - Part 2 950x540

Comparing 5 AI Business Models – Part 2 – Pros and Cons from Vendor Perspective

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

Comparing 5 AI Business Models - Part 1 950x540

Comparing 5 AI Business Models – Part 1 – Transformation or Near-Term Value?

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

The Three Kinds of AI ROI - Emerj's Trinity Model 950x540

The Three Kinds of AI ROI – Emerj’s Trinity Model

AI vendors and enterprise buyers struggle to get on the same page about the return on investment (ROI) of AI solutions.

Picking a First AI Project - A 3-Step Guide for Leaders 950x540

Picking a First AI Project – A 3-Step Guide for Leaders

Artificial intelligence is poised to change every industry - and to create trillions in economic value over the coming decades.

An Enterprise Innovation Leader's Guide to Successful AI Adoption

An Enterprise Innovation Leader’s Guide to Successful AI Adoption

This article was a request from one of our Catalyst Advisory Program members. The Catalyst Advisory Program is an application-only business growth coaching program  for AI consultants and AI service providers. The program helps AI consulting and services leaders win more deals and deliver more client value. Members receive one-to-one advisory, group coaching, and proprietary Catalyst AI best-practice frameworks. Learn more or apply at: emerj.com/catalyst.

The Four Keys to to Selling AI Services to the Enterprise

The Four Keys to Selling AI Services to the Enterprise

While AI vendor companies proliferate in every sector, enterprises need much more than advanced technologies to actually adopt and deploy AI. AI services and consulting firms are expanding to fill the gap - offering services that enterprises often don't have the in-house talent for, including:

Enterprise AI Buyers

Who Buys AI? Common Roles and Titles of Enterprise AI Buyers

This article was a request from one of our Catalyst members.

The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more and apply emerj.com/catalyst.

Selling AI Services to Smaller Enterprises - Leading with Education 950x540

Offering AI Services to Smaller Enterprises – Lead with Education

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

AI Vendor Selection

Three Phases of AI Vendor Selection for the Enterprise 

When we're called into an enterprise for our AI Opportunity Landscape research, it's common for me to discover that the reason we've been called in is that the company has (a) already spent millions with vendors they didn't see results with, or (b) they have 3-4 AI pilots underway with very little traction.

Identify Enterprise Firms Most Likely to Spend on AI Projects

Identify Enterprise Firms Most Likely to Spend on AI Projects

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

The 3 Elements of a Successful AI Business Case

The Three Elements of a Successful AI Business Case

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

How to Succeed with AI Projects - Lead with Strategy

How to Succeed with AI Projects – Lead with Strategy

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is a coaching program involving one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks based on insights from AI leaders at the world’s largest enterprises (AI adopters and buyers), and successful AI vendors and service providers. Learn more and apply emerj.com/catalyst.

The Survival of AI Startups in the COVID Crisis

The Survival of AI Startups in the COVID Crisis – and Implications for Business

At Emerj, for over three years, we've been tracking the development of artificial intelligence startups and solution providers across industries, speaking to founders and team members and communicating with the enterprise leaders and buyers who depend on this ecosystem of AI solutions. 

Executive AI Fluency

Executive AI Fluency – Ending the Cycle of Failed AI Proof-of-Concept Projects

Despite the billions of dollars being poured into AI startups and applications - it is common knowledge that most enterprise AI initiatives fail.

Machine Learning in Payments - an Overview in Disruptive Times

Machine Learning in Payments – an Overview in Disruptive Times

The coronavirus pandemic has ushered in a new era of digital payments; those who once mailed checks and made purchases in person are now paying their bills electronically and shopping online. As the economy is rattled by the coronavirus, there are some AI startups in the payments space that will succeed and others that will fail. All are pivoting rapidly to eCommerce, if that wasn't already their focus to begin with.

How to Deploy AI for Fraud Detection in Financial Services

How to Deploy AI for Fraud Detection in Financial Services

Fraud, money laundering, and other cyber crimes often increase in times of economic strife, and the pandemic is no different. In light of the coronavirus crisis, we believe that fraud detection applications are among the AI use-cases that are most likely to be adopted and deployed even when funds dry up for other kinds of more long-term, strategic innovation investments.

Artificial Intelligence and the Future of Supply Chain and Logstics

Artificial Intelligence and the Future of Supply Chain and Logistics

Supply chains contain every material, component, product and packaging for the objects that together compose the world we live in. However, there is an often invisible ingredient to successful supply chains: data. 

