It’s clear that artificial intelligence has already changed the way work gets done. Employees are using AI to write, research, analyze information, solve problems, and complete everyday tasks more efficiently. In many organizations, that adoption happened before leadership had an opportunity to establish clear expectations around how the technology should be used.
According to Microsoft research, 75% of knowledge workers already use AI at work, while 78% of AI users are bringing their own AI tools into the workplace. Nearly half of those users started within the previous six months.
The question has shifted from whether employees will choose to utilize AI to whether organizations are prepared to manage how it is being used. AI affects employees, workplace behavior, training, decision-making, compliance, privacy, and accountability. Those are areas where HR has an important role to play.
The organizations that successfully integrate AI will not simply adopt the technology. They will establish the policies, training, oversight, and accountability necessary to use it responsibly. If AI is changing how work gets done, HR cannot afford to be a bystander.
The Benefits of AI Are Real, But So Are the Risks
When used appropriately, AI can help organizations increase productivity, reduce administrative work, access information faster, and support employees with everyday tasks. It can serve as an assistant that helps employees spend less time on repetitive work and more time on responsibilities that require human judgment.
But the same technology that creates opportunities can also create risk. One example is Samsung. In 2023, engineers in the company’s semiconductor division used ChatGPT to improve productivity. Within weeks, employees accidentally entered confidential information into the chatbot, including source code and internal meeting notes. Samsung subsequently restricted generative AI use while it worked to address the issue.
The employees were trying to work more efficiently. Without clear guardrails, however, those well-intentioned efforts created organizational risk. The same concerns can appear in HR.
What happens when a manager enters confidential employee information into an AI tool to help write a performance review? What happens when AI is used to assist with recruiting or compensation decisions? What happens when an employee relies on an AI-generated answer without verifying whether it is accurate?
There are five areas where AI can go sideways: bias, accuracy, privacy, compliance, and accountability. AI can reproduce patterns in its training data, confidently generate incorrect information, expose sensitive information, create employment-law concerns, and make it tempting for people to defer responsibility to the technology.
AI Governance Requires HR, IT, and Leadership
AI governance is often treated as a technology initiative, but effective governance requires both technology and workforce expertise.
IT manages technology risk. That includes security and access, permissions and data, vendor reviews, system administration, monitoring, and incident detection. HR manages workforce risk. That includes policies and expectations, leader guidance, employee training, employee relations, employment compliance, and ethical judgment. Neither function can effectively govern AI alone.
For example, IT may be able to identify which AI tools employees are accessing. HR can help determine whether that usage indicates a training gap, a policy issue, or a concern involving employee performance or conduct. Leadership also has an important role in setting expectations and determining how AI fits into the organization’s broader strategy. AI governance should therefore be collaborative rather than departmental.
The goal is to create an environment where employees can use AI to improve their work while understanding the boundaries that protect the organization and its people.
Five Moves to Build AI Accountability
Organizations do not need to have a perfect AI governance program in place immediately, they just need to start. There are five practical moves organizations can take when establishing AI governance: assess, establish policy, train, create a committee, and begin oversight.
1. Assess Current AI Usage
You cannot govern what you do not know. Start by determining who is using AI, which tools they are using, what internal information they are entering, and how they are using those tools. Partner with IT to understand both approved tools and potential “shadow AI.” Employee surveys and leadership interviews can help provide a more complete picture.
The goal is to understand not just what tools employees are using, but why they are using them and what risks or opportunities that creates.
2. Establish an Acceptable Use Policy
Once you understand current usage, establish clear expectations. An AI acceptable use policy should address the purpose and scope of AI use, approved and prohibited tools, data and privacy rules, acceptable use cases, human oversight, incident reporting, and a regular review schedule.
The policy should make clear that AI is intended to support human judgment, not replace it. Employees remain responsible for reviewing and verifying AI-generated information. A simple, practical policy gives employees something they can reference and gives IT and leadership a consistent framework for managing AI use.
3. Train Employees
A policy is only useful if employees understand how to follow it. Training should cover what good and bad AI use looks like, how to write effective prompts, what information should never be entered into an AI tool, and how to recognize and validate inaccurate outputs. Training should also be ongoing. Organizations should track completion, incorporate AI education into onboarding, and update training as the technology evolves.
4. Create an AI Committee
AI governance should bring different perspectives together. An AI committee can include HR, IT, leadership, and employees who understand how AI is being used throughout the organization. The group can review emerging use cases, discuss risks and opportunities, address employee questions, and recommend changes to policies and training.
The committee does not have to be made up entirely of executives. Employees who are actively interested in AI may have valuable insight into how the technology can support the organization.
5. Begin Ongoing Oversight
AI governance does not end when a policy is written or training is completed. Organizations should continue monitoring AI usage, reviewing risks, managing incidents, evaluating new use cases, and ensuring that high-impact decisions receive appropriate human review.
IT can provide information such as AI tool usage reports, shadow AI reports, and adoption metrics. HR and leadership can help determine what those trends mean from a workforce and organizational perspective. The technology will continue to evolve, so the organization’s approach must evolve with it.
Moving From Adoption to Accountability
Because AI adoption is already happening, organizations need to decide how intentionally they will manage it. HR has an important role because AI is changing more than technology. It is changing how people work, what skills employees need, how decisions are made, and how organizations manage risk.
But HR should not do this alone. IT brings technical expertise. HR brings the workforce perspective. Leadership provides direction and accountability. Together, these groups can help organizations capture the benefits of AI while creating clear expectations around responsible use.
The first step does not have to be complicated: Assess what is already happening. Establish clear expectations. Train employees. Create shared oversight. Continue evaluating and adapting. The goal is to create a framework that allows organizations to innovate while protecting their people, information, and business.
If your organization is evaluating AI adoption, developing an acceptable use policy, training employees, or determining how AI will affect recruiting and workforce management, Hanna Resource Group can help. Our team can partner with your organization to assess workforce risks, establish practical governance processes, and create strategies that support responsible innovation.
