Making AI make sense: A human-centred guide for HR

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Making AI make sense:

A human-centred guide for HR

Executive summary

The world of work is shifting—fast. And HR sits right at the heart of that change. With the growing potential of AI to enhance how we serve people, reduce administrative overload, and shape more meaningful employee experiences, the question isn't whether to engage with AI—but how to do it in a way that feels human, grounded, and purposeful.

This article draws on rich conversations from a recent HR and AI roundtable, where HR leaders came together to tackle a critical challenge articulated by Obibugo Maduako-Ezeanyika, Director of People at Ottu Consulting: how to get businesses to adopt a proactive, long-term planned approach when identifying HR processes that would benefit from human-AI collaboration, rather than relying on reactive problem-solving. The discussion featured insights from Grant Walsh (Police Scotland), Sarah Coffin (Klipboard), Aidan McKee (Stratx Global), Samantha Laurie (global financial services), Muriel Schulz (Adeo), and Jacinta Hennessey (HubbubHR).

Many HR leaders admitted feeling overwhelmed—by tech language, system limitations, or fear of losing the human touch. Yet all agreed: AI, when applied thoughtfully, can enhance HR's impact, not diminish it. Only 15% of HR professionals feel confident using AI tools (McKinsey & Company, 2024), while a majority of employees fear job loss more than job change (Gartner, 2024).

We explore the core barriers holding teams back and offer a roadmap to shift from reacting to leading. The answer isn't more complexity—it's clarity. It's about starting small, focusing on real people problems, and building on a flexible, human-first HRIS foundation that integrates easily with changing tools and needs.

This isn't about replacing HR. It's about giving HR room to breathe again—and refocusing on what matters most: people.

The problem: How to clarify HR's approach to AI adoption

Many HR teams are enthusiastic about the potential of AI—but struggle to move beyond reactive problem-solving to planned implementation. The hesitation is human, and deeply relatable.

Obibugo Maduako-Ezeanyika explains the core challenge: "It goes back historically to the role of HR and people functions within organisations. HR function largely is supportive, and therefore investing in HR innovation in terms of improving HR processes is often misunderstood."

This creates a vicious cycle. As Maduako-Ezeanyika notes, "In many organisations senior HR leaders/ the chief people officer do not have voting rights or board representation therefore their ability to influence decisions around large investment in workforce transformation through HR AI and innovation can be limited."

The barriers are both structural and psychological:

We don't know what's possible. Sarah Coffin observes: "There's that disconnect between what people perceive AI to be able to do when they see the perfect stuff in the media versus the reality of what AI actually can achieve."

We're worried about the impact. Grant Walsh highlights the tension: "How do you balance the tension between a long-term strategic approach versus quick wins through use cases that show the value that can be added through AI?"

We don't know how to talk about it. The language of AI often alienates the very people it aims to help. As Josh Bersin notes, "When AI is framed as an existential threat instead of a practical tool, HR loses the room" (Bersin, 2024).

We're not set up for it. With limited budgets and rigid systems, experimentation feels risky. Without adaptable HRIS platforms that can integrate with AI tools, organisations struggle to pilot and scale solutions effectively.

But here's the truth: HR is better positioned than most to lead this change—because it's not about tech. It's about people, and that's what we do best.

"It goes back historically to the role of HR and people within organisations. HR function largely is supportive, and therefore investing in HR innovation in terms of improving HR processes is often misunderstood."

Obibugo Maduako-Ezeanyika

Director of People at Ottu Consulting

Making AI work for HR means leading with empathy, not engineering.

The shift to human-centred HR-AI approach

"At the senior end, bring external expertise—not from a sales AI perspective, but someone who's lived through big change implementation."

Samantha Laurie

Chief People Officer

Making AI work for HR means leading with empathy, not engineering. The shift starts by anchoring AI approach in human purpose, as our roundtable participants discovered.

Aidan McKee emphasises the importance of clarity: "When it's been successful, it's when we've engaged with the organisation to help really drive that reason to believe. So why are we doing this and how does it link to what we're trying to achieve?"

The key principles that emerged from the discussion:

Start with what matters to your people. McKee asks the crucial questions: "What's in it for you or what's in it for me? Simplify what feels very complex right now and bring that simplified approach back to why are we doing this."

Build bridges across the business. This isn't just an HR project. As Samantha Laurie suggests: "At the senior end, bring external expertise—not from a sales AI perspective, but someone who's lived through big change implementation."

