Creating an AI Workplace Policy: 5 Questions Every Business Should Consider

At Rockwood's 14th annual Leadership Summit, opening speaker Wade Wyant began a session on AI implementation with a warning few attendees expected: businesses need to start thinking about policies for AI-enabled glasses.

At first, the topic may have sounded unusually specific. Most business leaders are still focused on familiar tools such as ChatGPT, Microsoft Copilot, automated customer service platforms, and AI-assisted analytics. Glasses hardly seem like the most immediate concern.

But that was precisely the point, and it got us thinking.

AI is moving beyond applications that employees intentionally open and use. It is increasingly being embedded in glasses, meeting platforms, recruiting systems, security tools, manufacturing equipment, smartphones, and everyday software. In many cases, employees and business owners may not even recognize when AI is operating or understand what information it is collecting and how that information is being used.

AI-enabled glasses are not the whole story. They are an early illustration of a much larger shift toward what might be called ambient AI: technology that can continuously observe, listen, interpret, recommend, and act in the background.

For business owners, the goal should not be to stop that progress. These tools can improve productivity, make expertise more accessible, support employees with disabilities, shorten training cycles, strengthen quality control, and help people make better-informed decisions.

However, greater capability also creates greater responsibility. Here are five questions every leadership team should be discussing.

1. Where Is AI Already Operating in Our Business?

Many companies have more AI in their operations than their leaders realize.

That makes an AI inventory a practical first step. Leaders should understand:

AI capabilities may already be embedded in recruiting platforms, customer relationship management systems, cybersecurity tools, transcription applications, expense software, production equipment, cameras, and employee productivity applications.

• Which tools use AI
• Who approved them
• What information they collect
• Where that information is stored
• Whether the provider may use company data to improve or train its models
• Which decisions the technology influences

This exercise does not need to become a months-long technology audit. Even a basic inventory can expose overlooked risks, duplicated tools, unauthorized applications, and opportunities to use existing systems more effectively.

The important distinction is between knowing that employees use AI and knowing how AI participates in the operation of the business.

2. What Happens When AI Can See and Hear the Workplace?

AI-enabled glasses and other wearable devices can provide meaningful benefits. They can offer real-time transcription, translate conversations, guide technicians through unfamiliar procedures, document inspections, and connect frontline employees with remote experts.

In an industrial setting, for example, a wearable device could help a technician identify a component, retrieve instructions without stopping work, or share a live view with a more experienced colleague. In an office, transcription and captioning tools can improve accessibility and reduce the burden of taking notes.

Yet the same device may also capture customer conversations, employee interactions, computer screens, proprietary processes, protected health information, or confidential documents.

Unlike a phone held visibly in the air, glasses may not make it obvious that recording or data collection is occurring. Current workplace guidance therefore recommends that employers evaluate whether existing policies adequately address recording, privacy, confidential information, safety, accommodations, data retention, and consistent enforcement.

A thoughtful policy should answer practical questions before an incident occurs:

• Where may wearable devices be used?
• When must the wearer disclose that a device is recording or transcribing?
• Is affirmative consent required?
• Which areas or conversations are off-limits?
• Can information be uploaded to a personal account?
• How long may recordings or transcripts be retained?
• How will legitimate accessibility needs be handled?

The answer may not be a blanket prohibition. In some environments, the operational value will be significant. But use should be deliberate, transparent, and appropriate to the setting.

3. Are We Delegating Decisions or Judgment?

AI can organize information, identify patterns, generate recommendations, and help teams move faster. Problems arise when a recommendation quietly becomes a decision.

Hiring and employee evaluation are especially important examples. Recruiting platforms may screen résumés, rank candidates, analyze assessments, draft interview questions, or recommend which applicants advance. Performance-management tools may summarize employee activity or identify supposed indicators of productivity and potential.

Even when an outside vendor supplies the technology, the employer remains responsible for how it is used. Federal employment protections still apply when AI or other technologies participate in hiring and employment decisions.

Business owners should therefore ask:

• What factors influence the system's recommendation?
• Has anyone tested whether the tool systematically disadvantages certain applicants or employees?
• Can a person question or appeal the result?
• Are managers independently evaluating the recommendation?
• Are accommodations available for candidates who cannot fairly use the technology?
• Would we be comfortable explaining the decision without referring to "the algorithm"?

Human review should not merely mean clicking "approve." It should mean that a qualified person understands the context, considers contradictory evidence, and retains genuine authority to reach a different conclusion.

4. How Do We Verify That the Person on the Other End Is Real?

Fraud has always relied on urgency, authority, and familiarity. AI makes all three easier to manufacture.
A convincing voice clone may be created from publicly available recordings. A fake video may appear to show an executive authorizing a transaction. A fraudulent email may closely match the language and tone of a trusted customer, supplier, or colleague.

The Federal Trade Commission has warned that AI-enabled voice cloning can facilitate impersonation, fraud, and misuse of biometric information.

The response does not need to be technically complicated. Companies can establish simple verification procedures for high-risk requests:

• Confirm changes to banking instructions through a known telephone number.
• Require a second approval for unusual payments.
• Verify urgent executive requests through a separate communication channel.
• Create an internal phrase or protocol for sensitive instructions.
• Train employees that a familiar voice or face is no longer sufficient proof of identity.

The most engaged and visible executives may be the easiest to imitate because recordings of their voices and images are readily available. Visibility is valuable, but businesses should recognize the security exposure that accompanies it.

5. Who Is Accountable When AI Gets It Wrong?

AI can produce an answer that sounds polished, specific, and confident while still being incomplete or incorrect. It can also reproduce errors contained in the data, documents, or assumptions it was given.

That makes accountability one of the most important questions for business owners.

Every meaningful AI use should have a clear human owner. That person should understand the intended purpose of the tool, what can go wrong, which results require review, and how errors will be reported and corrected.

The level of oversight should correspond to the potential consequence. Using AI to brainstorm headlines does not require the same controls as using it to prepare a customer quotation, evaluate a job applicant, create engineering instructions, make a medical recommendation, or approve a financial transaction.

The National Institute of Standards and Technology's AI Risk Management Framework similarly encourages organizations to manage AI according to its intended use, risks, limitations, and impact rather than treating every application the same.

Start With Operating Rules, Not a Perfect AI Workplace Policy

It may be tempting to hand the entire subject to the legal or information technology team. Both should be involved, but AI governance is ultimately a leadership responsibility.

The strongest AI workplace policies will be informed by how people actually work. Leaders should speak with employees across functions and ask where AI is already helping, where it creates uncertainty, and what guidance people need.

A useful starting framework is straightforward:

• Identify the tools already in use.
• Classify applications based on their potential impact.
• Define which information may and may not be entered or captured.
• Require meaningful human oversight for consequential decisions.
• Establish verification procedures for sensitive communications.
• Train employees using realistic examples.
• Revisit the rules as technology and business needs evolve.

The objective is not to eliminate experimentation. In fact, employees are more likely to use AI productively when they understand the boundaries.

That may be the most important lesson for business owners: AI does not remove the need for leadership judgment. It increases it.

AI-enabled glasses may be the issue that gets a leadership team's attention today. Tomorrow it may be an autonomous agent, an AI-enabled machine, or a system that makes recommendations without announcing that AI was involved.

Businesses that ask the right questions now will be better positioned to capture the benefits, protect what matters, and respond thoughtfully as the technology continues to change.