Zukunft der Arbeit
Stimmen, die prägen, wie Organisationen sich an Automatisierung, hybride Modelle und verändernde Arbeitserwartungen anpassen
Speakers Associates represents 224 speakers on Zukunft der Arbeit, including Zavier Coyne, Thimon de Jong, Rahaf Harfoush, Nilofer Merchant, Russell Beck, Jeremy Blain, Katja Schipperheijn, Graeme Codrington, Lauren Ducrey und Kayleigh Fazan.
Most organisations talk about innovation as a culture problem. The harder question is whether they have a method anyone can repeat. Without a structured process for breaking preconceptions and rebuilding under real constraints, creative work stays trapped inside a few senior heads and dies on contact with the operating model.
Most leadership teams have formally committed to AI and data as strategic priorities. The harder problem is what comes next. Boards and executive committees that cannot interrogate vendor claims, distinguish genuine capability from hype, or set coherent data governance policy become dependent on specialists whose priorities may not align with theirs. Strategic intent without strategic fluency produces expensive, poorly governed technology programmes – and the gap is widening faster than internal capability is growing.
European boards are planning around an economy whose demographic and fiscal baseline is shifting under them. Pension liabilities, labour supply, and public debt are moving in directions that make the next decade of workforce and investment assumptions unreliable. Leadership teams need a macro reading they can trust before they commit capital or restructure benefits.
Senior teams keep running playbooks that worked a decade ago and wondering why engagement, trust, and pace are all slipping at once. The habits that built the company have become the ceiling on what it can do next. Fixing that means looking hard at leadership behaviour, not at another strategy deck.
Most organisations now ask employees to build trust, influence and visibility across digital channels with no real training in how to do it. The result is a workforce expected to lead, network and represent the brand without the connective skills any of that requires. The cost shows up in disengagement, weak internal networks and leaders who cannot translate authority into presence.
Most large organisations have run AI pilots. Very few have moved them into operating reality. The gap is rarely about the technology. It is about governance, internal capability, legacy stacks and the absence of senior leaders who can credibly translate AI from a vendor pitch into a portfolio of operational bets.
Boards are being asked to make capital and workforce decisions on AI without a shared map of where the technology is actually heading. Internal teams default to either pilot-by-pilot caution or unchecked enthusiasm, and neither produces a defensible long-range position. What is missing is a credible read of what the next decade looks like, grounded in technology history rather than vendor marketing.
Most boards now accept that AI will change their business. Few have a defensible view on what it changes first, what it changes structurally, and what it does to the labour model their P&L assumes. The gap between accepting AI as a trend and treating it as a strategic variable is where serious organisations are exposed.
Organisations are deploying AI faster than they are rethinking what their workforces should do. The gap between automation investment and workforce strategy is not a technical problem – it is an institutional one. Every historical wave of technological disruption has produced the same error: treating short-term labour displacement as permanent decline, or resisting disruption until the window for adaptation has closed.
Organisations are structurally biased toward speed and most leaders know it is costing them. Decisions made too fast, problems solved too shallowly, and talent dismissed too early are not isolated failures. They are symptoms of a culture that treats pace as a virtue and age as a liability, rather than as variables to be managed.
Most organisations have AI budgets. Most are still running pilots. The problem is not investment – it is that AI has been framed as a strategy in its own right, which turns a deployment decision into an open-ended design problem. Meanwhile, the gap between AI experimentation and scaled competitive advantage is narrowing fast. Organisations that cannot move AI into production – aligned to business goals they already have – will cede ground to those that already have.
Most cultures decay quietly while leaders are busy fixing other things. Engagement scores drop, the best people leave first, and remote and hybrid setups make the drift harder to see. The work is figuring out which few cultural levers actually move performance, and pulling them with discipline rather than rituals.