Design with people in mind. As Jeanne Meister observes, "The best AI systems are invisible—they reduce effort, increase insight, and fit smoothly into workflows" (Meister, 2025). Jacinta Hennessey notes: "Systems augmentation and automation, including AI, should be about reducing friction. If it does not reduce friction, it's not adding value."

None of this works without systems that can flex. That's why an adaptable, API-first HRIS is foundational—it ensures you can plug in tools, automate the right things, and grow sustainably as your needs develop.

These are not technology problems—they're trust, clarity, and collaboration challenges.

Barriers to change

When change feels too big, people shut down. The roundtable revealed common barriers HR teams face:

Fear of job loss. Maduako-Ezeanyika observed: "If it's sold as taking over the role of the human component in delivering service, then you will get resistance to change. But if it's sold as something that compliments what we currently do, then you get greater buy-in."

Confusing terminology. Sarah Coffin shared her company's approach: "What we benefit from having is a CIDO (Chief Information and Data Officer) who literally turned Copilot on and made it our default page. People get used to and start trusting AI once they realise it helped them write their email—it can't be that bad."

Silos and disconnects. HR, IT, and planning teams often run parallel, not together. The solution requires cross-functional collaboration and shared understanding.

Data gaps and system limitations. Even the best tools struggle if the underlying data isn't clean, connected, or trusted. Samantha Laurie noted: "You can't automate a broken process. Being aware that AI won't solve something if it's not already in decent shape is crucial." Research indicates that organisations with strong data infrastructure are significantly more successful in AI implementation (PwC, 2025).

These are not technology problems—they're trust, clarity, and collaboration challenges.

"What we benefit from having is a CIDO (Chief Information and Data Officer) who literally turned Copilot on and made it our default page. People get used to and start trusting AI once they realise it helped them write their email—it can't be that bad."

Sarah Coffin

Director of People Operations at Klipboard

The goal is helping HR to do more of what they came here to do.

Practical solutions

"For me, it's moving from the conceptual to the practical. The best way to get people on board is to show evidence of solutions and how they work. Even a plan that looks to pilot one or two aspects, evaluate, come back and then look—that shapes your wider long-term strategy."

Grant Walsh

Head of HR Service Excellence at Police Scotland

The roundtable participants shared valuable approaches for overcoming these barriers:

Start small and demonstrate value. Grant Walsh emphasises: "For me, it's moving from the conceptual to the practical. The best way to get people on board is to show evidence of solutions and how they work. Even a plan that looks to pilot one or two aspects, evaluate, come back and then look—that shapes your wider long-term strategy."

Find your internal champions. Sarah Coffin describes building trust: "We did a competition where we all made our own AI dolls. It was about breaking down the barriers and getting people comfortable with AI to not see it as this big, bad, dangerous thing."

Change the narrative. Don't lead with AI. Lead with what it allows: more time, better insights, fewer forms, more moments that matter. Coffin adds: "Really educating people on what can AI achieve, what is realistic, and taking away that shiny, amazing view you see in the media."

Focus on skills, not just processes. Muriel Schulz provides a compelling reframe: "Let's go back to the true value behind what we are trying to do—help business understand what are the core skills that they will need in the future." This aligns with research showing that the future of work will be less about traditional jobs and more about dynamic skill combinations (Jesuthasan & Boudreau, 2022).

Stay grounded in purpose. Use AI to clear space for the real work—coaching managers, growing culture, supporting people. The goal is helping HR to do more of what they came here to do.

Success comes from focusing on human outcomes first, then finding the right technology.

Case study insights

The roundtable discussion revealed several practical applications already showing results:

Technology company (mid-sized) Sarah Coffin's organisation at Klipboard turned on Copilot company-wide and ran AI competitions. The result? "Breaking down barriers of actually getting comfortable with AI so people feel like, 'Oh, it helped me write my email. It can't be that bad.'"

Public sector implementation Grant Walsh from Police Scotland emphasises the importance of governance: "We need to have an approach to data protection and all our compliance commitments. It is important to test the concept and then widen it out."

International retail change Muriel Schulz's approach at Adeo focuses on workforce planning: "Helping business identify the core skills they need today and having them reflect on the core skills they might need tomorrow. From the skills gap, you can help them design action plans—develop people, recruit new people, or automate tasks."

These examples demonstrate that success comes from focusing on human outcomes first, then finding the right technology—including the right HRIS infrastructure—to support those goals. Research supports this approach: organisations that successfully balance human-centred design with technological capability are more likely to achieve sustainable AI adoption (Deloitte, 2025).

