The Hunt is on for the Renaissance Man of AI | Why "M-Workers" are leading & building the future

“...the vast world of inner life beyond us, so different from that of outer seeming, illuminates our mind. Then the whole scheme of our customary values gets confounded, then our self is riven and its narrow interests fly to pieces, then a new centre and a new perspective must be found.”- William James

In 1991 David Guest penned an article in “The Independent” titled: The Hunt is on for the Renaissance Man for Computing. At the time, the skills gap in computing and shortages of technical specialists appeared to be easing. Standardization of computer systems, the rise of off-the-shelf software packages, and outsourcing to third-party IT providers meant that fewer in-house technical specialists were needed.

Although he expressed some skepticism, this re-awakened the call for a “Renaissance man,” or what came to be known as the “T-shaped people.” These are individuals with deep expertise in one domain (the vertical stroke of the “T”) and broad competence across other fields (the horizontal line), including IT, management techniques, and even domains like music. This person can see the “broad picture,” relate to people, understand their motivations, and still talk sensibly about systems and data. A corporate unicorn.

Guest was not the first person to articulate this need for redefining the workforce. Credit for that goes to a more obscure and little-known engineer—Denis Johnson. Published in 1978 in IEEE’s engineering journal, Denis argued that the best engineers of the day needed to be a “T-shaped manager.” For scientists becoming managers, this meant maintaining their technical credibility and deep domain knowledge while simultaneously developing competencies in management, business strategy, communication, and cross-functional leadership.

Management consulting firms, especially McKinsey, further popularized this notion and sought to develop their workforce accordingly throughout the 90s. Nowadays, it is not that uncommon to see more of these “T-shaped” workers across the landscape, including the executive suite. Some are technical first, like Sundar Pichai (Google and former McKinsey), and some are business first, like Andy Jassy (Amazon), but both are “T-Leaders.”

There’s a newer type of Renaissance man taking shape, driven by need, technology accessibility, and the commoditization of intelligence.

RISE OF THE M-WORKER

“We are all in sales. Period.” - Tom Peters

As the AI revolution marches on, I have experienced a subtle but dramatic shift in what the workforce of the future will be. The shift in the past several years has created what I call “The M-Worker.”

The “M-Worker” is defined by the three vertical strokes of the letter “M”, instead of the single vertical stroke of the letter “T”. Beyond what Tom Peters stated many years ago—”We are all in sales…”—I say that we are now all in sales, strategy, and product. The T-model leaves too much up for grabs.

Deep expertise in one thing and a broad range across many others—this vague definition limited the applicability of this formulation as a useful concept. Interestingly, the deluge of AI applications has enabled everybody to have an easier route to enhanced workplace capabilities that usually resided within specialized roles.

The tacit enabler of the “M-Worker” is the basic premise that everyone, on a first-principles basis, has the foundational capabilities to drive value across all three dimensions. In sales, the inherent building blocks possessed by most is the ability to communicate. In strategy, it’s efficient ways of working. In product, it’s having preferences. The progressive development and refinement of these create a productive “M-Worker.”

Startups, small businesses, and some exceptional large enterprises have been leveraging some form of the “M-worker” for a long time.

Amazon, my current workplace, famously seeks and nurtures these types of employees. Under the guidance of our well-known leadership principles, everyone at Amazon is expected to use them as operational heuristics. For example, principles such as 1) Invent & Simplify, 2) Think Big, and 3) Bias for Action, allow our teams to move fast and innovate. Using frameworks such as “one-way and two-way doors” gives everyone permission to innovate across the enterprise.

The result—a sales account manager can build a product, a product manager can draft ideas on strategy, and an engineer can participate in sales cycles, and so on. By democratizing and surfacing these latent capabilities across the workforce, the per-employee output and production skyrockets.

Before having my own startup and before working at AWS, I suffered what Thoreau would call “a quiet life of desperation,” where my professional capabilities and desires were stymied by my “role.” Most companies still operate in a relatively rigid fashion, where one’s role defines activities and domain of influence. Only at the executive level do you occasionally see exceptions to this rule.

What Is Different Now

Not only internally, but across many customers and across industries, I’ve started to see the siloed role structures start to soften. The great enabler is AI. The current versions of generative AI have made it easy for anyone to manifest their creative ideas.

Every dimension of our creative capability is now augmented.

This is how the “M-worker” is now rising to prominence. For those less inclined to pursue self-development across different skill sets, AI removes layers of effort that were once required to develop even an amateur capability.

Enabling workers at scale can be a daunting task. Absorbing too much change too quickly can spook employees and lead to second and third-order unwanted effects. Getting this right is not as simple as providing access to a new tool. Business innovation as a capability has increasingly grown in importance both at AWS and for our customers—this includes things like business innovation, value architecting, and strategy.

Collectively, these enterprise capabilities seek to take a critical and qualitative perspective on business transformation as a whole, not just technology. By validating business outcomes and the enablers across the workforce and value chain, enterprises deliberately and steadily build a more robust innovation capability - truly unlocking the value of AI, not just tired use cases.

Enabling and incentivizing self-development, learning & experimenting is one way to nurture the growth of an “M-Workforce.” Evolving hiring processes to seek these individuals is another way.

This area of business strategy is what I would call a “capital lite lever”—this means that you or your company can extract value from existing human capital without a large investment in economic capital. There are many forms of latent capabilities and resources across organizations that can be surfaced by discovering and operationalizing “capital lite levers,” but I will leave that for another post.

My guidance in a nutshell is to be and encourage an “M-worker” way of working.

Opinions My Own.