Lack of Governance Is Devaluing AI Investments Globally

It has been over three years since GPT-4 passed the Bar exam. That milestone got me believing that LLM AI was going to be a world-changing technology. I expected that learning to use AI effectively would be as fundamental as learning how to use a computer.

Most companies have tried to leverage AI as a tool in one way or another since then. Some have incorporated AI into their software or services to meet new customer requirements, and most have sanctioned using AI for writing emails or similar small but tedious tasks. Yet, most companies have seen little impact if any. Many early evangelists have taken a step back because they see LLMs as unreliable and find fixing hallucinations too tedious.

PWC’s global CEO survey, published in January, supports this fact. It shows that more than half of CEOs have seen no positive benefits from AI adoption. The vanguard AI users who are realizing both cost savings and increased revenue represent only 12% of companies.

Over the past decade I have noticed a pattern of promising technologies that garner significant attention but fade with limited impact to organizations. The Internet of Things, smart grids, 5G networks, digital twins, and quantum computing are all still present but not making much difference in our daily lives and not driving better performance for enterprises.

These technologies are promising but they often fail to bridge the gap between technical capability and operationalized in business. Companies need a structured approach to effectively bridge that gap and unlock the potential value of emerging technologies. Doing this has the potential to catapult a company ahead of competitors instead of worrying about how to avoid being disrupted.

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So what should leaders focus on when they are trying to build governance to manage innovation more effectively?

Scout and track emerging technologies – Early visibility buys you time to plan a strategic response as the technology develops.
Assess the real capabilities – Understanding what innovations can and cannot do shapes use cases for both you and your competitors.
Plan for relevance – Identifying circumstances that make an innovation strategically important lets you avoid disruption and be the disruptor.
Pilot before scaling – Educating leadership through experimentation lets you refine use cases and confirm adoption pathways.
Learn as much from success as failure – Lessons create value when they are properly documented and reused regardless of the outcome.