How the Coronavirus Will Change AI Innovation in Insurance

How the Coronavirus Will Change AI Innovation in Insurance

The insurance industry is being disrupted like it hasn't in decades. Unlike other events like Hurricane Sandy or even the 2008 financial crisis, the coronavirus is impacting essentially every corner of the world and more or less every industry.

AI Strategy in the Coronavirus Era - a Business Leader's Guide

AI Strategy in the Coronavirus Era – a Business Leader’s Guide

In the last two articles in this 3-part series, we discussed how AI priorities will shift in response to the coronavirus pandemic, as well as how companies can further leverage the advantages they have (and can create) to overcome the challenges they are facing in this uncertain time. 

AI Advantages and Challenges in the Coronavirus Era

AI Advantages and Challenges in the Coronavirus Era

At Emerj, our research involves tracking AI and innovation across industries, dialing into where AI is driving ROI, which we do through our AI Opportunity Landscape research. In these hard times, we're expecting many AI startups to fade away and many technology priorities within large enterprises to completely shift to be more in line with what we're going to be articulating in this article. 

New AI Priorities in the COVID19 Era 950x540

New Artificial Intelligence Priorities in the COVID-19 Era

The COVID19 outbreak has changed the world faster than anyone could have imagined.

Forced isolation has shifted meetings and activities to go on through web collaboration tools.

The AI Product Manager - A Key Role for the Future of AI Deployment

The AI Product Manager – A Key Role for the Future of AI Deployment

In the 1990's, Ben Horrowitz described a product manager as follows:
"A good product manager is the CEO of a product."
That definition isn't always a perfect fit, but it can be a good way of summarizing the responsibilities of a product manager; they are wholly in charge of bringing an in-house product from inception to generating an ROI. 

The ROI of Machine Learning - 3 Strategies for Measurable Results

The ROI of Machine Learning – 3 Strategies for Measurable Results

Many business leaders make the mistake of believing that AI and machine learning are like regular IT, but this could not be further from the truth. In large part, this is because, unlike simple software solutions for discreet business problems, it can be very difficult to measure the ROI of machine learning.

Near-Term AI Trends and the ROI of AI – An Overview 950×540

Near-Term AI Trends – A Guide for Mid-Size Business Leaders

What is the state of AI in business today - and what do mid-market business leaders need to know about AI now?

Enterprises Don't Fear AI - But Fear is Their Greatest Motive in Adopting It

Enterprises Don’t Fear AI – But Fear is Their Greatest Motive in Adopting It

You might not know it when reading AI vendor websites or press releases from enterprises, but when you dig deep enough into why enterprises actual adopt AI, the pattern is clear:

3 Ways to Build a Competitive AI Advantage

3 Ways to Build a Competitive AI Advantage – An Executive Guide

Companies looking to apply AI are looking for a competitive advantage in their industry, something that will give them an edge in the market and help them grow. However, not every AI application can give a company a competitive advantage. Many AI applications are simply going to become the new normal.

Retraining and Reskilling for AI

Retraining and Reskilling for AI – The State of AI Job Loss Today

One of the many concerns that business leaders have around automation is how they're going to adapt their workforce to new technology. The digital age has brought a rapid shift in the skillsets employees need to go about their jobs effectively, leaving little time for business leaders to come up with strategies for how to reskill and retrain their employees, prevent their companies from drawing disdain from the public, and how to compete with their peers.

Critical Capabilities - The Prerequisites to Successful AI Deployment

Critical Capabilities – The Prerequisites to AI Deployment in Business

Over the last four years, interviewing hundreds of AI researchers and AI enterprise leaders, we've consistently heard the same frustrations about AI adoption said time and time again.
"Culture is hard to change."
"Leadership doesn't know what they're trying to accomplish."
"Nobody knows what to do with these data scientists we've hired."
etc...
In our one-to-one work with enterprise clients, we've taken the most prevalent, recurring challenges to AI deployment and put them together into a framework of "prerequisites" to AI deployment.

3 Content Marketing Principles for AI Products and Services

3 Content Marketing Principles for AI Products and Services

Content marketing encompasses many ways to advertise and attract new potential customers. At Emerj, we've worked on hundreds of campaigns for AI-related products and services, and what we've learned is that content marketing for AI vendors boils down to two things:

How to Convert More Leads for AI Products and Services

How to Convert More Leads for AI Products and Services

Companies often emphasize artificial intelligence on their homepage or on services pages. While AI is currently an important topic, a simple mention of it on a website’s homepage will not get potential customers interested. Instead, it is more important to focus on the direct needs of the stakeholders who find an AI vendor website and their online properties in order to get them closer to a sale. 

