We’re Using AI, But Are We Using It the Right Way?

Lately, HR leaders tell me they feel caught in a contradiction. On one hand, AI is everywhere. Employees are already using it. Candidates list it on their résumés. Executives feel pressure to adopt it quickly to drive efficiency, productivity, and results.

On the other hand, many leaders are quietly asking the same question:

“Are we moving too fast—and are we putting ourselves at risk?”

That tension is real. And it’s exactly where most small and mid‑sized businesses are right now.

AI in HR Isn’t Coming; It’s Already Here

According to our State of the Workplace research, the overwhelming majority of employers and employees are already using AI at work. For HR tasks in particular, AI use is frequent and growing fast.

This isn’t a fringe experiment anymore. AI is becoming a standard part of how HR teams support benefits, performance reviews, employee engagement, and training.

I’ve spoken with countless clients who are excited by the possibilities, especially tools that offer real‑time insights into engagement and culture. As someone who came up in the era of annual engagement surveys and long feedback cycles, the idea of being able to take the pulse of your workforce in near‑real time is fascinating.

But excitement alone isn’t a strategy.

Don’t Adopt AI Just Because Everyone Else Is

One of my strongest beliefs about AI in HR is this: adoption should start with pain points, not pressure. Too often, organizations rush into AI because competitors are doing it or because leadership wants to “check the box.” That’s when problems begin.

AI doesn’t need to replace entire functions to be valuable. In many cases, it’s far more effective when it’s applied to small, specific tasks that alleviate friction, then tested, evaluated, and refined.

Pilot programs. Lunch‑and‑learn demonstrations. Limited use cases. These approaches make it easier for HR teams and employees to build confidence and trust with the technology before scaling.

The People Closest to the Work Should Help Shape AI Adoption

Another mistake I see is making AI decisions exclusively at the executive level. Frontline managers and individual contributors often have the clearest view of where processes break down, where accuracy suffers, or where engagement drops. They also tend to have firsthand experience with AI tools that could help.

Organizations that invite these voices into the conversation tend to see better results, not just better tool selection, but stronger buy‑in. When employees feel they have a say in how AI is introduced, it feels less like something being done to them and more like something being built with them.

AI Experience on a Résumé Doesn’t Always Mean What You Think

Recruiting is another area where I encourage leaders to slow down and ask better questions. Many job postings now require “AI experience,” and candidates are responding by highlighting it on their résumés and LinkedIn profiles. But AI experience varies widely.

Using AI to plan meals or vacations is very different from using it to improve workflows, analyze data, or support decision‑making in a business context. Employers need to probe deeper; ask how candidates have actually used AI, what tools they’ve worked with, and what problems they’ve solved.

Otherwise, “AI experience” becomes a buzzword instead of a meaningful qualification.

Compliance and Risk Can’t Be an Afterthought

As optimistic as I am about AI’s potential, I’m equally clear about the risks.

State and local governments are already regulating AI, particularly to prevent bias in hiring and employment decisions, and more regulations are coming. Litigation tied to AI‑related discrimination is already making headlines.

Even if you’re using a third‑party vendor, responsibility doesn’t shift. Employers are still accountable for how AI is implemented, how decisions are made, and how employee and customer data is handled.

That’s why auditing tools for bias, understanding data privacy practices, and staying current on regulatory requirements—especially in multi‑state or global operations—is no longer optional.

Governance, Not Guesswork

The organizations navigating AI most effectively are the ones treating it as a cross‑functional issue, not just an IT or HR project.

They establish governance programs or committees that include input from HR, IT, security, legal, operations, and finance. They define acceptable use policies. They audit vendors. They set clear frameworks for decision‑making, compliance, and accountability.

This isn’t about slowing innovation. It’s about protecting trust internally and externally.

The Balance That Matters Most

AI is already reshaping how employees get answers, how managers assess performance, and how organizations operate.

The challenge isn’t whether to use AI. It’s how to use it without losing the human judgment, fairness, and values that define your culture.

For SMB leaders, success with AI in HR comes down to balance:

• Efficiency with empathy
• Speed with oversight
• Innovation with responsibility

Used thoughtfully, AI can elevate HR’s impact. Used carelessly, it can undermine trust faster than almost anything else.

AI isn’t replacing HR. It’s raising the bar for how intentional HR leadership needs to be.

FAQs

Q: How are small and midsize businesses currently using AI in HR? 

A: AI is already widely used across HR functions including benefits administration, performance reviews, employee engagement, and training. According to TriNet's State of the Workplace research, the majority of both employers and employees are already using AI at work, and adoption is growing rapidly.

Q: What are the biggest risks of adopting AI in HR too quickly? 

A: Moving too fast without a clear strategy can introduce bias in hiring and employment decisions, create data privacy vulnerabilities, and expose organizations to regulatory liability. Even when using third-party AI vendors, employers remain accountable for how AI tools are implemented and how decisions are made.

Q: How should SMBs approach AI adoption in HR without taking on unnecessary risk? 

A: Start with specific pain points rather than broad adoption pressure. Pilot programs, limited use cases, and lunch-and-learn demonstrations allow HR teams to build confidence with the technology before scaling. Employees and frontline managers should be included in the process, not just executives.

Q: What AI regulations should HR leaders be aware of? 

A: State and local governments are increasingly regulating AI use in hiring and employment decisions, particularly to prevent algorithmic bias. Litigation tied to AI-related discrimination is already emerging. SMBs — especially those operating across multiple states — should audit AI tools for bias, understand vendor data privacy practices, and monitor evolving regulatory requirements.

Q: How can employers evaluate whether a job candidate truly has meaningful AI experience? 

A: Go beyond the résumé bullet point. Ask candidates specifically how they have used AI, which tools they have worked with, and what business problems they have solved. Using AI for personal tasks is very different from applying it to workflow improvement, data analysis, or business decision-making.

Q: What does good AI governance look like for a small or midsize business? 

A: Effective AI governance treats AI as a cross-functional issue rather than just an IT or HR project. It includes input from HR, legal, IT, security, finance, and operations; establishes acceptable use policies; audits vendors regularly; and creates clear frameworks for compliance and accountability.