Table of Contents

• What’s holding HR teams back from adopting AI
• Where to start: building confidence and cutting through noise
• Why defining problems matters more than picking tools
• Practical guardrails for safe AI use in HR
• Examples of AI in employee relations and investigations
• Strategic vs tactical AI adoption: where HR should focus next

Resources

Here are some of the resources I owe the audience!

• ‍People Powered By AI Book
• 10 books HR pros will want to read
• Claire’s LinkedIn‍
• Theresa’s Linkedin

What’s holding HR teams back from adopting AI

The hype around AI is everywhere. But when it comes to actual adoption inside HR teams, many leaders are stuck on the sidelines. Theresa Fesinstine, HR leader and founder of People Powered AI, explained why during our recent webinar.

“A lot of teams are hesitant because they don’t know where to start. There’s this sense that if you don’t already understand AI, you’re behind. And that creates paralysis.”
— Theresa Fesinstine

That paralysis shows up in different ways. Some teams wait for perfect policies before testing tools. Others dabble with AI personally but never formalize usage at work. And some avoid the topic entirely, worried about the risk of “doing it wrong.”

The problem is that while HR waits, employees are already experimenting with AI on their own. If HR doesn’t step in with structure, shadow usage becomes the default.

Why hesitation is risky for HR

• Employees form habits without guidance, which makes later governance harder
• Leaders miss easy wins that could save time immediately
• HR loses credibility if they’re seen as lagging behind other departments

The hesitation is understandable, but it can’t be permanent. As Theresa emphasized, HR doesn’t need to be perfect — they just need to get started.

Where to start: building confidence and cutting through noise

AI can feel overwhelming because the possibilities seem endless. Job postings, policy documents, ER cases, performance reviews — every HR task looks like a potential use case. But trying to “do it all” guarantees doing nothing.

Theresa advised starting with confidence-building, not transformation.

“You don’t have to overhaul your entire workflow. Start with one place where AI can take some weight off your plate. Build comfort, then expand from there.”
— Theresa Fesinstine

The first step is cutting through the noise. HR teams don’t need a thousand AI tools. They need a clear understanding of what problems they want to solve.

How to build confidence in early AI use

• Choose a small, repetitive task where the stakes are low
• Involve multiple team members so learning is shared
• Document results — what worked, what didn’t, and what time was saved
• Share the story internally to normalize experimentation

These small wins aren’t just operational. They shift culture. Once employees see AI as something approachable and useful, the fear starts to fade.

Confidence compounds. The more experiments HR teams run, the faster they’ll see opportunities to scale adoption responsibly.

Why defining problems matters more than picking tools

One of the strongest themes from the webinar was that tool selection is secondary. What matters most is defining problems with clarity.

“The more successful pilots will be the ones that actually have a clear problem defined first. What’s wasting a lot of your time at work? Where are you getting bogged down? Define the problem, then explore automation.”
— Theresa Fesinstine

Too often, HR teams get swept up in vendor promises. They buy an “AI assistant” without first asking what outcome they need. This leads to underused tools, wasted budgets, and frustrated employees.

What problem-first adoption looks like

• Start by listing bottlenecks in your HR processes
• Rank them by time wasted and frustration caused
• Identify where AI could reasonably reduce the burden
• Only then look for tools or workflows to match the problem

For example, if recruiters spend hours rewriting candidate outreach emails, AI can draft templates in minutes. If employee surveys pile up with open-text responses, AI can summarize themes. But the key is to start with the pain point, not the shiny tool.

This mindset keeps adoption grounded in real business value rather than novelty.

Practical guardrails for safe AI use in HR

Of course, experimentation comes with risk. Data sensitivity, privacy concerns, and bias are all real issues in HR workflows. The solution isn’t to avoid AI, but to establish guardrails.

“People have to be comfortable that if something goes wrong, they’re not going to get fired. When there’s that safe feeling, they will be more likely to take risks, try new things, and grow.”
— Theresa Fesinstine

Guardrails don’t just protect the company. They create psychological safety for employees trying out AI.

Examples of guardrails HR can set early

• Never upload personally identifiable information into external AI tools
• Keep a human in the loop for sensitive tasks like hiring and ER cases
• Establish a clear “safe to try” zone for low-stakes tasks
• Provide a way for employees to raise concerns anonymously

Each of these practices reassures employees that they’re not on their own. Guardrails turn experimentation into learning instead of liability.

The wrap-up here is simple: AI adoption doesn’t mean abandoning responsibility. It means combining innovation with caution, so progress and trust grow together.

Examples of AI in employee relations and investigations

Employee relations is one of the most sensitive areas in HR, which makes it both a promising and a cautious space for AI adoption. Theresa explained that some aspects of ER are ripe for automation, while others should always stay human.

“AI can help with the mechanics, but it cannot replace the human responsibility of caring for people.”
— Theresa Fesinstine

Where AI can add value in Employee Relations

• Automatically tagging and linking cases to spot patterns faster
• Summarizing case notes into digestible insights for HR leaders
• Flagging trends that may require culture interventions

These uses save HR teams hours of manual review while still keeping humans in control of outcomes.

Where humans must stay involved

• Conducting sensitive interviews
• Making disciplinary decisions
• Communicating outcomes to employees

In ER, AI is a support tool, not a decision-maker. Its role is to make data more usable so HR can focus on the human side of resolution.

Strategic vs tactical AI adoption: where HR should focus next

The final theme of the webinar was moving beyond tactical wins toward long-term strategy. Automating tasks is a start, but AI’s true potential lies in reshaping how HR operates.

Theresa argued that HR should position itself as the driver of AI transformation, not the passenger.

“HR has a chance to lead this change by showing how AI can be used responsibly and in service of people, not just efficiency.”
— Theresa Fesinstine

How HR can move from tactical to strategic

• Use early pilots to build momentum and credibility
• Partner with IT and legal, but lead with the employee perspective
• Tie AI adoption directly to business outcomes like engagement, retention, or productivity
• Share learnings openly so employees see HR as a trusted guide

The key is for HR to shift from reactive adoption to proactive strategy. Instead of waiting for other functions to dictate AI’s role, HR can model what responsible, human-centered adoption looks like.

Final word: AI adoption starts with small, human-centered steps

AI is already here. The question isn’t whether HR will adopt it, but how.

Theresa Fesinstine’s message to HR leaders is clear: start small, focus on real problems, create guardrails, and lead with humanity. Employees don’t need AI to be perfect. They need to know HR has their back as they navigate change.

“The benchmark isn’t whether HR implements AI flawlessly. It’s whether employees feel supported through the change.”
— Theresa Fesinstine

By taking this approach, HR doesn’t just adopt AI. They earn the trust needed to guide organizations into an AI-first future.

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