AI Doers Drown Out AI Naysayers

For most of last year, AI lived in a space dominated by two extremes. It was talked about constantly but trusted sparingly. Companies discussed it, budgeted for it and ran pilots, yet stopped short of giving it real responsibility. There was hesitation in the shift from automating workflows to agents with autonomy.

As 2026 begins, that hesitation is no longer the norm. Enough organizations crossed the line from experimentation to use that the argument about whether AI is “real”  has largely been resolved.

That shift was easy to miss because the public narrative moved in a different direction.

Throughout 2025, three competing stories dominated headlines. One framed AI as an existential risk that demanded restraint above all else.

Another dismissed it as an overhyped bubble fueled by investor enthusiasm rather than real value. A third argued that the space had become so saturated with “.ai” announcements that meaningful progress was impossible to distinguish from noise.

Those debates filled panels and opinion pages, but they obscured what was happening inside companies responsible for building products and running operations.

Why Trust Lagged Capability

Inside those organizations, the question was never whether AI was interesting. It was whether it could be fully trusted. For much of the year, the answer was no. AI was used as a helper, not a decision-maker. It summarized, suggested and analyzed, but humans remained firmly in control of outcomes. Autonomous systems touch sensitive parts of a business, from customer relationships to operations to money. Until leaders felt confident that AI could operate reliably within those boundaries, its role remained limited.

The Q4 Inflection Point

What changed late in the year was not the technology itself, but how companies judged their own readiness and that of the technology.

PYMNTS Intelligence followed 60 chief product officers at billion-dollar companies throughout 2025, and the data shows a clear shift. In August of 2025, nearly all (98%) said they were unwilling to grant autonomous agents any meaningful authority.

By November, that position had softened in a measurable way. Between August and November, the share of firms merely considering AI for core operations dropped from 52% to 30%. Active deployment jumped to 23%. By November, nearly 40% of enterprise product leaders had given autonomous agents real access to systems that actually run the business. These were no longer controlled demonstrations. They were real uses, tied to real outcomes.

The shift did not remain confined to technology companies, which were expected to move first.

Some of the fastest change came from goods and manufacturing firms, where almost no one had live deployments in August and nearly one in five did by November, often in supply chains, procurement and logistics.

Services followed a similar path over the same period, surging from 4% to 25%.

What began as a cautious talking point in August became operational by December.

Learning Replaced Waiting

This late-2025 shift wasn’t about automating isolated tasks. Companies stopped waiting for certainty and started learning by doing. Earlier in the year, many treated AI as a set of tools they could layer onto existing workflows. That approach limited its impact and delayed learning.

As the year went on, more teams began connecting AI across processes, allowing it to influence decisions and then measuring what happened next. Some focused on efficiency. Others looked for stability, speed or better use of people’s time. The motivations varied, but the result was the same. Once outcomes could be measured, confidence followed. Adoption was inevitable.

Consumers Were Already There

Consumers reached this point earlier, and their behavior quietly set expectations that bled into the workplace.

By August 2025, PYMNTS Intelligence found that nearly two thirds of consumers expressed interest in autonomous AI assistants across a wide range of everyday activities, most notably healthcare (71%), travel planning (70%) and financial management (66%). Among the 29 million power users who already used AI-native model every day to complete 25 or more of the 54 distinct tasks that we monitor, resistance to autonomy to handle day-to-day decisioning had nearly disappeared.

As many report using these models to help them with their daily work-related tasks: writing emails, ad copy, job descriptions, summarizing long documents. Over 7 in 10 power users say it would be harder or slower to do their jobs without the use of AI-tools, and 13% of them said they doubt they’d be able to do their work without it.

Consumers didn’t spend much time debating whether AI should act. They cared about whether it worked. As companies moved from discussion to deployment, they were catching up, in many cases, because their employees and customers were pulling them in that direction.

From Experiment to Infrastructure

By the end of 2025, AI had begun to show up where executives pay attention. And CEOs and CFOs began talking about things like improving productivity per worker. Faster cycle times. Reduced error rates. Better margins. Agents were no longer side projects or PowerPoint theater. They were part of how work got done.

As more data accumulates in 2026, those signals will grow clearer. Performance has a way of settling arguments that opinion cannot.

Of course, there will still be failures. Some companies will overpromise. Some deployments will fall short. No different from how every major technology transition unfolds. But those moments won’t define AI any more than the dotcom bust defined the internet. What matters is that enough organizations have moved past the question of whether to use AI and are now focused on how to use it well.

When the Argument Ends

That is why the balance — and the conversation — shifts in 2026. Not because the critics disappear, but because they no longer set the frame. Their voice is no longer the loudest. The story is no longer written by who is most vocal, most alarmed or most skeptical. It is written by the organizations that have already put AI to work and can show what changed as a result.

In 2026 and beyond, AI won’t be judged by how loudly it is debated. It will be judged by how quietly it becomes indispensable. And once that happens, the argument fades into the background, where it belongs.

 

Find more observations and insights from Karen Webster about what may lie ahead:

What 2026 Will Make Obvious