Artificial intelligence is being adopted at a record pace across industries, but many companies are finding that the results fall far short of the hype. According to Greg Davis, CEO of Bigleaf Networks and a veteran of scaling technology companies past the $100 million mark, the problem is rarely the AI itself — it is the fragile foundation underneath it.
“Companies aren’t struggling because they picked the wrong AI tools,” Davis writes in a new piece for Entrepreneur. “They’re struggling because they’re trying to layer AI on top of systems that weren’t built to support it.” With 25 years of experience across cloud, mobile and SaaS transformations, Davis argues that each wave of innovation carried the same promise — and the same pitfalls.
Unstable infrastructure accelerates bad decisions
One of the most overlooked mistakes, Davis says, is deploying AI on top of laggy or unstable systems. Rather than correcting for those weaknesses, AI amplifies them — making poor decisions faster and at greater scale. Leaders who expect AI to fix operational chaos are likely to see that chaos compound instead.
Complexity in tech stacks creates friction, not efficiency
A second critical gap is fragmented technology stacks. When AI tools are bolted onto disconnected, overly complex systems, the result is more friction — not less. Davis emphasises that simplification and integration must come before any AI layer is introduced. Without a coherent foundation, even the best models produce unreliable outputs.
The broader message is a familiar one in technology leadership: tools do not transform organisations — readiness does. As AI expectations continue to climb in 2026, Davis’s counsel is a timely reminder that the prerequisites for success are operational and structural, not simply a matter of selecting the right platform or vendor.