When AI Enthusiasm Becomes a Governance Problem
A troubling pattern has emerged among tech sector observers: some leaders at major technology companies appear to have lost all sense of proportion in their relationship with artificial intelligence. Outsized announcements, impossible-to-keep promises, strategic decisions completely disconnected from operational reality. In Silicon Valley and beyond, the term "AI psychosis" is being used openly to describe this runaway enthusiasm among the digital elite.
For an SMB leader, this debate might seem distant. But it has direct and practical implications — because its effects ripple all the way down to your business.
Leadership Noise, SMB Budgets
When a Silicon Valley CEO announces that AI will "revolutionize everything within 18 months," software vendors, consulting firms, and sales reps echo that message in boardrooms across the world. The result: SMBs face mounting pressure to invest fast and big, often without the information needed to make sound decisions.
Tech leadership hype creates a shockwave through procurement cycles. AI projects get launched in a hurry, driven by the fear of "missing the wave" rather than by any rigorous analysis of expected return on investment.
Three Warning Signs to Watch for in Your Organization
1. Decision by imitation. If the main justification for an AI project in your company is "our competitors are doing it," that's a red flag. AI adoption should stem from an identified business problem — not from a reflex to follow industry peers.
2. No definition of success. Before signing a contract or mobilizing your teams, ask one simple question: how will we know in six months that this project succeeded? If no one can answer precisely, the project isn't ready.
3. Unanticipated technology lock-in. AI enthusiasm can push organizations to sign quickly with a vendor. Take time to evaluate reversibility: can you switch solutions in two years without losing your data and workflows?
Clarity as a Competitive Advantage
For SMBs, there is a structural silver lining: you don't have shareholders pushing you to outbid competitors at press conferences. You can afford to be methodical.
In practice, that means requiring a proper scoping phase before any AI project kicks off: which process are we trying to improve? What data will we use? Who on the team will own the change? These questions may sound basic — yet they are absent from most failed projects.
The companies getting the most out of AI today are not the ones that followed the grand speeches of big tech CEOs. They are the ones that defined a realistic scope, ran a quick test on a real use case, measured the results, and iterated from there.
Keeping a Cool Head in an Overheated Sector
AI offers real, measurable opportunities for SMBs: automating repetitive tasks, analyzing customer data, supporting content creation, and streamlining sales operations. But these benefits are built on solid foundations — not on headline-grabbing announcements.
The "AI psychosis" of the tech elite is, in effect, an invitation to cultivate what large organizations struggle to hold onto: a clear sense of priorities, operational grounding, and the ability to say no to what doesn't serve your business model.