A Pathway to Career Acceleration – Getting Started with AI

Daniel Faggella

Daniel Faggella is Head of Research at Emerj. Called upon by the United Nations, World Bank, INTERPOL, and leading enterprises, Daniel is a globally sought-after expert on the competitive strategy implications of AI for business and government leaders.

A Pathway to Career Acceleration

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.

I’ve summed up some of these points in the short video below – including a live reading of some of the responses from our email subscribers:

Before diving into the upcoming report, I want to highlight a theme that has been a common thread throughout this series: Career opportunity for nontechnical professionals in the era of AI.

Case Studies of AI Career Advantage for Nontechnical Professionals

Who earns more: the best AI developer, or the best AI strategist?

It’s the strategist.

Jeff Bezos didn’t build the website at Amazon.com, he directly the internet and web strategy – and arguably even more crucial role. Now with the advent of AI – nontechnical professionals with initiative can gain valuable and rare AI knowledge and experience and set themselves up for vastly more career opportunity and income in the coming five years.

Below, we’ll explore the careers of professionals who captured AI career opportunity without learning to code.

Emerj Podcast Guests:

Sankar Narayanan, Chief Practice Officer, Fractal Analytics

Sankar was part of one of our AI in Industry podcast interviews earlier this year – and his episode received excellent feedback, and highlighted methods of quantifying the return on investment of complex AI projects.

He holds a bachelor’s degree in engineering, and later a master’s in finance – and held a variety of analyst roles before joining Fractal 13 years ago. Piercing and practical AI insight (and even a C-level position at an exciting and fast-growing firm) don’t require an AI PhD (Sankar doesn’t have one), they require a functional understanding of AI, and a strong understanding of what it truly takes to apply it (which Sankar has in spades).

(Sankar’s episode on the AI in Industry podcast was part of our very popular article on the ROI of AI – which also includes an embedded audio player of Sankar’s interview).

Muriël Serrurier Schepper, Co-founder, AI-Training.nl – Associate Partner, Holland Consulting Group

Muriël shared her AI career journey on the AI in Industry podcast recently. She began by getting consciously involved at AI projects while working at Rabobank, then transferred those skills to AI-related work at Shell and other companies – and now runs her own consultancy in addition to working with the Holland Consulting Group.

Is she paid for her ability to write code?

No. Muriël is paid for her ability to practically apply AI, and to guide executive teams to make the most of AI opportunities – strategic skills which are often vastly more valuable than programming.

You can listen to Muriël tell her own career path story in her recent interview on the AI in Industry podcast.

Corporate and Organizational Leaders:

John N.T. “Jack” Shanahan

John N.T. “Jack” Shanahan – Director, Joint Artificial Intelligence Center

Few initiatives are more exciting in the US public sector than the Department of Defense’s Joint Artificial Intelligence Center (JAIC).

With so much riding on the line (US security, continued economic and technological superiority, national defense), you’d expect the US government to put an AI PhD in charge, right?


Jack Shanahan serves as Director of JAIC, a man known for his leadership ability and functional experience, not for his technical ability.

The person with the subject-matter expertise and a strong conceptual grasp of AI will always trump programming skills when it comes to strategic and leadership roles related to AI – and even the US DoD is no exception.

David Tyrie

David Tyrie – Head of Advanced Solutions and Digital Banking, Bank of America

Bank of America is one of the largest banks in the US (we’ve covered their AI innovations in past articles), and Erica – their personal virtual assistant and chatbot – is one of their most important strategic moves in digital.

So – surely the person leading this initiative would be an AI expert or researcher with a strong academic background in computer science, right?

Well, wrong.

Bank of America certainly has many sharp data scientists and ML engineers working at the firm – and working on Erica specifically – but it’s not an AI researcher who is heading up the roll-out and application of this new chatbot – it’s someone with a background in… well… banking.

David Tyrie heads up the Erica effort, and other digital banking solutions, and he earned a Psychology degree back in 1987. Nothing in AI or computer science. No AI certificates.

Instead, David grew his career in banking from the ground up, beginning with MFS Investment Management back in the 1980’s, to Bank of America Merrill Lynch in 2010, to Bank of America in 2015.

He’s heading up an absolutely critical role for Bank of America – not for his ability to write code – but his ability to combine a strategic view of AI and emerging technology with a deep understanding of banking strategy.

