Artificial intelligence is all the rage. Since the release of OpenAI’s ChatGPT 3.5 in November, news commentators and business pontificators can’t seem to stop talking about the imminent disruption due to generative AI and large-language models (LLMs). Business leaders from all sectors are asked about their plans for generative AI on earnings calls and in press conferences. Government officials are calling for regulation or even a pause in AI development. Futurists warn about the end of humanity.
All the chatter is leading to a massive increase in the valuation of all things AI. NVIDIA, the maker of advanced chips powering AI, has seen its market valuation quadruple since November to a valuation over $1 trillion. Leading tech companies on the forefront of AI — Google/Alphabet, Microsoft, Apple, even Facebook/Meta — have seen their valuations spike in the past six months.
Real vs. False Paradigm Shifts
What is an executive or investor to do?
As a recent Super Bowl ad admonished: No one wants to be the “Larry” who continually dismisses game-changing technology. Imagine instead being on the forefront of integrated circuits, personal computing, mobile computing, social media or gene sequencing. Savvy investors and businesses capitalize on the new, new thing to great benefit.
On the other hand, history is littered with those too early or too eager to catch waves that never fully materialize. Who can forget the dot-com craze and crash? Billions were invested and lost on companies with “creative” valuations, despite having limited or no sales and no viable path to earnings. Similar manias gripped radio-frequency identification, data serialization and exchanges — as well as, currently and increasingly, cryptocurrencies.
In our lifetime, a lot of capital has been lost by chasing false paradigm changes and a lot of earnings missed by not paying attention to real paradigm changes. Why do large groups of otherwise accomplished and smart people persist in making such bad decisions? How can we best identify when the hype is turning to mania? Or when does the hype actually underestimate the long-lasting impact of a new technology?
The Questions to Ask
Executives and investors need to address key questions when considering the latest technology trend. And the answers to those questions are likely to depend on the specific sector.
What Kind of Change?
First, is this an evolutionary or revolutionary change? Does it impact the underlying nature of competition within the industry? Does it redefine the core value proposition to customers or change the available business models? Does it render existing capabilities less valuable or even useless? Does it open opportunities to deconstruct the value chain, allowing for new entrants to capture value in niche positions in the market?
If any of the above are the case, the new technology may be more revolutionary than evolutionary.
Consider the push to use AI to create fully autonomous vehicles. If successful, this will likely be a revolutionary change to the auto industry. The locus of power will shift from hardware — designing and manufacturing the car — to software — refining and deploying the AI. The entire value proposition and business model will likely shift to a ride-sharing model, one in which individual car ownership wanes. A fee-for-product business will be replaced by a subscription model or maybe even one that is primarily used as an advertising vehicle, so to speak. The car will become a platform, opening up an entire ecosystem of adjacent business opportunities.
But for some, generative AI will be more evolutionary — allowing for increases in productivity but not fundamentally shifting the architecture of the industry. It is important to recognize that these productivity gains may be long in coming, as is often the case with new technology. The impact may be slow-moving and relatively benign. While critical to competitive success, AI may not challenge the existing paradigm.
What’s the Pattern?
Second, is this the right time to invest? With fully autonomous vehicles, the answer always seems to be “next year,” at least if you listen to Elon Musk. Whether the answer is next year or decades away (or never), it’s an important question.
To determine the answer, consider another question: Where are we in the industry life cycle? The “industry life cycle” amounts to a common pattern with new, disruptive technology.
Real Paradigm Change
In our experience, real paradigm change often comes in without attracting lots of attention. The technology is frequently championed by lonely advocates and dismissed out of hand by those who are successful in the existing business paradigm. The enthusiasts understand the new technology needs to be justified on traditional measures of business success, and the value proposition should be obvious.
Consider mobile computing: It didn’t take long for its disruptive potential to lead to pioneering, novel applications, like ridesharing.
False Paradigm Change
So, when does the latest proposed disruption signal a false paradigm change? Warning signs include coming in loudly, declaring the old business metrics are meaningless, or that the entire business cycle no longer applies (see again the dot-com boom). Another red flag: Enthusiasts declaring “You just don’t get it.” It’s a bad sign when they can’t explain the underlying economic rationale for the technology (see also: crypto champions).
