When the business process outsourcing (BPO) leaders pour lukewarm water over AI, one hears the air leaking from a bubble. BPOs have been a key part of the hype around AI as a business solution. The McKinseys, Genpacts, Deloittes, and PwCs for years have touted AI and as a result, made large consultancy fees. AI now proliferates for every business problem. Whether it’s generative, (still kicking around) machine learning, NLP, LLMs, agentic, robotic process, and now sovereign AI (domestically developed and powered)–it’s been positioned as the solution for simplifying processes and reducing administrative burden. Of course, a fair chunk of this involves getting rid of those pesky human factors in overseeing whether these new systems and software actually work, or reducing them to the lowest cost possible, to pay for all the AI spend.
Unfortunately for the BPOs, their customers are telling them that AI Is Not Quite All That. In fact, for the money they have spent, it hasn’t performed. Yet. But they remain optimistic, a neat bit of cognitive dissonance or perhaps justification.
The Deloitte global survey of 3,235 business and IT leaders confirms the gloomy news to date–yet it’s full speed ahead. Only 20% have experienced revenue growth as a result of AI. Transformation is coming along slowly; 25% of those surveyed believe that AI is transforming their organizations, which corresponds to 84% not redesigning jobs or work around AI capabilities. In this area, there’s a lot of resistance. While 55% of workers are reportedly open to AI technology, only 13% of workers are highly enthusiastic about AI, 21 percent would prefer to avoid it, and 4% actively distrust it. There’s also a lot of pilot-itis. Only 25% report shifting 40% or more of their AI experiments into live use, though optimistically they project that will increase to 54% in three to six months.
Yet they’re justifying AI. Totally. 66% reported that it improves productivity and efficiency, which contradicts the low revenue growth. 58% of companies are already using it to some extent, with adoption to hit 80% within two years. 74% of companies plan to deploy agentic AI within two years, even though only 23% are using it now and 21% have a model for governance of autonomous agents–a high risk level. 42% believe their strategy is ‘highly prepared’ for AI adoption. Another part of AI adoption has surfaced–sovereign AI, to reduce dependency on foreign sourcing, vendors, and infrastructure. 83% reported that this was at least moderately important to them. The Register 21 Jan, Deloitte’s State of AI in the Enterprise report (PDF, January 2026)
PwC’s larger survey of 4,454 business leaders in their 29th Annual Global CEO Survey contains gloomier and more detailed feedback for AI advocates. “Most CEOs say their companies aren’t yet seeing a financial return from investments in AI.” Only 30% reported increased revenue and 26% saw lowered costs. More than half–56%–did not see either lower costs and higher revenue. 22% reported an increase in costs due to AI.
Another finding is that isolated AI projects aren’t delivering value. Companies lack a clear strategy in building AI foundations such as clearly defined road maps and sufficient levels of investment.
A relatively small proportion of their surveyed CEOs say they’re applying AI to a large or very large extent to areas such as demand generation (22%); support services (20%); the company’s products, services, and experiences (19%); direction setting (15%); or demand fulfilment (13%). In a previous survey, only a tiny minority of workers–14%–are using generative AI daily. PwC’s report goes on to identify many other factors reshaping global business and influencing growth, in context confirming that depending on AI as a quick fix is not paying off. The Register 20 January, PwC 29th Annual Global CEO Survey (January 2026).
Reality tends to bite. Many of last year’s corporate layoffs were attributed to heavy AI investments that weren’t paying off, but books needed to balance by year’s end and it was taken out of human capital. Layoffs are projected to continue across all industries in 2026. Books balance another way, though. The AI bubble is deflating from Inflated Expectations into the early stages of the Trough of Disillusionment. How long it will take to move to the Slope of Enlightenment is anyone’s guess–two years, five, a decade? The useful tool of the Gartner hype cycle strikes again–as it did with telehealth and health tech. Separately, we’ll be looking at OpenAI’s ChatGPT for Healthcare and Anthropic’s Claude for Healthcare.
Most Recent Comments