Getting Started with AI 1200x200@2x

Subscribers Like You:

But you don’t have to be a corporate or public-sector leader to find career opportunities with AI strategy knowledge.

Even with relatively modest career aspirations and no desire to have to “lead the charge” of AI – regular managers, VPs, and consultants can raise their market value and career opportunity in more modest ways by simply learning the critical context around AI.

Here are some stories from our own email subscribers – which I mentioned in the first installment of this series:

  • Product Manager Turned AI Strategist – A product manager who has been on our Emerj newsletter for over a year becomes an in-house “AI strategist” at a multi-billion dollar company because he understands AI use-cases and adoption better than anyone in the C-suite – and his new position is not only more fun, but pays more.
  • Unemployed Marketer Locks in Job with Hot AI Startup – An unemployed marketing professional listens to our podcast for months and is able to land a job at a hot AI startup because she “gets it”, can speak their language, and understands their use-case and value.
  • Strategy Consultant Nabs Exciting and Lucrative AI Projects – A strategy consulting firm with no real background in AI consulting learns from our Executive Guide articles and is able to work with multi-billion dollar companies and help them with AI adoption – developing what will become lucrative and exciting partnerships in AI transformation.
  • Small Town Martial Arts School Teacher Becomes International AI Strategist – That’s my story, actually – read my previous “AI Career Gap” article which covers how I went from a 4000-person town in Rhode Island (with no background in AI or computer science) to world with organizations like the World Bank and United Nations for our AI research.

Stories like this always make me smile because I know that gaining an edge in AI knowledge and insight now will yield strong future benefits for nontechnical professionals.

I mentioned this in a previous tweet before – but it warrants showing it again:

AI Career Opportunity Questions from Emerj Subscribers

When I initially sent out requests for our AI for Career Advantage article series, we received literally hundreds of replies by email – and dozens more survey responses and LinkedIn messages.

Most of the replies involved requests for what kinds of insight would be most helpful to go along with the release of the “Getting Started with AI” report. The requests broke down into three main categories:

1 – AI Career Paths on the Business Side, Not the Coding Side

This was an interesting one. Lots of people requested a breakdown of the actual roles that nontechnical person can fill in order to contribute to AI. In other words – they want to know what specific knowledge they can learn and tasks they can be a part of to get ahold of AI career opportunity.

Here’s a comment and question that came in from our survey – this is probably the best wording I saw:

“The career path for folks who want to focus on AI from a business/strategy perspective, whoever, is NOT clear. When I look at JDs for anything related to AI/ML, the role requirements typically ask for considerable technical depth.

It’s not clear even for folks with a technology background who are interested in working in the AI space, but are looking to do so from a business perspective. So the question is … where are the ‘Business AI’ jobs?” – N.G., former Microsoft executive, Seattle Area

As promised, these requests and ideas have become the inspiration for the resources and tools we’ll be releasing for the launch of the “Getting Started with AI” report. Just categorizing and reading all of the responses from our subscribers was a big deal – but the real work came in actually turning those ideas into additional best-practice resources that will be released on November 21st with the full report.

2 – End-to-End Map for AI Projects

We received a number of questions that looked like:

  • “I’d like to know the steps of an AI project, and what do to in each one?”
  • “What are the phases involved in really deploying AI, and can you walk me through each of them in a simple guide?”

Over half of these requests asked not only to see the steps and phases, but to walk through a real example of AI adoption with a real company, to understand all the hurdles and challenges involved at each step.

Here’s one of the requests I thought was representative:

“For me – it would be important o know concrete examples of what an end-to-end ML project looks like: from initial business scoping with customers/stakeholders, to data collection/understanding/transformation, model training/evaluation, deployment, monitoring. Who does what, common challenges and how to overcome them. What can be automated, what can’t.” – R.B., manager in a large financial services consulting firm, Sweden

3 – Where to Start with AI Adoption and Strategy

There were a lot of questions about getting AI projects off the ground, about practical steps for making AI work – and determining where to focus AI efforts to see an ROI. A number of subscribers also asked about how to convince senior leadership about AI.

Here’s one actual request:

“I’d like to learn critical points on why and how to adopt AI. [A breakdown of] how to assess if a company is ready to embrace and monetize a true AI strategy.” – D.B., consulting group CEO, Boston Area

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