If You Start with AI, You’re Already Doing It Wrong!
Are you surprised that—despite making hefty investments in AI—your organization isn’t seeing the meaningful returns you expected? You’re not alone. Many leaders are finding themselves in this very position: excited by AI’s potential, investing in shiny new models, yet falling short when it comes to real business impact.
Main reason?
AI doesn’t yield its full value when it’s confined to a handful of disconnected use cases. It’s not enough to sprinkle AI into a few projects and hope for transformation. Without a connected, enterprise-wide strategy that’s deeply aligned with your core business goals, even the most advanced AI tools can fall flat.
Too often, organizations are getting the order of operations wrong. They are diving into use cases prematurely or delegating the AI agenda entirely to technical teams, missing the opportunity to lead with vision. And that’s where the real risk lies—AI becomes a siloed experiment instead of a game-changing lever for growth, innovation, and competitive advantage.
The truth is, the strongest AI strategies rarely begin with AI. They begin with purpose. They begin with the company’s north star—its business strategy. From there, AI becomes the fuel, not the destination.
According to a recent Economist Impact report, while 66% of executives believe AI is critical to their success, only 38% believe their use of AI gives them a competitive edge. Even more stark is the sentiment from the C-suite, with three out of four leaders agreeing that failure to scale AI in the next five years could result in their company going out of business.
These findings raise an essential question: If AI is so important, why are so many companies failing to realize its full value?
It’s because the strongest AI strategies don’t actually begin with AI at all. They begin with a deep understanding of the business’s north star: its core strategy, customer problems, and long-term goals.
When AI is implemented in isolation, disconnected from a clear business context, it becomes just another shiny object. But when it's used as a fuel to drive existing business strategies, anchored to KPIs that reflect competitive advantage, it becomes transformative.
This is a lesson well-known to product managers. Successful product development is built on understanding the "why" and "what" before jumping into the "how." AI-powered product design and development is no different.
Too many teams begin with a technology-first mindset: “We have GPT, so let’s find a way to use it.” This approach may result in clever features, but rarely leads to lasting customer value or business impact. Instead, product teams should be asking:
What are our customers’ biggest pain points?
What value can we deliver that competitors can’t?
How can data and AI help us do that better, faster, or cheaper?
Once those questions are answered, AI becomes a tool in service of the solution, not the solution itself.
The companies that will win in this new AI-driven era aren’t necessarily those with the most powerful models, but those with the clearest strategies. And that strategy must begin with business outcomes, not algorithms.
The best AI strategies begin with a simple question: “What do we want to achieve?”
Only then should the conversation turn to how AI can help us get there.
If you're unsure where to start or facing challenges aligning your AI initiatives with your business objectives, I can help in identifying the core issues and crafting a customized strategy that ensures your AI efforts are perfectly aligned with your organization's goals and growth trajectory. #openforconsultingopportunities
