Trailblazers and innovators: The role of adaptive leadership and experimentation in AI adoption

Nous recently hosted a summit on the Human Side of Generative AI. Attended by more than thirty leaders, representing the private, public and not-for-profit sectors – financial services, retail, energy, higher education, defence, and more – it was designed to push the curious towards proactive, forward-thinking AI adoption.

We emphasised the human side of AI for a simple reason. While some mistakenly see the technology as a mostly or even exclusively technological question, we remain convinced that it is, in fact, first and foremost a human one. The revolutionary changes that AI has the potential to bring about will impact us first and foremost as people: they will change how we work, how we interact, how we live. The capacities they have the potential to unlock in us – and the capacity to ensure successful adoption that actualises and maximises those benefits – are entirely human, too.

Those latter capacities might best be summed up, as they were at the summit, as the “three Ls”: listening, learning, and leadership. The Human Technology Institute's Llewellyn Spink spoke about the importance of leaders listening to their employees about the hopes for AI and how it might assist in their work and free up capacity, as well as their concerns about its (somewhat overstated) potential to render their skill sets obsolete. AI and data strategist Tina Wiremu-Brook emphasised the importance of learning about the technology, keeping abreast of the latest developments, and following how other sectors and organisations are utilising them.

We spoke primarily about leadership. How can you encourage and model AI adoption in your organisation? How do you combine experimentation with more technical implementation? It quickly becomes apparent that effective leadership both depends on and enables or encourages listening and learning: the leaders who best adapt to the new reality, and who most successfully implement the transition to AI in their organisations, will be those who have listened most attentively to their people and most readily committed themselves to learning while proactively pushing forward in a way that encourages others to speak up, experiment, and learn.

It is this kind of adaptive leadership that renders AI adoption more than a mere technical problem. While getting the technical aspects of the transition right is obviously important – both in terms of having the technological capacity as well as developing clear governance models and the like – it means little without the adaptive work that shifts people’s mindsets and encourages new behaviour, sometimes on a day-to-day basis. Leaders must be trailblazers, ready to ride into the wide blue yonder, as well as mad scientists, ready to experiment and fail.

We don’t only mean experimenting in terms of the various manifestations or applications of AI, though testing these and their relevance to your organisation is obviously important. Different organisations have different needs and the way AI is used, and the burdens it will lift, will obviously differ between them as a result. Adopting AI pell-mell, for its own sake, is as nonsensical as not adopting it at all, or waiting until it is far too late. (You can read about Nous’ Organisational Architecture Framework, which we recently used to explore AI adoption, here. It emphasises the importance of having your mission define your use of AI rather than the other way around.)

No, we mean experimenting with the way you interact with your people to understand what’s really going on for them, with the way you frame the challenge and opportunity of AI, with your leadership style in general. What words are you using to discuss AI? How are you engaging your people, encouraging their own experiments with the technology? How are you taking what they tell you about these, what you and they have learned through trial and error, and factoring them into your next attempt?

Because make no mistake: you will make mistakes. Not only is the wild blue yonder wilder and bluer in the case of AI than it is in other cases of organisational transformation – think repotting a full-grown oak in its entirety as opposed to mere decorative topiary – but the technology is moving too quickly for your first attempt at transition to be the last. This is likely to be a rolling revolution. Adapting your leadership style, and constantly so, is going to be vital.

Many leaders are already demonstrating how, by encouraging experimentation and modelling adoptive behaviours, they can position their organisations at the forefront of this transformation.

JPMorganChase pairs AI experts with senior leaders to identify opportunities for embedding AI into every aspect of the firm. By involving senior leaders, JPMorgan ensures that AI integration is aligned with the company's strategic goals and operational needs, while also fostering a culture of innovation. Non-senior employees are invited to play a crucial role in the bank's AI transformation, too, by contributing to various aspects of AI and data science projects. These employees help in deploying AI technologies across different business units, ensuring smooth and effective integration, and collaborate with leaders and other team members to identify opportunities for automation. By involving employees at all levels, JPMorgan ensures a holistic approach to AI transformation, fostering a culture of innovation and collaboration.

We might also consider the approach of Moderna, which is collaborating with OpenAI to manage its own transition. In 2023, the pharmaceutical and biotechnology giant launched its own instance of ChatGPT, mChat, which was built on the OpenAI API and has since been adopted by more than 80 per cent of the company’s employees. Moderna now has deployed more than 750 GenAI solutions across the business, working with employees across legal, research, manufacturing, commercial, and other functions, augmenting and enhancing their work.

Other organisations are at earlier stages of development. Nous recently completed an evaluation of the Australia Government’s whole-of-government trial of Microsoft 365 Copilot. The largest of its kind in the world, the six-month trial made Copilot available to more than 7600 staff across more than sixty agencies. Chosen for the way it could be integrated into government workplaces with minimal disruption, Copilot and its adoption resulted in numerous efficiency gains across various business-as-usual and office management tasks. Participants also became increasing comfortable exploring the tool’s more novel capabilities, emboldened by the opportunity to experiment in a safe and responsible way. Our recommendations for the public service included that agencies offer specialised training reflecting agency-specific use cases and that effective change management strategies be used to support the integration of generative AI, highlight its benefits, and encourage adoption.

At Nous, our own AI Studio leads the development of internal tools that embed GenAI in group-wide processes, while also creating bespoke, project-specific solutions upon request from individuals and teams. Our leaders encourage AI adoption through communication and behaviour modelling. As development and uptake accelerate, we expect to see our people adapt with intention and become as used to working with and alongside AI as they are with any other tool in their repertoires.

What is perhaps most relevant about the example of the Nous AI Studio is the way it has rendered the “three Ls” a collective concern. On the one hand, it plays a leadership role, enabling people to experiment in a safe way by giving them access to tools with the potential to reduce the more remedial aspects of their workload while increasing their overall productivity. It simultaneously develops more advanced applications that test the boundaries of how the technology might be used. On the other hand, end-user feedback and end-user needs often flow the other way, too, with people asking for applications to be developed – a ChatGPT that can write non-rhyming free verse, for example – that the AI Studio’s leaders might not have thought of or considered. The listening, learning, and leadership begin to flow both ways.

This is an important takeaway and something to keep in mind as you embark upon your own transition. Because of the seismic nature of the shift, it is likely to touch every aspect of your business, and stewardship of AI adoption ultimately belongs to all your employees, at every level, as a result. If you wish to compete with companies that, as yet but a twinkle in some entrepreneur’s eye, are likely to have AI baked into their DNA from the get-go, in addition to being adaptive yourself, you should commit yourself to ensuring that your people are, too.

Get in touch to discuss how your organisation can embrace the potential of AI.

Connect with Christie Allison, David Diviny, and Tony Fiddes on LinkedIn.