Despite heavy investment in artificial intelligence across industries — with roughly 88 % of companies reporting regular AI use — many organisations are finding that adoption stalls and performance gains plateau once the initial excitement wears off. According to analysis in Harvard Business Review, executives frequently observe that while teams experiment with new tools, they don’t integrate AI deeply into everyday workflows, leaving leaders increasingly concerned about whether the technology will deliver meaningful return on investment.
One of the core reasons adoption stalls is that businesses often treat AI as a stand-alone experiment rather than a fundamental change to how work gets done. Many organisations run numerous pilot projects but never define clear criteria for moving beyond proofs of concept, leading to a situation where tools are used ad hoc rather than embedded into operations — a pattern sometimes called the “pilot trap.”
Organisational barriers also play a major role. Companies frequently struggle with data quality, infrastructure complexity and skills gaps, meaning that models don’t perform well or aren’t used at scale. Without clean, well-governed data and personnel who understand how to align AI capabilities with business goals, adoption often stalls even when leadership is enthusiastic.
Finally, a lack of strategic alignment and workflow redesign can undermine adoption. When AI is simply added on top of existing processes without re-thinking how tasks are structured, employees may see little difference in their daily work — and some even resist using the tools. Successful adoption, the report suggests, requires not just technology deployment but organisational change, clear objectives and measurable outcomes.