A Pathway to Career Acceleration

A Pathway to Career Acceleration – Getting Started with AI

In this article, I'll showcase 6 examples of nontechnical professionals who used their business and subject-matter expertise (not their coding ability) to have more exciting careers in AI, and I respond directly a number of questions and comments from Emerj subscribers about AI knowledge for career advancement.

Finding AI Trends

3 Ways to Discover AI Trends in Any Sector

Business leaders, managers, and consultants with an eye on AI aren’t just trying to learn what AI can do, they’re trying to discover ways to gain an AI advantage.

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AI Frameworks for Success – Bring Value to Any AI Initiative as a Non-Technical Professional

This is the second article in our "AI for Career Acceleration" series - be sure to read the first installment (and watch the video on that page).

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The AI Career Gap – AI Knowledge as a Career Accelerator

Last month we ran a podcast series on the AI in Industry podcast on the theme of “Advancing Your Career in the Era of AI”, with a focus on how non-technical professionals can become more valuable in the market, and can become involved in AI projects and initiatives, without ever learning to code.
I received twice as much feedback on this series as any other series we’ve ever run on the podcast - which surprised me.
It surprised me because I think about everything on Emerj.com as being useful for nontechnical professionals. We’ve built our editorial calendar and our products around the needs of nontechnical professionals who want to make the most of their careers, but this recent series spoke to that topic directly.
But hitting directly on the theme of “Advancing Your Career in the Era of AI” clearly hit a cord.
For that reason, I’ve decided to release a three-part video and article series on that same topic, breaking down the lessons that were most important for me - and sharing a bit of my own story going from small-town martial arts instructor to international AI speaker and strategist.
Before getting into the small-town martial arts instructor part, I’d like the share a pivotal Silicon Valley conversation that changed the course of my career:

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Predicting the ROI of AI – Pitfalls to AI Adoption in the Enterprise (Part 3 of 3)

In the final installment of the "Pitfalls to AI Adoption" series, we talk about predicting the ROI of AI. There are a lot of misconceptions running rampant around the ability to gauge the return on investment of artificial intelligence. In this article, we talk about what can and can't be done when it comes to investing in artificial intelligence and predicting what the return might be.

AI Integration Challenges - Pitfalls to AI Adoption

AI Integration Challenges – Pitfalls to AI Adoption in the Enterprise (Part 2 of 3)

In this second installment of the "Pitfalls to AI Adoption in the Enterprise" series, we're going to talk about underestimating the integration needs of artificial intelligence and machine learning.

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Avoid AI Novelty – Pitfalls to AI Adoption in the Enterprise (Part 1 of 3)

What's harder than training an algorithm to detect images or automate a process? Collecting and cleaning the data in the first place.

Artificial Intelligence in Corporate Banking - Current Applications

How to Discover the AI Initiatives of Fortune 500 Companies

There is always a fascination with what the biggest and most powerful companies in any given sector are doing. If you look in the world of eCommerce, everybody is ultimately referencing Amazon. In the world of banking, firms like JP Morgan are referred to and everyone's interested in their newest hires in terms of the C-suite and their newest innovations in terms of technology. Analyzing bigger firms seems to have a level-setting effect.

Go-to-Market Strategy for an AI Product - From Insight to Action Plan (Part 3 of 3)

Go-to-Market Strategy for an AI Product – From Insight to Action Plan (Part 3 of 3)

Welcome to part three of this three-part series on go-to-market strategy for an artificial intelligence product or service. In part one we talked about what kind of insights you want to get out of a go-to-market strategy. In part two we talked about how those insights are gleaned.

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Go-to-Market Strategy for an AI Product – Building the Strategy (Part 2 of 3)

In part one of this series, we talked about what insights to get out of a go-to-market strategy project. In this second installment, we're going to be diving into how to get those insights.

Go-to-Market Strategy for an AI Product - What to Discover (Part 1 of 3)

Go-to-Market Strategy for an AI Product – What to Discover (Part 1 of 3)

When clients come to us for custom research projects, sometimes it's because it's a big firm that's looking to make acquisitions or it's a company that's looking for some kind of competitive intelligence. They're looking at who else is offering things like them and how they can position themselves against those other competitors in the market.

Should I Go to an AI Event - How to Decide Which Events to Attend

Should I Go to an AI Event? How to Decide Which Events to Attend

Should I attend an artificial intelligence event or not?

What event should I go to?

Should I go to this event?

The Competitive Dynamics of AI - Now and in the Future (AI Zeitgeist 7)

The Competitive Dynamics of AI – Now and in the Future (AI Zeitgeist 7 of 7)

We’ve made it to article seven of seven in this “AI Zeitgeist” series. It’s been a while building up to this, and I’ve kept the competitive dynamics of AI as the topic of this seventh article because to me everything builds up to this.

