Is AI the new ESG? HR’s role in shaping responsibility and readiness

At our recent roundtable dinner with a group of Chief People Officers, hosted by Nick Croucher and Jenny Gardiner, one theme consistently surfaced as both energising and unsettling. Artificial intelligence is no longer an abstract concept or future ambition. It is embedded in everyday workflows, influencing decisions, accelerating automation, and reshaping how work gets done.

What stood out was not just the widespread nature of AI adoption, but the tone surrounding it. There is clear excitement about the potential of generative AI and AI agents to drive efficiency, enhance employee experience, and support digital transformation. Alongside this sits a degree of uncertainty. Many organisations are still working out not just how to use artificial intelligence, but how to think about it in the context of workforce strategy, social responsibility, and long-term sustainability.

“What stood out was not just the widespread nature of AI adoption, but the tone surrounding it. There is clear excitement about the potential of generative AI and AI agents to drive efficiency, enhance employee experience, and support digital transformation. Alongside this sits a degree of uncertainty. Many organisations are still working out not just how to use artificial intelligence, but how to think about it in the context of workforce strategy, social responsibility, and long-term sustainability.”

Ben Francis | Head of People Operations | The Key Group

The tension between opportunity and uncertainty

The conversation returned repeatedly to a central tension. AI presents significant opportunity yet introduces complexity that many organisations are not fully prepared to manage.

On one side, leaders are seeing immediate gains. AI is enabling faster decision making, improved performance management, and new levels of productivity. Predictive analytics is enhancing workforce planning and talent management, while automation is reducing manual processes and freeing up time for more strategic activity. This reflects wider market trends, with almost nine out of ten organisations now using AI in at least one function, although most are still in early stages of scaling its enterprise impact.

On the other side, uncertainty remains. AI governance raises critical questions around data privacy, algorithmic bias, and human oversight. Research highlights a growing gap between rapid AI adoption and the maturity of governance frameworks, creating potential ESG related risks for organisations that move too quickly without sufficient structure.

This is where HR’s role becomes central. HR leaders are uniquely positioned to connect AI adoption with people strategy, ensuring that innovation aligns with employee engagement, leadership development, and the broader future of work.

Is AI becoming the new ESG?

One of the most thought-provoking questions raised during the discussion was whether AI is following a similar trajectory to environmental, social, and governance.

ESG has become a proxy for how organisations demonstrate responsibility, particularly in areas such as sustainability, carbon footprint, and social impact. Increasingly, AI is becoming a signal of how future ready an organisation is.

There are clear parallels:

• Both artificial intelligence and ESG require strong governance, accountability and transparency
• Both shape external perception and internal trust, particularly among employees and stakeholders
• Both demand a clear strategic stance from leadership, including CHROs and executive teams

In fact, AI governance is already being treated as a material investor consideration, reinforcing its connection to broader ESG expectations.

At the same time, there are important nuances:

• There is no universal model for responsible AI or ESG implementation
• Approaches vary depending on industry, regulation, and risk appetite
• Alignment with workforce transformation and business strategy is essential for both

Leading research reinforces that responsible AI frameworks must be tailored and context specific, rather than applied as a uniform model across organisations.

For many organisations, AI is now part of a broader narrative that includes sustainability, innovation, and long term value creation. As with ESG, the absence of a clear position can create as much risk as taking the wrong one.

The evolving complexity of AI governance

AI governance is evolving rapidly and presents distinct challenges. Ownership is often fragmented across HR, IT, legal and business leaders, making alignment difficult. Without clear accountability, organisations can quickly experience inconsistency in how AI is used and understood.

Leaders are also balancing the need for control with the need for innovation. Restrictive policies can limit experimentation and slow reskilling and upskilling efforts. At the same time, a lack of structure can increase risk across data privacy, intellectual property, and ethical decision making.

The pace of change adds further complexity. As generative AI and AI agents continue to evolve, traditional governance frameworks struggle to keep up. This is driving a shift towards principles-based AI governance, where flexibility, human oversight and ethical considerations are prioritised alongside innovation. Global standards such as the OECD AI Principles emphasise values including transparency, fairness, accountability and sustainability, reinforcing the need for adaptable governance approaches.

Ultimately, the most effective governance models are those that combine clear standards with continuous monitoring, cross functional collaboration and the ability to evolve in line with both technological and regulatory change.

A continuous discipline, not a one time solution

One of the clearest insights from the discussion is that AI governance is not a static initiative. It is an ongoing discipline that must evolve in line with technology, regulation and organisational needs.

“The productivity paradox around AI is real!”

Charlotte Forsyth | Board Advisor and Fractional CPO | Dizplai

This requires a more dynamic approach:

• Governance frameworks must be regularly reviewed and adapted as AI capabilities develop
• Workforce strategy should integrate reskilling and upskilling to support long term adoption
• Cross functional collaboration needs to be sustained to ensure consistency and alignment
• Organisations must actively monitor how AI is shaping employee experience, engagement and internal mobility

This thinking aligns with global guidance that positions AI governance as an iterative, evolving process grounded in continuous oversight and improvement, rather than a one time implementation.

For HR leaders, this means embedding AI into broader people strategy, ensuring alignment with talent management, leadership development and organisational values.

The leadership imperative

AI is not just a technology shift, it is a workforce transformation that will redefine how organisations operate.

The organisations that will succeed are those that approach AI with both ambition and accountability. They will invest in HR technology, integrate AI into workforce planning, and prioritise employee wellbeing alongside innovation.

HR leaders have a critical role to play in shaping this future. By aligning AI adoption with organisational culture, social responsibility and long term strategy, they can help ensure that technology enhances, rather than undermines, the human experience of work.

How we can help

For CHROs and HR leadership teams, the priority now is to move from experimentation to intention:

• Define your organisation’s position on AI and its relationship to ESG and sustainability.
• Align stakeholders around a clear approach to AI governance. Invest in the skills, structures and leadership capabilities needed to support transformation.
• Most importantly, keep the conversation active. The future of work will be shaped in real time, and organisations that listen, adapt and lead with clarity will be best placed to succeed.

If you are exploring how to embed artificial intelligence into your workforce strategy, or looking to refine your approach to AI governance, we would welcome the opportunity to continue the conversation.