Photo credit: Nick Seagrave via Unsplash
Back in the 2000s, I was lucky enough to work for an organisation which recognised the difference between management and leadership. It wasn’t my first leadership role, but it was my first employer which attempted to teach leadership. I learnt lessons which have stayed with me ever since.
One of those lessons was that, while some leadership qualities stay stable, the context of leadership keeps changing. I only have to think back to the workplace I entered in the late 1980s (smoke filled offices, memo filled intrays, and terminals you had to queue up for) and compare it to the workplace of today. Alongside the changes in attitudes, policies and practices, the most obvious change is in digital technology and its penetration into all aspects of business.
It’s time to return the compliment: technology is changing again and the role of leaders is changing with it. To accompany the course on enterprise AI leadership which Ajit Jaokar and I will be delivering with Oxford University next year, we are writing a book which will be available in early 2027. We hope that it will be helpful to leaders who are figuring out how to lead in the age of AI, and technologists who need help to explain to their leaders how things have changed. We will cover:
Episteme (knowledge): the fundamental characteristics of humans, models, agents and traditional software needed to make sense of their roles within an enterprise.
Ethos (character): the traits and behaviours that a leader will need to embrace in the age of AI, including the relationship that they and their teams have with AI.
Philia (friendship): the team that an AI leader needs to build, and the importance of mutual support and education in a time of shifting skills and emerging expertise.
Arete (excellence or virtue): the ways in which leaders and their teams can guide, control and govern AI to ensure alignment with their values.
Telos (the end, or goal): the vision of an AI enabled organisation, including the integration of AI into business products and processes.
Techne (art or skill): the skills which an AI enabled workforce must have, the skills which AI agents must have, and the ways they work together.
Oikonomia (economy): the supply chain and partnerships which AI leaders will need to build, and practical approaches to managing AI costs and maintaining flexibility.
Phronesis (practical wisdom): the traits of a leader who can face a future of rapidly changing AI capabilities, make sense of it, and lead their organisation.
You may have spotted some unfamiliar terms in that list: those aren’t technical terms from the field of computing or AI, but from Ancient Greek philosophy, particularly the work of Aristotle. As I wrote a while back, at a time when the very nature of reasoning is in question, it seems wise to seek insight in persistent traditions of human thought.
However, although our book will use philosophy as a way to make sense of a shifting world and the leader’s role within it, it is not a philosophy book: those concepts provide the frame in which we explore practical, technical details, as well as frameworks for decision making and governance that are capable of guiding action.
As ever, the blank page is daunting, but we have plenty of questions that will help fill it. There are two more terms we have borrowed from Ancient Greek: hexis, or what a person chooses to be, and praxis, or what a person chooses to do. These terms reflect the two halves of our method: the choices a leader makes to shape themselves and their team; and the choices they make to put AI to work in their organisation.