Exacerbating the mania is the typical rise of an ecosystem of supporting players catering to the new, new thing — consultants, investment advisers and technology futurists who are incentivized to maximize the hype. Consider: When was the last time one of these players came into your office and said, “Nothing startlingly new to discuss, no game changers coming down the pipeline”?
AI: Real or Hype?
What does this mean for AI? A year ago, it would be easy to make the argument that AI was coming in on a cat’s paw — quietly, under development for decades, largely ignored by the general public, the fascination of a dedicated bunch of enthusiasts, promising massive gains in productivity and value creation.
Today? The cat’s out of the bag. The hype is at its most hyperbolic. Everyone is embracing the gold rush. You can’t have an earnings call without it being mentioned. Bold predictions are being made that the machines are coming for our livelihoods — or maybe even our lives! How do we know what is real and what is just hype?
How to Be Best Positioned?
This takes us to our third critical question: Who is best positioned to capitalize on the new technology? Not all opportunities are created equal. Another common pattern with industry life cycles is the competitive shakeout, in which many companies fail or disappear through mergers and acquisitions. The challenge is not only if-and-when to invest, but what companies and industries should invest and are likely to survive a coming disruption?
In this digital age, most disruptive changes, real and not so real, rely on information technology for execution. Life cycles are compressed, and the time from the new thing becoming the old thing is getting shorter. In our experience, most IT budgets are focused upon current activities rather than support of innovation. The traditional chief information officer’s primary focus is actually on cost containment and risk avoidance.
Smart executives carefully question how to execute on technology, especially how things are integrated. They develop structures to support innovation. They create easy on-ramps for the new technology and, just as importantly, they create an easy off-ramp for those technologies that no longer add sufficient value. They adopt architectures that allow them to maintain a portfolio of applications — adding as desired and culling as needed, avoiding application count creep that drives costs up. They create incentives that don’t punish failure and do encourage experimentation and exploration. In the parlance of the Valley, they fail fast and learn.
Smart companies develop the capability to separate the real from the false, the gradual evolutionary technologies from the game-changing revolutionary technologies. They staff, fund and govern each differently. They invest in “absorptive capacity” — the ability to follow and assess scientific discoveries, which will likely be early harbingers of paradigm changes. They understand that periods of global instability and large nation-state competition — such as the one in which we find ourselves — tend to accelerate technology development as the pressure to lead becomes paramount.
Smart executives think about their entire “technology stack.” They understand the importance of their underling digital infrastructure — things like data lakes and cloud computing. They invest in their analytic capabilities, from developing simple dashboards to deploying sophisticated AI. They develop applications that allow them to create and capture value. And, most importantly, they have a digital strategy — a vision of how to best position themselves in a rapidly changing marketplace, a vision based on the reality of the firm’s existing and evolving capabilities.
The Discovery of Fire or Evolution of Automation?
Ultimately, what should we make of ChatGPT and other generative AI? Will it be the paradigm-shifting disruption many are heralding? If you question the impact and importance of AI, do you “just not get it”? Is the CEO of Google right that this is more important than the discovery of fire? Ask yourself: Has there been a compelling use case of costs saved and investment dollars returned?
Or is this just the next evolution of IT capabilities — a natural extension of business intelligence, machine learning and automated decision-making? After all, we have had automated stock trading, automatic shopping, automated phone support and chatbot recommendations for quite a while now. At the end of the day, will it simply re-enforce existing business models and traditional capabilities for success?
History will provide the answers. We hope we have provided executives and investors some of the right questions to ask.
Mike Lenox is the Tayloe Murphy Professor of Business at the University of Virginia Darden School of Business, Senior Faculty Fellow at UVA's Miller Center and the author of Strategy in the Digital Age: Mastering Digital Transformation. Tom Schaumburg (MBA ’83) is an independent consultant with decades of experience as a practitioner in industry and decades of selling technology … he has been on both sides of the desk and is a Darden alumnus.