AI is making businesses more productive. But are those gains leaking before they reach the bottom line? For 23% of CEOs, the answer is yes. So what's getting in the way? 1️⃣ 33% Legacy tech and ways of working 2️⃣ 32% Organizational complexity and regulation 3️⃣ 17% Saved time isn’t being put to better use. The latest CEO outlook explores what’s getting in the way and what leaders can do about it. https://ow.ly/wFOc50ZUlE7 #ShapeTheFutureWithConfidence #CEOs
The goal of AI was NEVER to make the lives of employees easier, just to eventually give them more work to do. No surprise, CEOs lied about this nonstop during the initial boom. The bottom line is the only one that matters, and always has been. Your leaders are investing in AI to replace you, not help you. Period. All of them. 100%.
The operator read on this is pretty simple: saved time doesn't automatically become productive time. Across three stores, every efficiency gain I ever found got quietly absorbed by the day unless I deliberately pointed it somewhere that mattered. Number three on that list is the whole game. The tech did its job, and then nobody owned what came next. The companies actually keeping the gains are treating those saved hours like inventory, with someone accountable for where they go.
From my experience with regulated entities, I would rank the continuation of legacy systems and ongoing regulatory restrictions as the factors most impacting productivity gains that could have otherwise been achieved from the adoption of AI.
EY's 17% may point to a bigger change. As AI makes analysis, scenarios and experiments cheaper, companies will have more and more credible things they could do with the time they save. The CEO's problem may become less about finding good options and more about killing them. Not bad ideas. Good ones. Because AI can give a company ten credible ways forward. It still has to commit its people, money and attention to a few. AI may make saying "no" one of the most valuable CEO decisions.
These numbers like impressive, but they raise more questions than they answer. Where is the evidence that AI created the productivity gains in the first place and how exactly were they measured? Without the underlying data, this feels less like an analysis of AI impact and more like marketing wrapped in statistics.
AI can improve productivity, but the real value comes from improving the processes around it too. Faster doesn’t always mean better.
Saved hours need ownership, not optimism. Without a clear destination, they vanish into the daily grind.
The organizational complexity finding stands out to me. Technology can create capacity, but capacity doesn't automatically become value. Leaders still have to redesign processes, clarify decision rights and determine where the time being saved should be reinvested. Otherwise, organizations can become more efficient at doing work that may no longer need to be done the same way.
The interesting question is whether governance is part of the friction — or part of the mechanism for converting AI productivity into value. Good governance should clarify decision rights, ownership, acceptable use, review thresholds and accountability so that newly created capacity can actually be redeployed with confidence. If governance and compliance are added only after AI adoption, they may become friction. If they are designed into the operating model, they can help organisations scale AI productivity into sustainable business value.
AI 🤖 has a huge impact also on our business 🧑💼