AI: It’s the Same but Different

Are You Afraid of the Dark?

In my almost 40 years in Silicon Valley I have been a part of or had a front-row seat to some truly astounding technological innovations and trends: the rise of the personal computer at work, the proliferation of the home PC a decade later, the internet explosion of the 1990s, the migration to cloud computing, the ubiquity of smartphones, the dominance of social media in our lives, and the reinvention of entertainment through streaming.

And then there is AI.

In 1962 Stanford established SAIL, the Stanford AI Lab. For almost six decades AI had many false starts as a technology that was “finally arriving.”

But about eight years ago things changed. In 2016 I posted the following on Twitter with my VC hat on:

In January 2019, Tomer Cohen, Chief Product Officer at LinkedIn, came to my Product Management class at the Stanford Graduate School of Business and gave a lecture on how AI was impacting the Product Manager’s job. He would return in subsequent class sessions, and for three and half years he was ahead of the curve talking about things that many PMs and most companies had a hard time relating to on a day-to-day basis.

When ChatGPT was launched at the end of 2022, Tomer officially became a genius.

Since the launch of ChatGPT and with the subsequent evolution of various LLMs, I have never seen such a rapid adoption of a technology in businesses across all sizes and geographies. I work with companies all over the world and this is unlike anything I have ever experienced. Charts like this from Mary Meeker are widely available to all:

The data is consistent when looking at AI vs. the adoption of new computing/hardware platforms:

(NB: Note that “Year 2” is 2023-2024 for AI.  Insider Intelligence assumes the growth curve flattens out in the coming years, but it is also possible that the curve takes on a y=x² or even a y=x³ shape for an extended period of time.)

Aside from the barbell perspectives of AI being the greatest technology ever invented to it being the precursor of the end of our species, the momentum of this technology is astounding, pervasive, and global.

We all know this from what we read.

But to the average executive or manager, how should they think about AI in their job and also in how it will impact their company?

The easy, critical, required, and largely undifferentiated task is to learn about the technology – to find out how it works and to explore what possible applications are likely to come soon. Online courses are readily available which explain how “the magic” is done, and some simple Google searches allow businesspeople to become conversant in the likely business applications.

But there are two important things that business leaders must internalize which are not often said out loud…

Be Wary of the Power Players

The tech industry in the last 20+ years has become globally powerful and influential. The vast amount of wealth that has been created has been concentrated in very few hands, and tech companies have dominated commercial profits and the growth of most stock indices for the last two decades.

But no matter how we cut it, the current leaders in AI all bring a sordid side to their activities. Let’s start with Sam Altman, the CEO of OpenAI. Aside from the mixed messages regarding his exit at Y Combinator, he got fired as the CEO of OpenAI, and then was brought back and the company’s Board was blown up and reconfigured with his supporters.

There is also the opaque and highly conflicted nature of his personal investment portfolio.

The dude gives new meaning to the adage, “No conflict, no interest.”

In addition, the number of executives that have departed OpenAI over ethical concerns of the organization’s actions is non-trivial at best.

Where there is smoke…

Our friends at Meta are very active in AI development, and have been reportedly talking with Apple and other large companies with whom they might partner on their AI capabilities. This activity comes from the same people who gave us confusing and hidden privacy settings, the Cambridge Analytical scandal, and of course, the Facebook Papers.

Even Microsoft, whose reputation is no longer of the young Bill Gates who bullied the computer industry, but rather of the wise and evolved Satya Nadella, seems like it concocted a deal to acquire Inflection AI without actually acquiring Inflection AI in order to avoid regulatory scrutiny.

Since AI is on a path to become ubiquitous for companies of all shapes and sizes, business leaders in every organization must pay close attention to the incentives and behaviors of their key suppliers of AI – as they would with any other key component or tool used in their business.

Assuming that the providers of AI technology will make choices that are in the interests of their customers flies in the face of the past behaviors of these individuals and companies.

The truth isn’t pretty, but that doesn’t make it any less true.

You wouldn’t trust a supplier who sold you shoddy products with substantive material defects, and you wouldn’t trust a supplier whom you thought was taking advantage of you, your data, and your company for their own interest.

These AI behemoths are suppliers with sketchy activities in their backgrounds. They should be managed as such.

Have an Opinion on What it Means for Your Labor Force

The continued evolution of AI as well as communication and collaboration tools create an interesting dynamic: increasing the speed with which certain jobs will cease to exist.  In his seminal book, Future Shock, Alvin Toffler quoted two great thinkers,

John Diebold, the American automation expert, warns that "the effects of the technological revolution we are now living through will be deeper than any social change we have experienced before." Sir Leon Bagrit, the British computer manufacturer, insists that automation by itself represents" the greatest change in the whole history of mankind."^[1]

Toffler went on to argue that we as humans are unprepared for this change. When he wrote the book in 1970 (!), he predicted the rise of products being sold as experiences, fast fashion, the move to cities, and he coined the phrase “information overload.”

Fast forward 54 years and his prognostications seem frighteningly accurate. When one considers how quickly technology has changed since he wrote this work, we can comfortably predict that the ongoing displacement of labor and capital will only accelerate over the coming decades. One can imagine a new form of organizational design that is not built in the structure of “Globalization 1.0,” which was fundamentally a labor arbitrage opportunity and structured in a “hub and spoke” model. Leaders could maintain a corporate headquarters in a specific location where strategy and key decisions were made, and low-cost manufacturing could be placed in Asia, low-cost software engineering could be put in Eastern Europe, and low-cost customer service could be delivered by people in India.

“Globalization 2.0” will enable companies to operate more like a mesh network, with equally important nodes spread either within or across countries. The digital tools available to workers are now more sophisticated than ever before, and geographically dispersed organizations can operate with even greater effectiveness and tap into global talent.

Leaders need to have a point of view on how the future of work will shape their organizations: what will be required to deliver great goods and services to customers, what their labor force will want and demand, and how their organizations should be designed to take advantage of these trends (and is not destroyed by them).

I often ask managers and executives the following:

“If you look around your company, you know what jobs are going away in the next five years due to AI. What are you doing today to retrain your labor force?”

And, to be clear, the education system can’t keep up – whether it is K-12 or our top universities. The speed and impact of these changes are happening more quickly than faculty can study, absorb and teach students. Thus, companies need to think about investing in a constant re-skilling and re-training of their personnel in order to be competitive.

While hiring new employees can bring new perspectives into a company, some studies show that it can cost up three times as much to hire a new employee vs. retraining an existing employee.^[2] Heather McGowan has argued that “Learning Is the New Pension” and will become a requirement for companies to invest in their employees both for employee retention and ongoing competitive advantage.^[3]

The rate of technological change isn’t going to slow down – the jobs of today’s leaders are only going to get harder. Regarding AI, how leaders react to and acquire their AI solutions may become as important as deciding what markets to compete in and what products to sell.

And every leader, regardless of his/her background and function, needs to understand the impact of AI on their teams — it is an existential issue evolving at a breakneck pace for the humans that work in your organization.

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[1] Toffler, Alfred. Future Shock. P. 15.

[2] From 2016 Studies by the Association of Talent Development, UC Berkeley and the Society for Human Resource Management

[3] McGowan, Heather. “Learning Is the New Pension,” Forbes. October 29, 2019.