Future of Work
Voices shaping how organisations adapt to automation, hybrid models and shifting expectations of work
Speakers Associates represents 224 speakers on Future of Work, including Zavier Coyne, Thimon de Jong, Rahaf Harfoush, Nilofer Merchant, Russell Beck, Jeremy Blain, Katja Schipperheijn, Graeme Codrington, Lauren Ducrey and Kayleigh Fazan.
Most leadership teams treat AI as an efficiency question rather than a question of identity. When algorithms absorb cognitive work, the traits that actually differentiate an organisation become both more valuable and harder to preserve. The strategic question is not whether to adopt AI but what a business chooses to remain unmistakably human about as AI reshapes the default.
Most large organisations have more knowledge than they can use and less curiosity than they need. Process discipline, accumulated expertise and AI tooling do not by themselves produce the next product, the next category, or the next reason for a customer to choose. Leaders are being asked to defend creative capacity inside companies that have spent two decades engineering it out.
Vacancies and unemployment coexist even in growing economies, and most workforce strategies have no rigorous model for why. The mismatch between available work and employed workers is structural, rooted in search frictions that standard hiring logic does not account for. Automation and AI are accelerating job creation and destruction at the same time, introducing new versions of those frictions faster than institutions – or organisations – can adapt.
AI has moved faster than the institutions it is reshaping. Leaders now face a version of the problem that universities are confronting first: when the tools students, employees, and customers use can produce plausible work in seconds, the old boundaries around expertise, integrity, and credentialing stop holding. The question is no longer whether to adopt AI, but which parts of the institution it quietly dismantles if you do.
Automation is closing the distance on the technical work, and the differentiating capability inside organisations is becoming relational: trust, candour, and the quality of conversations under stress. Most cultures have starved those skills for a decade. Leaders inherit teams that collaborate by default, not by intention, and the cost shows up in attrition, stalled change, and customer relationships that never deepen past the transaction.
Mid-market banks and regional financial institutions are losing the talent contest before they get to the strategy contest. Their leadership culture was built for a stable industry that no longer exists, and their employer brand still speaks to a workforce that has moved on. The work is rebuilding both at the same time, while the core business is also being redesigned.
Most large brands are running metaverse and avatar projects inside the same marketing teams that built their websites. The output is decorative, not commercial. Companies that want a serious return from digital worlds need to decide whether to retrofit existing functions or stand up a dedicated avatar-native business, and they need a credible view on which categories of revenue, audience, and intellectual property warrant the second route.
Building a marketplace from zero is a different discipline from running marketing inside a mature business. Leaders who have only operated inside the enterprise tend to under-invest in supply-side acquisition and over-invest in demand-side spend. The question is how to apply enterprise marketing rigour to early-stage growth without losing the founder economics that make scale-up possible.
Work-life balance is the wrong model. It treats work and life as competing demands to manage, not interdependent conditions to cultivate. Engagement spending keeps rising and burnout keeps rising with it, because most leaders are solving for the wrong thing. What organisations actually need is a different framework, not a better implementation of the same one.
Most large organisations were designed for predictability and control. They are now being asked to operate in conditions where neither holds. Senior leaders need a model of leadership that takes uncertainty, meaning and human motivation as starting points, not soft additions to a hard machine.
Most large organisations have run AI pilots. Few have moved AI into operating reality at scale, with clear lines on governance, accountability and where it is allowed to make decisions. Boards now need a sharper read on what AI can actually do for their business, what it should not do, and how to deploy it without inheriting risks they cannot defend in front of regulators or customers.
Most organisations invest in technology to do the same work faster. That gap – between efficiency and genuine effectiveness – is where digital transformation programmes stall and where competitive advantage quietly disappears. As generative AI accelerates the pressure to adopt, leaders face the same trap at greater speed: automate the existing, rather than reinvent what is possible.