"Helping business identify the core skills they need today and having them reflect on the core skills they might need tomorrow. From the skills gap, you can help them design action plans—develop people, recruit new people, or automate tasks."

Muriel Schulz

HR Foresight and Innovation Executive Director at Adeo

An API-first HRIS isn't just nice to have—it's how you build a foundation for ongoing development.

Practical recommendations

"Help people understand what's in it for them by demonstrating the impact of doing nothing versus the benefits of change."

Aidan McKee

Chief People Officer at Stratx Global

Here's how to move from curiosity to confidence, based on the collective wisdom of our roundtable participants:

Reconnect with purpose. As Maduako-Ezeanyika emphasises: "It's about what does it deliver and how does it enable the organisation to deliver its strategic goals. So that's the important conversation and narrative in terms of selling it organisationally."

Prioritise human outcomes. Choose AI projects that improve experience, not just efficiency. McKee suggests: "Help people understand what's in it for them by demonstrating the impact of doing nothing versus the benefits of change."

Integrate AI into your roadmap. It's not a side project. Samantha Laurie recommends a two-tiered approach: "Bring case studies to exec leaders and gamify the experience for broader organisational engagement."

Invest in adaptable systems. An API-first HRIS isn't just nice to have—it's how you build a foundation for ongoing development. Without this flexibility, organisations struggle to integrate new AI capabilities as they emerge.

Measure what matters. Time saved, moments created, sentiment shifted. Start tracking impact early, as Walsh suggests: "You access funds by showing return on investment."

Build organisational readiness. As Maduako-Ezeanyika notes: "Culture change requires taking people with you. It requires collaboration with other departments. Change isn't happening in isolation."

Conclusion

AI doesn't remove the human from HR—it creates more space for it.

By taking a thoughtful, human-first approach, HR can lead this moment with clarity and care. As Jacinta Hennessey observes: "No one got into HR to fill out more forms. These tools can let us do what we all got into this to do—spend more time being human, working with humans."

The roundtable participants agreed: we don't need to know everything to begin. We just need to stay anchored in our role as supporters of trust, connection, and growth. Maduako-Ezeanyika concluded: "At the bottom line, it's about change. The terminology, the messaging, and the language are crucial for getting adoption and buy-in at all levels."

Let's stop thinking of AI as the future—and start seeing it as a friend to the present. One that, with the right systems behind it, can reduce the noise, improve the work, and help us do more of what we came here to do.

"No one got into HR to fill out more forms. These tools can let us do what we all got into this to do—spend more time being human, working with humans."

Jacinta Hennessey

Chief Strategy Officer at HubbubHR

Call to action

Start small. Be curious. Choose tools—and partners—that flex with you. Focus on real human moments. That's how we build a better, more adaptive HR function—together.

References & citations

Bersin, J. (2024). "When AI is framed as an existential threat instead of a practical tool, HR loses the room." From LinkedIn commentary.

Deloitte (2025). Global Human Capital Trends.

Gartner (2024). Future of Work: Employee Perception Report.

Jesuthasan, R., & Boudreau, J. (2022). Work Without Jobs: How to Reboot Your Organization's Work Operating System. MIT Press.

McKinsey & Company (2024). State of AI in HR Survey.

Meister, J. (2025). Future Workplace. Quoted in Forbes HR Tech Trends Panel.

PwC (2025). HR Technology and Workforce Data Readiness Survey.

HubbubHR is redefining HR technology for the global mid-market. We help organisations move beyond rigid legacy systems with a flexible, API designed, AI-enhanced full HR suite—built for speed, simplicity, and customer autonomy. Backed by CHRO-led research, our global “people hub” evolves with you, supported by a hands-on team committed to your success. In today’s dynamic world of work, HubbubHR’s flexible platform, combined with expert service, delivers a solution that adapts to meet your complex needs, empowering leaders to make insightful, data-driven decisions.

HubbubHR is redefining HR technology for the global mid-market. We help organisations move beyond rigid legacy systems with a flexible, API designed, AI-enhanced full HR suite—built for speed, simplicity, and customer autonomy. Backed by CHRO-led research, our global “people hub” evolves with you, supported by a hands-on team committed to your success. In today’s dynamic world of work, HubbubHR’s flexible platform, combined with expert service, delivers a solution that adapts to meet your complex needs, empowering leaders to make insightful, data-driven decisions.