Thinking Beyond Efficiency: How HR Can Lead AI Transformation

Thinking Beyond Efficiency: How HR Can Lead AI Transformation
March 2, 2026 6 mins

Thinking Beyond Efficiency: How HR Can Lead AI Transformation

Thinking Beyond Efficiency: How HR Can Lead AI Transformation

Discover how HR can drive people-first AI transformation with data, upskilling, and smart investments that empower employees and strengthen business impact.

Key Takeaways
  1. AI can empower employees to focus on strategic, high-value work by automating repetitive tasks.
  2. HR plays a crucial role in leading AI adoption by aligning technology with people needs, mapping workflows and ensuring the transformation is people-centred.
  3. Successful AI strategies require HR leaders to collaborate with employees and identify real pain points. Data is also critical to transformation.
Practical Tips to Empower Employees and Make the Right AI Investments

“The biggest myth about AI and its role in the workforce is that it’s a job replacement tool, but that’s not the real story,” said Amanda Scott, Head of Talent Solutions for Aon in North America. “The real role of AI is to help employees free up capacity, to expand their roles and liberate their time for strategic, high-value work.”

Helping both the C-suite and the workforce understand the role of AI is where HR can provide true innovative leadership and colleague enablement. When HR leads AI strategy, it becomes a people-centered transformation, not just a technology upgrade or simple efficiency play.

HR leaders know their people. They know the everyday tasks of the business inside out and they’re in an ideal position to help ensure investments in AI deliver strong returns. Although AI transformation can feel overwhelming and ever-changing, HR leaders can build a successful, people-focused AI strategy by trusting how their core expertise provides value in strategic transformations. Here are three practical tips on how to get started:

1. Start with a business problem and work backwards

Where are employees limited by rote, repetitive tasks that take up way too much of their time? HR leaders have deep insight into where colleagues are burdened by time-consuming activities that take away from meaningful impact. Examples include:

  • HR can work with commercial leaders and operations to process map repeatable skills or tasks, such as calculations, data aggregation and even high-level research activities that are best suited for some form of AI.
  • HR often serves as a first stop for understanding the ideal skills needed for a role, and can help to surface gaps in talent or tech to move the transformation forward.
  • HR often also tends to have ownership of skills data, so they are best suited to make these mapping exercises effective.

“Before selecting an AI solution, it’s essential to thoroughly map out the opportunities and pain points within your organization,” said Marinus van Driel, Head of AI and Workforce Transformation at Aon. This process involves engaging with employees across different levels to identify the specific challenges and bottlenecks they face in their daily tasks and workflows. It also involves evaluating the tasks that employees perform, which can be done easily at an enterprise level using tools like Aon’s AI Sensitivity Analysis. By documenting these issues, HR leaders not only gain a clearer picture of where AI can add genuine value but also demonstrate a collaborative approach that respects employee expertise and input.

“Gaining a clear understanding of real pain points and opportunities fosters buy-in, reduces resistance to change and helps tailor the solution to fit existing processes, ultimately driving better outcomes and more sustainable adoption,” Van Driel explained.

2. Upskill and train employees to grow and transform their roles

Upskilling and reskilling are key to AI and workforce strategies. Giving employees a pathway to grow and gain new skills helps to assuage fears about AI as a job eliminator. Organizations benefit by gaining an engaged workforce that’s ready to contribute to organizational growth.

One of the classic examples of automation increasing employment – while evolving job roles – is the ATM boom of the early 2000s. Many assumed that ATMs would drastically reduce the amount of bank tellers employed in the U.S. However, Economist James Bessen found that teller employment actually grew as banks opened more branches to gain market share. While ATMs automated basic transactions, tellers’ roles evolved to focus on relationship building and selling more profitable products.

To develop effective tailored learning paths, HR leaders should first conduct skills assessments to identify both current capabilities and gaps aligned with evolving business needs. It’s important that AI tools are not simply deployed without adequate training. HR teams are skilled in developing and implementing consistent frameworks, which could include:

  1. Mapping out opportunities for AI use
  2. Mapping out skills gaps for AI and determining training and hiring requirements
  3. Building AI into existing L&D programs and calendars
  4. Housing data in a consistent way to measure success, risks and opportunities over time
  5. Creating a formal cadence of review that works in a dynamic environment
  6. Getting employee feedback on the process – is it really making an impact or are we just checking a box?

Collaborate with employees and managers to co-design training modules that reflect individual career goals and organizational priorities. Most importantly, ensure employees can access the tools they need.

3. Use Data in C-Suite Conversations

Discussions about AI can often feel theoretical, so it’s critical to bring actionable data to CFOs and CEOs. Data provides a tangible vision of the future.

  • Data can quantify the number of hours that could be liberated by using AI tools, paving the way for innovation.
  • The right data can also demonstrate measurable outcomes to help leadership teams envision how AI can transform their operations and strengthen competitiveness.
  • Good data can also allow for more strategic hiring, and less reliance on contractors and third parties

As with AI strategy in general, staying grounded in the day-to-day tasks within your organization helps to provide a concrete workforce transformation strategy. Use data to map AI to specific tasks and show how roles can be transformed, not eliminated. Showing before-and-after scenarios demonstrates the impact of AI adoption to the C-suite and highlights the critical role of HR in implementation.

Conclusion

AI gives HR leaders and incredible opportunity to empower employees, build resilience and foster collaboration across all levels. By focusing on data-driven insights, employee engagement and targeted upskilling, organizations can unlock new avenues for growth while ensuring their workforce remains adaptive and future-ready. The path forward is clear: harness AI to create value, not just automation, and position your people at the heart of transformation.

General Disclaimer

This document is not intended to address any specific situation or to provide legal, regulatory, financial, or other advice. While care has been taken in the production of this document, Aon does not warrant, represent or guarantee the accuracy, adequacy, completeness or fitness for any purpose of the document or any part of it and can accept no liability for any loss incurred in any way by any person who may rely on it. Any recipient shall be responsible for the use to which it puts this document. This document has been compiled using information available to us up to its date of publication and is subject to any qualifications made in the document.

Terms of Use

The contents herein may not be reproduced, reused, reprinted or redistributed without the expressed written consent of Aon, unless otherwise authorized by Aon. To use information contained herein, please write to our team.

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