As AI and machine learning (ML) move from theoretical concepts to tangible tools within organizations, HR professionals are uniquely positioned to shape how these technologies are introduced, governed, and used.

In this post, we’ll explore a practical, people-centered approach to building an AI roadmap for HR - one that is strategic, ethical, and aligned with the pace and needs of your organization.

To set the tone, consider this quote from Ginni Rometty, Former CEO of IBM:

"Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we'll augment our intelligence."

That spirit of augmentation, not opposition, frames everything we’ll discuss. AI should enhance our capabilities, not undermine them. The goal isn’t to hand the wheel to machines, but to become better drivers with AI in the passenger seat.

Step 1: Understand your organization’s readiness

Before you launch into AI strategy, you need a clear-eyed view of where your organization stands. This isn’t just about IT infrastructure, it’s about digital mindset, leadership vision, employee appetite for change, and operational maturity.

Start by asking: Is AI a strategic demand for your company? If so, why? If not, why not? Are your leaders enthusiastic or hesitant? Is your infrastructure ready, or are you patching together systems?

You’ll also want to assess how your organization handles transformation. Consider your company’s personality. Are you a digital master with robust technology, strong governance, and integrated leadership? Or perhaps more conservative, holding back while you wait for clarity? Maybe you're in the beginner category, which means you're unfamiliar with AI’s potential and are still developing your digital literacy. Or perhaps you operate like a fashionista, moving quickly and adopting new tools without deep infrastructure.

None of these is inherently wrong. The key is to know where you are, so you can plan where to go.

Step 2: Evaluate leadership capacity and culture

Digital readiness is only part of the picture. Leadership capacity is just as critical.

Ask yourself: Do your leaders have a transformative vision for how technology will shape the future? Is there clear ownership and collaboration between IT, business leaders, and HR? Are roles and responsibilities well defined, or is it unclear who’s driving what?

The truth is, many organizations operate with a “fence-sitter” mindset. In other words, they're interested in AI but aren't sure how to act. That’s where HR comes in. You can help assess readiness across the organization, not just in infrastructure, but also in culture: Do employees feel excited about AI, or anxious? Are your leaders leading or waiting to follow?

One helpful insight from my studies at MIT is that digital transformation isn't just about platforms. It’s about people talking to the right people at the right time, having shared goals, and making room at the table for HR to be a key voice in governance and vision.

How HR can support real leadership in uncertain times
Uncertainty isn’t something we’re temporarily going through. It’s the environment we live in now. Whether you’re working in healthcare, education, service, tech (or any other field), we’re all feeling the same pressure. Things like economic volatility, regulatory changes, shifting markets, and leadership shakeups are more
People AllianceSandra Pham

Step 3: Run thoughtful, strategic pilots

If your organization is early in its AI journey, pilots are your best friend. They let you experiment without overcommitting, learn quickly, and demonstrate real value.

But not all pilots are created equal. Be strategic in what you test and who you involve. Ask:

  • What value can be gained? Look at time savings, data synthesis, better employee experiences, or bias mitigation.
  • Where can AI reduce cognitive load without diminishing quality? Automating repetitive tasks is a smart start, but always with human oversight.
  • Which leaders and teams are best suited for early involvement? Ideally, choose early adopters or functions with dynamic roles, larger teams, or newer structures. These tend to be more receptive to testing and change.

Importantly, when selecting pilot participants, you want alignment, not just from HR but across leadership. Make sure expectations are clear. Leaders should understand their responsibilities during the pilot: offering oversight, validating outputs, and contributing feedback. AI doesn’t absolve leaders of accountability, it requires new kinds of partnership.

And don’t forget your employees. Gauge their perceptions early. Are they intrigued or worried? Do they see AI as a threat to jobs or as a tool for growth? Their responses will influence adoption far more than any slide deck.

Step 4: Build your roadmap with five core pillars

Once you've learned from pilots, it’s time to build out your broader AI roadmap. Here are the five foundational pillars to guide that process:

1. Strategy

Define your organization’s target state with AI. What problems are you trying to solve? What outcomes are most valuable? Think long-term, not just what you need now, but what will be critical two years from now.

2. Governance

Governance isn't about slowing things down. It's about enabling innovation responsibly. Identify who’s involved in decision-making, what policies are needed, and how risk will be managed. It’s about creating clarity so AI doesn’t get implemented in silos or without oversight.

3. Technology

Evaluate your current tech stack. Can it support meaningful AI interventions that are fast, fair, and efficient? Do you need external tools, or can you scale with what you have?

4. Data

Good AI requires good data. Ask yourself: Why am I collecting this? Who benefits? Is it valid, ethical, and complete? Avoid the “garbage in, garbage out” trap. Without high-quality data, even the best algorithms will produce poor results or worse, biased ones.

5. Culture & skills

Do you have the right skills and mindset in your organization? Is there accountability and openness to experimentation? This is where HR plays a major role, not just in skills training, but in helping employees see AI as a partner, not a threat.

Designing environments for growth: The future of employee experience
In this article, I take you behind the scenes of how we’re designing growth-centric environments at ThredUp and why now, more than ever, it’s the most important investment any company can make.
People AllianceNatalie Breece

Step 5: Don’t skip ethics and risk management

Ethics must be a central part of your AI roadmap rather than just an afterthought. The risks are real: biased algorithms, privacy breaches, unfair outcomes. But so are the opportunities if you approach AI thoughtfully.

Set up an internal AI governance council with representation from HR, IT, legal, cybersecurity, finance, and your AI/ML leads. This council should:

  • Oversee data use and privacy.
  • Develop policies around explainability, transparency, and accountability.
  • Ensure alignment with evolving regulations and compliance standards.
  • Monitor for unintended outcomes, including bias or discrimination.

Ethics doesn’t mean slowing progress, it means building trust.

Remember: Just because you can, doesn’t mean you should. Thoughtful AI use means considering the moral implications, not just the technical feasibility.

Step 6: Define what success looks like

As you scale AI efforts, you need to measure their impact. This means going beyond anecdotal wins and capturing meaningful, organization-level data.

Here are some useful categories to track:

  • Performance metrics – Are processes faster? Is the employee experience smoother? Are learning or recruitment programs more effective?
  • Predictive analytics – Are you identifying trends or issues earlier (e.g., turnover, engagement drop-offs)?
  • Business impact – Is AI helping reduce costs or increase productivity? Is there a measurable improvement in team efficiency or service delivery?

Most importantly, keep refining your approach. Pilots are great, but iteration is essential. Adjust based on what’s working, and don’t be afraid to change direction if needed.

A roadmap for people, not just tech

AI isn't a plug-and-play solution, it’s a shift in how work gets done. And that shift must be guided by the people who understand work best: HR.

As HR leaders, we have a unique opportunity to shape the future of AI adoption in our organizations. We can ask the right questions. We can lead pilots with purpose. We can champion ethics, equity, and transparency. And we can help our teams see AI not as something to fear, but as a tool that frees us to do more meaningful work.

So, wherever you are on your AI journey, remember: you’re not behind. You’re at the beginning of something. Let’s make sure that something is done with intention, integrity, and humanity.