Daniel Faggella

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.

Picking first AI projects in 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.

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.

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.

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.

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.

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.

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.

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

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.

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

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

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.

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.

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.

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.

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.

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.

What a year it’s been.

We’ve seen our subscribers in enterprises around the world rethink their strategic priorities from the ground up in the face of COVID-19, and we’ve seen our clients in the AI events space reimagine their entire business model over just a few months. We've also see the rise in new AI consultants spinning out of almost every industry - finding new ways to serve the urgent transformation needs of enterprises in crisis.

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.