As a leader of a diverse and growing organization, I constantly scan the horizon for market shifts and operating environment changes that require us to respond and align our services. The same applies to most of the high-performing businesses and social impact organizations we advise, regardless of sector because complacency rarely breeds success long-term.
But the habit of constantly responding to—and trying to predict—market shifts can feel overwhelming, especially when seemingly “disruptive” new technologies or business methods grab headlines.
Nearly every leader is tracking the advent of more sophisticated large language models and generative AI, and for good reason–—these technologies offer the potential for real gains in productivity and efficiency. Simultaneously, the feeling of “missing out”—what I sometimes dub corporate FOMO–—is very real. What if we’re already behind? What if we don’t do it right? Shouldn’t we be all-in on [fill in the blank with the latest trend or technology]?
In some cases, leaders overreact and move too quickly towards unproven technologies or methods without a compelling rationale.
Time will tell just how transformative the current generation of AI technology proves to be. What’s certain, however, is that generative AI won’t be the last “this changes everything” technology or headline to trigger corporate FOMO. Advising leaders of all types has helped me distill three approaches for analyzing these trends—separating rose water from snake oil and leading organizations through hype cycles with clarity and purpose.
1. Develop a healthy skepticism
In the moment, it’s challenging to avoid jumping on the bandwagon of new trends and technologies. An effective antidote to combat those instincts is to pause and reflect on similar hype cycles that have ultimately proven less transformative than their initial claims, which can help to frame the current “shiny object” in a more realistic light.
The pros and cons around generative AI are easier to unpack when placed in the context of the past 15-plus years of related “Big Data” and machine learning breakthroughs and failures. Some were real, while others were smoke and mirrors, but few businesses failed outright because they weren’t the earliest adopters of data analytics and machine learning-driven automation.
Lessons from adjacent sectors can prove helpful. For example, revisiting the early exaggerated claims around blockchain and distributed ledger technology is a reminder that new technology can change businesses and markets—but we rarely understand its potential in the earliest days of adoption. Cryptocurrency is likely here to stay, while non-fungible tokens (NFTs) remain a waste of time for most organizations.
2. Be the second (or third!) mover
For decades, Apple steadfastly refused to be a first mover around most technology breakthroughs, instead letting competitors spend time and resources racing ahead with often shaky first-generation tech. Apple watched, learned, and only then went to market with (usually) more refined and proven solutions.
Strategic patience is crucial for all leaders navigating pressure from staff, customers, or supply chain partners to embrace the next brand-new thing. Unlike many investors who go all-in on these early bets, organizational leaders can rarely afford more than one bite at the apple. Business leaders face a much steeper downside to getting it wrong, which begs for a more measured approach to placing bets on new technology or methods.
For example, several companies took a measured “wait and see” approach in the early years of the pandemic. Because they retained office space signaling a future return to office, they were able to better pivot back to today’s “normal” at lower cost and with a less negative impact on employee morale.
3. Understand where the money gets made
Finally, the leaders I’ve witnessed who are most skilled at navigating hype cycles are those who have a keen understanding of who is making money off new disruptive technologies and business models, and how. Leaders don’t need a PhD-level understanding of how to train a large language model. But they need to understand how companies, both large and small, are profiting from these technologies and services.
Google just announced that it is building a nuclear reactor in Tennessee to provide more electricity to fuel the computing power required for its Gemini AI services. The financial stakes for generating profit from those services are enormous, even for a company like Google. The profit pressures are real, and for companies selling these services, they need and want decision-makers to feel that pressure. Leaders who have the patience and confidence to step back and better understand how profit pressures might contribute to overhyped claims are the ones who ultimately make better decisions for their companies and organizations in the long run.
FINAL THOUGHTS
At the end of the day, technological and business process innovation are real, and no company or organization succeeds in the long term by burying its head in the sand and ignoring marketplace disruptions.
But not every claimed once-in-a-generation breakthrough is real or will last. Parsing the signal from the noise is what great leaders do best, often by employing strategic patience and a dose of healthy skepticism to ensure that when they do place big bets, they’re betting with the best odds possible.
This article was originally published in Fast Company on March 28th. To read the original article, click here.
