AI is beginning to reshape the way organizations operate, and HR is at the center of the transformation.
From Bolt replacing its HR department with AI systems to Moderna merging HR and IT teams, companies are reengineering people functions with technology. McKinsey reports that 72% of organizations now use AI in at least one function; up from 50% two years ago.
However, the pace of AI tool implementation is outstripping the development of necessary skills among HR professionals. In fact, only 35% of HR professionals feel confident using AI tools.
This gap isn’t just about learning new platforms. It’s a deeper capability challenge: How HR can lead the use of AI in ways that are strategic, ethical, and people-centric
This comes down to developing core HR expertise that enables HR teams to build AI fluency— the working knowledge, judgment, and confidence to engage with AI tools. These aren’t technical skills, but they are essential for HR to lead with AI.
Here are the three critical areas of expertise your team needs.
1. Develop deep HR expertise first
The foundation of AI fluency isn’t technical.
That makes deep HR expertise the first, and most essential, building block for working effectively with AI. It begins with judgment, experience, and a strong understanding of people and organizational dynamics.
When this works
- AI insights are interpreted with context, not just data
- Tools are selected based on real people challenges
- HR sets a people-centered agenda in tech conversations.
When this breaks down
- AI outputs are taken at face value
- Tools are introduced without a clear HR use case
- Tech teams build systems with little HR input.
AI can process information and surface patterns, but it can’t decide what matters. It can’t distinguish between a temporary performance dip and a systemic engagement issue. It can’t weigh a candidate’s potential against long-term culture fit. These are judgment calls grounded in experience, context, and the ability to interpret nuance. These are the skills that only a well-grounded HR professional brings to the table.
To guide AI responsibly, HR professionals need to:
- Understand the organizational problems they’re solving.
- Evaluate tools through a people-first lens.
- Communicate people’s priorities clearly in cross-functional teams.
Strong HR expertise also provides the filter through which AI recommendations are evaluated. When an AI model flags employees as “flight risks,” an HR leader with deep knowledge will ask: What patterns is the system seeing? What assumptions is it making? What other factors should be considered? Instead of treating AI as a black box, they treat it as input, valuable, but incomplete without human insight.
This expertise also plays a crucial role in collaboration. When working with IT, data teams, or vendors, HR must bring a clear point of view: here’s the problem we’re solving, here’s how success looks, and here’s what matters to our people. Without that clarity, technical teams may build solutions that are technically elegant but operationally ineffective.
The bottom line
AI can only enhance what HR already does well. HR teams that are confident in their core craft are best positioned to get value from AI. Fluency begins with deep HR expertise and a clear sense of purpose, not with tools.
2. Develop a practical understanding of AI
HR doesn’t need to code, but it does need to comprehend.
AI fluency requires more than surface-level tool use. HR professionals must understand the mechanics behind AI: how it’s trained, what it does well, and where it can fail. Knowing the fundamentals allows HR teams to ask smarter questions, make better decisions, and stay in control of how technology shapes their function.
When this works
- HR asks smart questions about how tools function
- AI outputs are reviewed before use
- HR and IT speak a shared language.
When this breaks down
- Tools are trusted without scrutiny
- Automation makes unchecked decisions
- HR stays silent in technical discussions.
At its core, AI is a system trained on patterns in data. It identifies trends, predicts outcomes, and generates outputs based on what it has seen before. But this process is not neutral. The data used to train AI models reflects real-world biases, gaps, and assumptions, and without human oversight, those patterns can be amplified in ways that harm people and organizations.
Understanding these dynamics enables HR to engage critically with AI. For example, a basic grasp of concepts like machine learning, natural language processing, or algorithmic bias empowers professionals to:
- Evaluate vendor claims with skepticism and clarity
- Recognize the limits of what AI can and cannot do
- Identify when human intervention is needed to avoid errors or unfair outcomes.
This literacy is also key to working cross-functionally. IT and data teams often use technical language that can alienate non-technical stakeholders. But when HR speaks the language of AI, enough to engage, challenge, and contribute, they become credible partners in shaping solutions.
Importantly, this isn’t about becoming an expert in everything. It’s about understanding enough to lead. When your HR team can explain, in plain language, how a tool works and what risks it carries, they build trust across the organization.
Example
A generative AI tool recommends learning paths. A fluent HR professional asks:
- What data is it using?
- Is it adapting to different roles or goals?
- How do we prevent irrelevant or biased suggestions?
These aren’t technical questions, they’re leadership questions. And fluency gives HR the confidence to ask them.
The bottom line
Fluency depends on understanding how AI systems function sufficiently to guide, challenge, and lead responsibly.
