AI Panic: Why Strategy Must Come Before Hype
The surge in AI interest over the past two years has pushed businesses across industries into a frenzy. From boardrooms to product teams, everyone is being asked the same question: "What’s our AI strategy?" Unfortunately, in many cases, the answer is little more than a reaction to market pressure, not a plan rooted in business need, technological readiness, or clear ROI.
The FOMO-Fueled Rush
Companies are afraid of being left behind. This fear has led to rushed investments, pilot projects with no direction, and executive decisions made more for PR than performance. According to Gartner, up to 85% of AI projects fail to deliver business value. That’s not just inefficiency — that’s wasted time, capital, and trust.
We’ve seen organizations deploy large language models without understanding how to fine-tune them, plug in AI-powered tools without considering integration with core systems, and hire AI consultants without clear deliverables. The result is a growing number of expensive experiments that don’t scale or stick.
What’s Missing: Use Case, ROI, and Alignment
At the root of the problem is a lack of discipline in three areas:
The Hidden Costs of Hype-Driven Investment
When companies pursue AI without a strategy, the costs go beyond budget overruns. Technical debt builds up as teams scramble to retrofit AI into systems that weren’t designed for it. Teams burn out. Stakeholders lose confidence. And while leadership chases the next trend, core business problems remain unsolved.
Worse, failed AI initiatives create resistance. Once people experience poorly deployed AI, they become harder to convince the next time, even when the use case is strong.
What a Thoughtful AI Strategy Looks Like
A disciplined approach to AI doesn’t start with "What can this model do?" but with "What problem do we need to solve?" From there, a strong strategy involves:
Not every problem needs AI. And when it’s the right fit, AI must be treated like any other strategic investment — with governance, accountability, and clear KPIs.
The Way Forward
Hype has its place — it brings attention and resources. But attention without direction leads to waste. The companies that succeed with AI will be the ones that resist the panic and ask better questions: Is this solving a real problem? Do we have the data? Can we measure success?
AI is not a race to adopt. It’s a process to understand. Strategy must come before hype, or the cost will be much greater than missing a trend. It will be missing the point entirely.