Artificial intelligence is quickly becoming a part of everyday work. For employers, that creates both an opportunity and a challenge.
AI can help employees work more efficiently and reduce time spent on routine tasks. However, organizations also need to consider the risks associated with AI, particularly when it comes to sensitive information, inaccurate outputs, and using AI to support important business decisions.
Here are some practical uses, risks, and best practices businesses should consider when adopting AI in the workplace.
AI is particularly useful as an assistant.
It can help employees organize information, accelerate repetitive tasks, develop ideas, and get started on work that ultimately remains the employee's responsibility.
The right use cases will vary by organization and role, but there are several practical ways employees can begin using AI at work.
AI-powered meeting tools can help employees record and transcribe meetings, summarize discussions, and identify action items.
For example, an AI meeting assistant may be able to identify what was discussed, decisions that were made, and tasks assigned to different participants. This can provide employees with a useful backup to their own notes and reduce the chances of an important follow-up falling through the cracks.
Employees should not necessarily stop taking notes or paying attention because AI is working in the background. Instead, the technology can provide another resource for reviewing what happened and identifying next steps.
AI can also act as a useful second set of eyes.
Employees who regularly produce emails, articles, guides, presentations, reports, and other written materials can use AI to identify grammar issues, improve readability, or suggest revisions.
The important distinction is between assistance and replacement.
An employee can give AI a draft and ask for suggestions, but the employee should still decide which changes make sense. AI-generated writing can sound polished while still containing inaccurate information, awkward wording, or language that does not match the organization's voice.
Sometimes the hardest part of a project is getting started.
Employees can use AI to brainstorm ideas, develop an initial outline, organize existing thoughts, or explore different approaches to a topic.
For example, instead of asking AI to write an entire article, an employee could explain the topic, audience, and points they want to cover and ask for ideas on how to organize them.
The AI provides a starting point. The employee provides the expertise, judgment, and final product.
There are also opportunities to use AI for tasks that involve sorting through large amounts of information.
For example, AI may help identify information that matches predetermined criteria, summarize lengthy documents, organize feedback into categories, or highlight recurring themes.
However, organizations should be especially careful when these activities involve employees, applicants, customers, financial information, or other sensitive data. AI can help organize information, but people should remain responsible for consequential decisions.
The general principle is simple: Use AI to assist with the work, not to replace human judgment.
The benefits of AI can make it tempting to use these tools for almost everything.
That is exactly why organizations need to understand their limitations.
AI-generated responses are based on patterns in the information available to the model. An answer that sounds confident or professional is not necessarily accurate, unbiased, or appropriate for a particular business situation.
Several risks deserve particular attention.
AI can make mistakes.
Generative AI tools can produce inaccurate information or "hallucinations," where the model presents fabricated or unsupported information as though it were factual.
This becomes especially risky when AI-generated information is used for reporting, calculations, research, compliance, or business decisions.
AI can help an employee build or organize a report, for example, but relying on unverified AI-generated numbers to make an important business decision introduces unnecessary risk.
Employees should verify facts, calculations, sources, and other important information before using AI-generated outputs.
AI is not inherently objective.
Its responses can reflect biases contained in the information it has been trained on or provided. Users can also unintentionally introduce bias through the way they phrase a prompt.
That is particularly important when AI is involved in processes that affect people.
Organizations should be cautious about using AI to independently make decisions involving employees, applicants, compensation, customers, or other consequential matters. Human review remains essential.
One of the most significant risks of using AI at work is providing a public AI tool with information that should not have been shared.
Employees should avoid entering confidential, regulated, proprietary, or personally identifiable information into public AI tools.
Depending on the organization, that could include:
Employees do not necessarily need to memorize every possible example. Instead, they should learn to recognize the pattern.
If information identifies an individual, reveals confidential business operations, provides access to a system, or has financial or proprietary value, it should be treated with caution.
A useful question to ask before entering information into an AI tool is:
“Would I be comfortable sending this information to an outside party or posting it publicly?”
If the answer is no, employees should stop and determine whether the information is appropriate for that AI tool.
AI can produce polished work very quickly. That convenience can make it easy to rely on it too heavily.
Employees still bring context, experience, creativity, expertise, and accountability to their work.
AI should not become the explanation for an inaccurate communication or a poor business decision. Someone within the organization ultimately needs to own the work and be accountable for how it is used.
This is particularly important when the work could affect an organization's professional reputation. AI can help develop ideas and refine work, but employees should be cautious about outsourcing the expertise that customers, coworkers, and business partners rely on them to provide.
Responsible AI adoption does not necessarily require an enormous compliance program.
Organizations can start by creating clear expectations around which tools employees can use, what information they can provide, how AI-generated work should be reviewed, and who is ultimately accountable for it.
One practical approach is to teach employees four habits when working with AI:
Looking to dive deeper into strategies on adopting AI at work? Check out this article on how to use AI at work responsibly.
AI is already changing the way people work, and organizations do not need to choose between completely embracing the technology and blocking it altogether.
Instead, businesses can focus on finding practical ways AI can improve productivity while establishing guardrails that protect employees, customers, business information, and the organization itself.
AI can reduce administrative work, help organize information, accelerate first drafts, and support everyday tasks. Human judgment, however, remains essential—particularly when decisions involve employees, customers, payroll, finances, compliance, or other high-risk matters.
Want to take a deeper look at what responsible AI adoption can look like in your organization?
Watch our AI at Work: Practical Uses, Risks, and Responsible Adoption webinar for a discussion of practical AI use cases, human oversight, protecting sensitive information, and the questions business leaders should consider when developing AI policies and governance.