3. Develop responsible and effective AI tool use
Fluency shows up in how tools are applied every day.
Once HR professionals have a strong foundation in HR practice and a working understanding of how AI functions, the next step is applying tools with intention. This is where AI fluency shows up in everyday work. Not in theory, but in the decisions HR makes about how and when to use AI, and what boundaries to set around it.
When this works
- AI tools are aligned to clear business outcomes
- HR builds checkpoints for bias and error
- Teams are transparent about how AI influences decisions.
When this breaks down
- Tools are added with no clear goal
- Outputs are used without verification
- Employees are left in the dark about how AI affects them.
Using AI effectively means aligning tools with real problems. It’s not about adding AI for the sake of innovation. It’s about asking: Does this tool solve a priority issue? Will it improve a key process? Can we measure its impact? The most fluent HR teams treat technology as a lever for better outcomes, not just quicker ones.
Responsibility, however, is where true fluency is tested. Every AI-enabled tool comes with risks, no matter how simple or powerful. Automation in recruitment might save time, but without oversight, it can amplify bias. AI-generated feedback may increase consistency, but it can also strip nuance from performance conversations. Generative tools in learning can create fast content, but may also introduce errors or misinformation.
Fluency means using these tools deliberately, with safeguards in place:
- Establishing clear criteria for how tools are evaluated and selected
- Building in human review at key decision points
- Being transparent with employees about how AI is used and why
- Monitoring outcomes to ensure fairness, accuracy, and alignment with values.
It also means embedding responsible use into team norms and workflows. For example:
- In recruitment: Use AI to scan for baseline qualifications, but always involve a human to assess potential and fit.
- In learning: Let AI recommend courses, but ensure they are contextually relevant and updated.
- In analytics: Let AI flag trends, but interpret them through the lens of culture, history, and people dynamics.
When HR professionals operate this way, they don’t just “use” AI. They set the standard for ethical, people-first deployment by understanding the potential and the pitfalls.
The bottom line
AI fluency isn’t just knowing what a tool does; it’s knowing when, why, and how to use it in a way that reinforces trust and drives impact.
The risk of skills lag in HR
When AI is introduced without the right skills in place, dependency instead of progress is created. Tools may streamline tasks, but they can’t replace human judgment, cultural context, or ethical decision-making. Without the knowledge to question, guide, or refine AI systems, HR risks becoming reactive and sidelined.
This skills lag impacts HR’s effectiveness and threatens its influence. Without the ability to speak the language of AI or participate in cross-functional discussions, HR loses its voice in critical decisions that affect people and culture. To stay relevant, HR must accelerate skill development and reclaim its role as a proactive leader in AI-powered transformation.
How to build AI fluency as an HR capability
AI fluency isn’t just an individual skill; it’s a core HR capability. But for fluency to take root across the function, it must be supported by broader AI readiness. That means aligning upskilling efforts with the systems, structures, and strategies that enable effective, responsible use of AI at scale:
- Clear purpose and strategy: HR teams need to know not only how to use AI, but why. This starts with a clear plan that defines the business outcomes AI is meant to support, the problems it will help solve, and the use cases where it creates real value. When AI adoption is guided by strategy, fluency becomes focused and intentional.
- Strong governance: Policies, oversight, and ethical standards help ensure that AI is deployed safely and fairly across the employee life cycle. HR must be involved in shaping these guardrails, bringing a people-first perspective to issues like bias, transparency, and accountability.
- Data and technology infrastructure: It requires reliable data, integrated platforms, and scalable tools.
- People readiness: This includes shared awareness, buy-in, and a culture that supports experimentation. When HR professionals are engaged and curious, they help drive adoption and identify opportunities from the ground up. Advocacy isn’t just top-down; it grows from teams that see the value and know how to use AI responsibly.
- New skills: As AI evolves, so must the HR team’s capabilities. This goes beyond one-off training. It means continuous development, exposure to emerging tools, hands-on learning, and space for reflection. Peer learning, scenario-based workshops, and structured upskilling pathways all help teams build and sustain real fluency.
And none of this happens without leadership. When HR leaders ask informed questions, model responsible use, and prioritize learning, they set the tone for the entire function.
To sum up
The integration of AI into HR is now a reality. Tools are already reshaping how we hire, develop, support, and retain people. Still, the real opportunity lies not in the tools themselves but in how HR professionals use them.
When adoption outpaces understanding, organizations face real risks: poor decisions, ethical missteps, and lost trust. But when HR builds AI fluency, it becomes a strategic force that shapes the future of work. It’s about making better decisions, enabling more human experiences, and ensuring that progress doesn’t come at the expense of principles.
