As studies show persistent gaps in trust around AI, organizations risk patchwork adoption and faltering transformation projects
In recent months, ‘doomsday’ AI warnings from high-profile leaders have become a staple storyline for media outlets.
Take September as an example.
Bill Gates warned it could “cause a billion deaths” if left unchecked; a group of AI ‘godfathers’ featuring OpenAI’s chief scientist cautioned that it could spark an “intelligence explosion… threatening human control over AI systems’; and even the Pope claimed that fears of rogue AI bots are not “fake news.”
These stories are front-page items for a day, maybe two. Then they fade into background noise that’s becoming increasingly problematic for organizations and their AI plans.
Whatever your stance is on such claims, their veracity, and the motivations behind them, the overriding outcome is that they have embedded a culture of fear among workers.
Mind the gap
This is not a new problem.
For years, executives and experts have weighed in on claims, working to mythbust or provide reassurance over concerns on areas including job security. And yet, people remain scared about what AI’s impact will be.
Workplace studies have persistently shown AI trust gaps, with employees failing to buy into leadership adoption plans.
AI SaaS firm WalkMe recently surveyed 3,750 executives and employees across 14 countries, from enterprises with 1,000 or more employees, for its 2026 State of Digital Adoption report. It paints a troubling picture for employers and investors.
While enterprise AI investment surges to record levels, a disconnect between workers and leadership is growing.
61% of executives trust AI for complex, business-critical decisions, dropping to just 9% for workers. And while 88% of executives are confident employees have adequate tools; only 21% of workers agree.
These gaps are everywhere. WalkMe’s study also finds that 78% of executives want to discipline shadow AI, despite only 21% of workers having been briefed about AI policies and warned about breaches. Another 2026 study, this time from Multiverse, finds that while 59% of leaders believe employees work with AI every day, only 42% of employees report doing so.
PwC’s 2026 Global Workforce Hopes and Fears Survey — which surveyed close to 50,000 workers across 48 countries — adds more color.
It finds that while some ‘front-runners’ (14% of employees) boast AI capabilities and receive learning opportunities, the majority of employees (56%) make up an ‘engine room’ who are not frequent users of generative AI daily and lack access to learning and development resources.
This is a dangerous combination. When people are bombarded about the possible dangers or risks of AI in their private lives, and then given little professional support or instruction from their managers and leaders, friction is inevitable.
WalkMe reports that workers now lose the equivalent of 51 working days a year to technology friction, up 42% from 2025 — a three-year high — and reveals that the primary cause of this multi-million dollar problem is absent workplace guidance.
Cutting through the noise
Media noise and headline hysteria are not going away any time soon. Employers can do little to control this, and must accept that the starting point for the majority of their workforce will be one of skepticism, if not fear, about plans for AI rollouts.
Failing to establish trust risks slowing progress, while building it can accelerate adoption — Edelman identifies knowledge and trust as the two top drivers of increased enthusiasm for the growing use of AI.
Leaders can control how they reach, reassure, and prepare employees, and assess whether the message they are trying to deliver is cutting through.
Internal communications teams, executives, and managers must work together to create multiple, cross-functional channels and two-way touchpoints between leadership, AI champions, and employees.
Rollouts and projects should be communicated early, transparently, and with an emphasis on role-specific task changes rather than vague promises. Staff should be involved in the decisions about how, why, and when AI can augment existing work.
Role-modeling builds trust
Leadership and managers must also remember to walk the walk. Role-modeling can also help to build trust.
At Microsoft, for example, Chief Strategy and Transformation Officer Kathleen Hogan (formerly Chief People Officer) recently detailed how the firm has built workforce trust in its AI strategies.
“In our experience, leaders set outcomes and accountability, while the people closest to the work see where AI adds value and where human judgment must stay central,” Hogan explains. “Managers connect the two, and their role-modeling and support has been one of the strongest predictors of success.”
Microsoft finds that when managers actively model usage, the trust workers place in agentic AI rises significantly, as does the value it creates.
“Employees on teams where managers create psychological safety are 1.4 times as likely to be high-frequency users of agentic AI,” Hogan continues. “Where employees have context, capability and agency, they can become the engine of transformation.”
‘Think hard’ about skills development
Company-wide education is also key to removing fear, building trust, and eliminating friction.
By default, employers tend to focus on providing the most detailed resources and training opportunities for staff who are already confident and comfortable with AI. Investing in these champions (‘front-runners’) is pragmatic, but the remaining majority of the workforce must not be neglected.
In PwC’s study, just two in five of ‘engine room’ workers, and barely half (51%) of all workers, report having access to the AI learning and development resources they need.
“There is a real risk that the global workforce is starting to move at different speeds,” explains Pete Brown, Global Workforce Leader at PwC. “Leaders need to think hard about where they invest in skills, how they give people the opportunity to adapt, and how they hold on to the capabilities they most need.”
Microsoft takes such an approach, with leaders “responsible for setting a clear ambition, helping employees build the skills to contribute and giving them a meaningful role in deciding how the work changes.”
“We are creating hands-on ways for employees to build those skills,” Hogan says. “This includes an early in career development program which matches “emerging engineers with experienced preceptors and AI-assisted learning.”
Without structured opportunities to learn and develop, employees will continue to fear the impact of a technology they don’t understand. The headlines they see across social and traditional media will fill gaps in understanding. And the inevitable lack of trust and friction that follows will damage productivity and cause expensive AI projects to falter.
