Session 5: How CHROs are Helping to Transform Their Organizations Through AI

Update introduction to: We brought together CHROs from a range of industries, including telecommunications, medical devices, and manufacturing, to hear how their organizations were actively piloting, adopting, and implementing AI technology. Here is what we learned.

Three key takeaways from our conversation with CHROs whose organizations are actively piloting, adopting, and implementing AI technology.

Key lessons from CHROs whose organizations are actively adopting AI

Our attendees shared the opportunities, challenges, and lessons they had faced when implementing AI across their organizations.

Lesson 1: The change curve of AI is now exponential

The group discussed the vast change that AI will bring to organizations—and how it would reimagine business models. Professor Tsedal Neeley at Harvard Business School shared how companies need to think about AI in terms of radical change, rather than incremental change. “It’s not about tweaking existing systems; it’s about creating new systems, processes, and structures,” she said. “In five years from now, our organizations will look very different.”

CHROs spoke about the velocity of changes that AI is bringing. One shared: “The pace and rate of change has never moved as fast as it is now. The things we discussed 12 months ago are already irrelevant, and the change curve is exponential.” Another added: “AI might have been around for 20 years, but the next generation of this technology is a fundamental shift that will impact our products, the nature of the workforce, and the way we work.”

All attendees focused on the downsizing of mundane or routine tasks, from admin tasks to customer services, to software development, to Marketing, with the introduction of co-pilot being a fairly ubiquitous starting point. One CHRO pointed to artists and software engineers as the two most disrupted functions, being able to perform their roles significantly faster than before.

With the opportunity that comes from being able to radically re-imagine the organization at scale comes the risks of not keeping pace with competitors. One CHRO shared how AI was “not another fad,” adding that the biggest risk was getting left behind. “AI isn’t a bolt-on. This is changing the business model, breaking the data silos, and rewiring everything … Doing nothing, perhaps due to fear of the unknown, is the worst thing to do. The winners will get involved quickly, make mistakes quickly, and learn quickly.” Another added that accessing talent would be critical to keeping pace. “Without it, we can’t scale or innovate as fast as we want.”

Lesson 2: There is a moral imperative to reskill and upskill talent affected by AI

It was accepted that while every technological revolution has eventually created more jobs than it had axed, AI will radically change the shape of some organizations and talent needs. The group discussed how early AI adoption is often more about augmentation, rather than replacement. “There are plenty of things that AI needs humans for,” one CHRO said. The group discussed how leaders needed to pay constant attention to the experiences of their teams as they interact with AI in their roles, and accept that although productivity may increase, the cognitive load of employees’ remits while leveraging AI won’t necessarily decrease.

However, the group also recognized that AI would inevitably reduce workforces. One CHRO shared: “There will be redundancies due to AI for people at all levels. We have a moral duty and societal responsibility to re-skill, upskill, and support people into new careers.”

As part of this conversation, there was a high level of empathy, and a communal agreement that re-structured talent should be given every opportunity for agency, support, and reskilling. Some approaches included supporting people into new careers, and supplementary skills training. One CHRO also shared how they had offered voluntary redundancies with 120% severance in an effort to increase empathy around AI transformation.

Lesson 3: Breaking the “shame cycle” around AI understanding

The conversation also touched on the transformation of leadership roles and the necessity of building trust and connectivity within the executive team to facilitate meaningful change. This is about a mindset shift. Tristan Jervis, co-leader of RRA’s Technology Practice, explained that while AI transformation needs to be led by the CEO, CEOs very much still need a cabinet of leaders around them who could help deliver change, at scale, including CHROs. It was discussed how C-suite leaders did not have to become deep experts in AI, but have a level of fluency where they could understand the scale of the opportunity, how and where to deploy AI, and how to enact change management across the organization.

Professor Tsedal Neeley shared how two issues typically cause inertia around technology transformation. “First, shame—from those who don’t know anything about AI. Second, feeling overwhelmed—often in the belief that you have to know it all.” Breaking through these barriers—both across leadership teams, the board, and across the wider organization will be critical to accelerating AI adoption and implementation. “When people don’t understand a new technology, especially senior leadership, they get overwhelmed because they think they need to know the entire ecosystem of AI. They don’t.”

The quickest way to break this shame cycle is to adopt the 30% digital fluency rule [see box] as quickly as possible, which will improve engagement and innovation around AI, and encourage teams to share ideas, experiment together, and fail fast.