The Changing Landscape of AI Priorities of Business Leaders (AI Zeitgeist 6 of 7)

The Changing Landscape of AI Priorities for Business Leaders (AI Zeitgeist 6 of 7)

We come to the sixth installment in the "AI Zeitgeist" series, and this one is about the changing landscape of artificial intelligence priorities for business leaders.

Buying and Adoption Readiness for AI (AI Zeitgeist 5)

Buying and Adoption Readiness for AI (AI Zeitgeist 5 of 7)

This article is part 5 of a 7-part series called “AI Zeitgeist,” where we’ll be mapping out the details of AI adoption over the next 10 years and explore the critical changes in the AI ecosystem that business leaders need to understand.

Accessibility of AI in Business - AI Zeitgeist

The Increasing Accessibility of AI in Business (AI Zeitgeist 4 of 7)

This article is part 4 of a 7-part series called “AI Zeitgeist,” where we’ll be mapping out the details of AI adoption over the next 10 years and explore the critical changes in the AI ecosystem that business leaders need to understand.

The Evolution of AI Talent and Training - AI Zeitgeist 3

The Evolution of AI Talent and Training (AI Zeitgeist 3 of 7)

This article is part 3 of a 7-part series called "AI Zeitgeist," where we'll be mapping out the details of AI adoption over the next 10 years and explore the critical changes in the AI ecosystem that business leaders need to understand.

How "AI" Will be Discussed in the Future - AI Zeitgeist 2

How “AI” Will be Discussed in the Future (AI Zeitgeist 2 of 7)

This article is part 2 of a 7-part series called "AI Zeitgeist," where we'll be mapping out the details of AI adoption over the next 10 years and explore the critical changes in the AI ecosystem that business leaders need to understand.

The 3 Phases of AI in the Enterprise: Emergence, Adoption, and Dispersion

The 3 Phases of AI in the Enterprise: Emergence, Adoption, and Dispersion (AI Zeitgeist 1 of 7)

The following statements are all true, but not in the way you might think:

AI is hard for most companies to adopt.
Machine learning talent is hard to find and hard to hire.
AI gives some companies new ways to compete in the market.

Will There Be Another Artificial Intelligence Winter? Probably Not

Will There Be Another Artificial Intelligence Winter? Probably Not

Here at Emerj we’re dedicated to cutting through the AI hype that’s permeating the current zeitgeist in the business world. Although we’re skeptical about many of the claims that AI vendors make on their websites about what they’re AI software can do, it seems unlikely that the AI hype is going to disappoint venture capitalists and governments enough to usher in a third AI winter.

Feature Engineering for Applying AI in Business

Feature Engineering for Applying AI in Business – An Executive Guide

We talk a lot about the concept of connective tissue here at Emerj, the fact that a company that wants to apply AI not only needs to have access to data, not only needs to hire normally very expensive artificial intelligence talent, but also has to have the connective tissue of related subject-matter experts who can work with that talent.

Spot Fake AI Companies Quickly - Look out for the Fake AI Rebrand

Spot Fake AI Companies Quickly – Look Out for the Fake AI Rebrand

We've seen a lot of what we call "fake AI rebrands" in the last 18 months, and I suspect that as long as AI is a buzzword, we will only see more and more of this. Business leaders are going to have to keep their eyes peeled for these kinds of companies in their midst.

"Psuedo-AI" and When It's Okay for Humans to be Behind the AI

Pseudo-AI – When “AI” is Really a Human, but That Might be Okay

One of the biggest problems facing business executives when it comes to adopting AI is determining whether a company is truly leveraging AI or simply using the term as a marketing strategy. We have discussed rules of thumb for assessing the authenticity of AI companies in previous articles based on insights derived from hundreds of interviews with industry experts and AI researchers over time.

Will Robots Take Your Job

Will Robots Take Your Job? Be Wary of Messaging from Startups and Enterprises

Something that dawned on me very early on in reading biography and history is that incentives rule the world, that company's, nations, individuals ultimately do things primarily for their own self-interest. And there's nothing inherently wrong with that, but it's important to bear it in mind.

The AI Advantage of the Tech Giants: Amazon, Facebook, and Google

The AI Advantage of the Tech Giants: Amazon, Facebook, and Google

If one tunes into social media, it's easy to be convinced that every AI startup is making a lot of money, making a big difference in the companies that they're working with, and driving real revenue. However, as we've mentioned many times here at Emerj, most AI applications are really in pilot mode.

