It’s likely that many enterprises have created — or are at least considering — AI policies that clearly lay out approved AI tools and their uses, set up training programs for employees to help them use the tools in their jobs, and establish guardrails around those systems to avoid issues such as security vulnerabilities and data bias.
But how many of these policies have received the blessing of employees? It’s a key question, because many workers are highly wary of AI.
They worry that it will cost them their jobs, either by taking over their work or because companies will cut jobs and use the savings to fund investments in AI research and infrastructure. They worry about AI-powered performance tracking software impacting raises and promotions. They worry about AI screening of job applications for future roles.
Even employees who have embraced AI to assist their work have reason to worry. Many say that using generative AI tools saves them time, but the time savings are eroded by “botsitting” — having to check and recheck output, provide missing context, fix errors, and go through multiple iterations before the desired outcome is achieved. They may also have to wade through “workslop,” low-quality genAI output that hasn’t been properly vetted by co-workers.
Additionally, workers say that as AI makes them more productive, their workload keeps increasing. All of this can add up to “prompt fatigue” or “AI brain fry,” mental exhaustion that affects heavy genAI users, particularly when they bounce between multiple AI tools.
AI policies that don’t take these factors into account are apt to be problematic. Employees may even organize to protect themselves from AI in the workplace. Indeed, tech pros are increasingly interested in unionizing, driven in part by the incursion of AI.
It doesn’t have to come to that. Company leaders can proactively work with their employees to develop AI policies that take employee well-being into account. The result might be stronger AI adoption, better business outcomes, and a happier, more productive workforce.
The 2026 Tech Sentiment Report by technology career marketplace Dice found that professionals are generally not resisting AI itself, “but rather, they’re looking for clarity around how it will affect their jobs, careers, and workplace decisions,” says Paul Farnsworth, president of the firm. “The research suggests that employee buy-in comes from making AI feel like something being done with workers rather than to them.”
In many cases, IT management runs the deployment of AI, and this can ultimately result in employees being left out of any decision making.
“When IT leaders drive deployment, they ask questions about integration, security, and capability,” says Amy Loomis, group vice president, Workplace Solutions at IDC. “That is not the same as asking workers how AI could actually improve their day, where they waste time on tasks that add no value, and where a well-designed tool would make a real difference.”
Following are some key steps to building an AI policy everyone can agree on. Bear in mind that any worker protection items should be in addition to the usual corporate governance, risk, and compliance AI policies, not a replacement for them.
Invite input from everyone involved
It might sound obvious but can’t be overstated: the only real way to produce an AI policy that employees will accept is to get their input.
“We started by surveying our employees through SurveyMonkey to see what they were already using and why,” says Monica Washington Rothbaum, COO and senior attorney at law firm J&Y Law. “Then we sat down with every department, and involved operations, IT, HR, and leadership from the beginning. We wanted to understand the opportunities, but we also wanted to understand the risks” of AI.
Most AI policies “fail when they’re created in a conference room and handed down from the top,” Rothbaum says. “The people using these tools every day need to be part of the conversation. That’s why transparency became a major focus for us” in creating an AI policy.
Organizations should include employees in policy development, pilot programs, and feedback processes, Farnsworth says. This is especially important because Dice research found that only 48% of organizations have formal AI policies, while nearly one quarter of professionals surveyed said they’ve used AI without manager approval.
Keep the lines of communication open
Creating an AI policy is not a one-and-done proposition. Organizations need to keep communicating with employees as AI and tools evolve.
“We communicated updates during company all-hands meetings, through email, in Microsoft Teams, and through department-level discussions,” Rothbaum says. “We even designated a member of our marketing team to oversee communications around AI adoption so there was clear ownership and accountability.”
The biggest mistake organizations make is treating AI like standard software, Rothbaum says. “It’s not. It’s an operational change,” she says. “It’s a communication challenge. It’s a governance challenge. The technology itself is often the easy part. The hard part is deciding what data can be used, who has access, how outputs are reviewed, and how the organization remains compliant while the technology continues evolving.”
Address fears about employment
One of the biggest drawbacks to AI adoption, from the standpoint of many employees, is the worry that AI tools will ultimately take away their jobs or many of their responsibilities.
Indeed, this has already been the case at some tech companies. A majority of non-AI technology professionals think AI eliminates more jobs than it creates, according to the Dice report, and three quarters think
junior-level workers are most at risk of displacement.
“Reassurances that no jobs will be lost ring hollow when workers can see
reorganizations happening around them,” Loomis says. “The organizations that sustain worker trust communicate specifically about what is changing, what it means for individual roles, and what the organization is committing to in return.”
One way to get around these concerns is to include provisions in policies that require any decisions around individual workers’ employment to be made by a human. That way no one can be dismissed from their job at the discretion of a machine.
Ensure access to training programs
Another way to gain workers’ support for AI policies is to include provisions about access to ongoing training and educational programs designed to build on their existing knowledge and provide them with valuable new skills.
“Employees are more likely to embrace AI when they see opportunities to grow alongside it,” Farnsworth says. “As AI becomes increasingly embedded in daily work, organizations should invest in AI literacy, upskilling, and career development programs to help employees adapt to changing job requirements.”
And those programs should be codified in AI policies. Guaranteeing workers access to training that evolves with the technology and enterprise workflows “requires treating training as a policy commitment with defined standards, timelines, and completion tracking,” Loomis says.
“Effective AI training does two things: it teaches workers how to use specific tools in the context of their specific roles, and it builds the human skills, judgment, critical thinking, and adaptability that determine whether workers can use AI well rather than just technically. Both are necessary,” she says.
When training is treated as a one-time event rather than a continuous policy commitment, Loomis says, adoption stalls and distrust grows. Ongoing “human skills training is gaining explicit recognition as core to
effective AI use,” she says.
Adopt guardrails against harmful uses of AI
This needs to be a standard component of any AI policy. But the language of proper and improper uses of AI tools and data must be clear for everyone in the workforce.
Such guardrails not only address cybersecurity and regulatory concerns, but can help prevent uses of AI that result in discrimination.
“The organizations that get the most value from AI won’t be the ones that adopt it the fastest,” Rothbaum says. “They’ll be the ones that communicate clearly, train consistently, and build the right guardrails before they need them.”
Confidential, client, firm, or employee information may not be entered into any AI tool unless explicitly authorized and approved, according to the J&Y Law policy.
Emphasize the positives of AI
Policies will of course include restrictions on the use of AI and rules around avoiding risks, but they also need to share how workers can leverage tools to help make their jobs easier or more fulfilling.
“One thing we’ve seen is that effective AI policies aren’t just lists of restrictions,” Farnsworth says. “Instead, they provide employees with clear guidance on how to use AI responsibly and confidently in their work. At Dice, our AI policy encourages employees to use AI when it can improve productivity, while establishing guardrails around data security, confidentiality, and human oversight.”
A good policy will help employees better understand that AI presents not just risks, but opportunities as well.
More on AI in the workplace:
- How tech workers can protect themselves in the age of AI
- The AI tech job slaughter gets real
- Burned out by bots: The rise of prompt fatigue in the workplace
- ‘Botsitting’: The AI time-savings killer only governance can stop
- AI ‘workslop’ is the new productivity killer
- Do you need an AI ethicist?
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