As You Bet on AI, Make Sure It’s Not Your Strategy That’s Artificial

There was an axiom we used in venture capital that said that the industry had a memory of only 10 years. Whatever was learned 10 or more years past, in other words—from what to avoid, to what to prioritize—was said to be forgotten, only to be painfully re-learned repeatedly at decade intervals. The origin of the phrase was directly tied to the lesson that the predicted impact of any new innovation is always grossly overstated. You don’t have to have ever worked in venture investing to know this to be true. Just flip back in your memory to see. An eon ago, the fax machine was claimed to foretell the end of physical mail. It wasn’t, nor years later was email, though it too was unveiled with similar claims. Desktop computing was boasted to be the demise of large data management and mainframe computing. To be sure, desktops, then laptops, then smartphones all dramatically changed how we do what we do; but the cloud and server farms show the prediction to have been over-imagined. Most artifical intelligence innovations are simply tools. These tools’ actual impact occurs only in the context of the larger purposes, plans, and strategies they serve. Yet, too often, we speak of the innovation as strategy itself, as if “using more artificial intelligence in 2025 and beyond” is enough to represent a strategy. It’s not. It’s also why this latest version of this repeated lesson isn’t just about overstatement. It’s about confusing tools and tactics with strategy. In the last year, my research has put me in touch with many of the organizations considered leaders in AI, including in determining its uses in and impact on business. Even those developing the tools feel a sense of marvel at what AI can do. In turn, they’ve spent much of the past few years striving to put AI to work as quickly as possible, in part for its speculated promises, and no doubt too for the assumed rewards AI might bring. For the AI developers paying close attention, two things give them pause. The first has caught most of them by surprise: AI is proving to have power beyond what even its designers know, and to a degree, none of them can predict nor control fully. In response to that particular awakening, in 2023, a group of leading firms suggested that there should be a collective pause taken to think about the deeper implications of what AI might bring, consider the possible ripple effects that might result, and jointly explore how shared guidelines might be followed. Some, surprisingly quite a few, were willing to sign on to a formal agreement. Few were prepared to act. The technology’s promises, even unverified, were just too great not to speed ahead, logic be damned. The cost of confusing AI tools with strategy. The second thing giving leaders in AI pause was more disturbing in its implications. It was the stark reality that in the rush to embrace AI, an increasing numnber of organizations suddenly found themselves struggling to answer seemingly simple questions like: What business are we in? So busy were they chasing the tool, that they found themselves suddenly having a hard time remembering what business goals, mission, even strategy the tool was there to support. Almost without their noticing, their priorities had become unintentionally inverted, with the tool no longer the supporting mechanism, but instead the dominant focus. It began firm by firm, but the error of putting AI ahead of the strategies it should be supporting has quickly developed into a disturbing, even dangerous trend. As broader evidence, a recent report from consulting firm McKinsey & Company called this out, and warned of the costs of confusing tools and tactics with strategy. “It’s time for a reset,” McKinsey declared. “The initial enthusiasm and flurry of activity (around AI) is giving way to second thoughts and recalibrations as companies realize that capturing AI’s enormous potential value is harder than expected.” More than just a passing observation, McKinsey was blunt. “With 2024 shaping up to be the year for AI to prove its value,” they wrote, “companies should keep in mind the hard lessons learned … that competitive advantage comes from building organizational and technological capabilities.” It isn’t that AI has no role, it made clear, referring specifically to generative AI. But incorporating it into any organization’s strategy cannot take form as a simple add-on. To leverage AI effectively means “rewiring the business.” Any experienced leader with a memory stretching beyond any one innovation cycle understands that strategy is an ongoing recalculation—a reconsideration, reconfirmation, and if need be a reorganization—of how all the pieces and parts that give an organization advantage fit together. Including its tools. Thoughtlessly adding anything new or blindly jumping on the latest bandwagon in and of itself yields no lasting advantage. As magical as AI seems right now, it must be part of this larger recalculation. It is not a strategy in and of itself. Without a doubt, AI will bring change–it already has–and advantages, though likely different than those predicted. It will not, however, displace the fundamental truth that ongoing success requires far greater strategic thought and effort. EXPERT OPINION BY LARRY ROBERTSON, FOUNDER, LIGHTHOUSE CONSULTING @LRSPEAKS