Fake "AI Experts" on LinkedIn - and How to Spot Them Quickly

Fake “AI Experts” on LinkedIn – and How to Spot Them Quickly

Finding the right people to do a job has always been a problem, especially when it requires a high level of expertise. Hiring professionals (84%) are relying more and more on social media to find the right talent, and B2B executives often look to LinkedIn for leads when it comes to finding the right companies to provide crucial services. It is no wonder that people and companies hoping to catch their attention make a point of putting up a robust profile on LinkedIn. However, businesses looking for companies to provide artificial intelligence services need to look at these profiles carefully.

Where Can Artificial Intelligence be Used in Business? - An Executive Guide

Where Can Artificial Intelligence be Used in Business? – An Executive Guide

Most of the time when we have requests for speaking engagements here at Emerj, they're from business leaders. At the time this article was published, I just came back from a presentation at National Defense University in Washington DC. Presenting there was unique in many regards. Obviously, the use cases for tanks and submarines are quite different than they are for drug development or selling more products off retail shelves.

Applying AI in Business - The Critical Role of Subject-Matter Experts

Applying AI in Business – The Critical Role of Subject-Matter Experts

We have discussed the importance of having the right talent in place when it comes to AI adoption in enterprise quite thoroughly here at Emerj. The scarcity of data science talent and its price point are one of the main reasons small businesses are not likely to adopt AI successfully at this time.

The Difference Between Artificial Intelligence and Machine Learning

The Difference Between Artificial Intelligence and Machine Learning

Broadly, artificial intelligence involves a machine doing something that only a human would be able to do. That said, computer scientists disagree on if certain computing capabilities from several years ago still constitute AI. Nowadays, many of these capabilities might just be called software.

Applying Artificial Intelligence in B2B and B2C - What's the Difference?

Applying Artificial Intelligence in B2B and B2C – What’s the Difference?

We discussed the difficulties large businesses may have in adopting AI in our previous article; despite this, last month we fleshed out the reasons why it’s still more difficult for small businesses to apply AI than the enterprise and how they might catch up to larger businesses in the future.

Managing the Risks of AI - A Planning Guide for Executives

Managing the Risks of AI – A Planning Guide for Executives

This article is based on a presentation given by Emerj CEO Dan Faggella at a recent conference “Artificial Intelligence and Business Ethics: Friends or Foes?” held at the University of Notre Dame. 
The conversation about artificial intelligence and ethics ranges from the broad to the specific. On the one end, there are governments making laws and policies on national, state, and local levels. In the middle, you have industry-wide agreements on certain protocols on privacy expectations, ways of handling customer data, and other ethical considerations within the framework established by the government.

How to Tell if an AI Company is Lying About Using AI

7 Ways to Tell if an AI Company is Lying About Using AI

A few months ago, we spoke about three rules of thumb for assessing companies and trying to figure out if they are really doing AI or just using it for marketing purposes in our How to Cut Through the Artificial Intelligence Hype piece. Since it was so popular, I was inspired to write this follow-up.

Ben Levy Emerj

Should My Startup be Using Machine Learning and AI?

Almost all young companies and companies in the start-up ecosystem today would like to talk about how they leverage AI or machine learning. In most cases, this is to make their product sound special and exciting. However, the fact is most young companies do not have the resources or the talent needed to leverage artificial intelligence in a way that would add to their value proposition.

How to Cut Through the Artificial Intelligence Hype - Three Simple "Rules of Thumb"

How to Cut Through the Artificial Intelligence Hype – Three Simple “Rules of Thumb”

Artificial intelligence and machine learning are hot terms right now, and many companies are eager to talk about how their products rely on these cutting edge technologies. Established companies and startups want to explain how AI is a critical part of their business.

Is Artificial Intelligence for Small Business?

Is Artificial Intelligence for Small Business? Factors to Consider for Technology Adoption

AI is being likened to a "Fourth Industrial Revolution" because of it's potential for creating profound change in people’s lives, much like the invention of steam engines (First Industrial Revolution), electricity and mass production (Second Industrial Revolution), and the rise of the digital age (Third Industrial Revolution) had in the past.

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Enterprise Adoption of Artificial Intelligence – When it Does and Doesn’t Make Sense

Chances are you have already been bombarded on social media or in your inbox about all these “revolutionary AI” this and “game-changer AI” that.

How to Apply Machine Learning to Business Problems 3

How to Apply Machine Learning to Business Problems

It's easy to see the massive rise in popularity for venture investment, conferences, and business-related queries for "machine learning" since 2012 - but most technology executives often have trouble identifying where their business might actually apply machine learning (ML) to business problems.