Artificial Intelligence & Generative AI speakers
Artificial intelligence is changing how organisations operate, compete and make decisions. Speakers Associates can help you find an AI keynote speaker or artificial intelligence speaker, as well as expert-led training and workshops that help your people understand what the technology means and use it effectively.
Speakers Associates represents 356 speakers on Artificial Intelligence & Generative AI, including Kemal Apaydin, Olivier Sibony, Rahaf Harfoush, Purna Virji, Itai Green, Limor Ziv, Tom Goodwin, Daniel Trabucchi & Tommaso Buganza, Jennifer Willey and Katja Schipperheijn.
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For a conference, leadership retreat or all-hands, an AI keynote speaker can give your audience a clear view of what is changing, which developments matter and where artificial intelligence can create practical business value.
A keynote is only one option. If your priority is adoption, implementation or better use of the technology across your organisation, a workshop or training programme may be more useful. AI training for employees, AI training for executives and tailored programmes can be brought to focus on your own teams, workflows and business priorities.
The aim is not to make every delegate a technical specialist. It is to help people make informed decisions about where artificial intelligence and generative AI can improve productivity, strengthen existing work and create new opportunities.
Most strategic plans assume next year will look like this year. They are built on linear assumptions about technology that has been advancing exponentially for decades. Investment cycles miss inflection points by years; budgets arrive late to capabilities already commoditising.
Most large organisations have AI strategies their workforces are not equipped to deliver. The capability gap sits inside the firm: tens of thousands of professionals whose roles are quietly being rewritten by automation, while learning functions still ship classroom modules. The question for the executive team is no longer whether to invest in reskilling, but how to do it at the pace technology is moving.
Most organisations do not fail because they cannot think of new ideas. They fail because they cannot stop doing the old ones. The harder problem for senior teams is not generating innovation but dismantling the legacy practices, narratives, and habits that absorb every new initiative and quietly neutralise it.
Once a financial or strategic commitment depends on AI, evidence is needed that the system placed into use can do the work that commitment assumes.
Most organisations are not short of signals about technological change – they are short of a coherent way to read them. AI, robotics, quantum computing, and biotech are not arriving in sequence; they are arriving together, and their strategic implications compound. The real risk is not moving too slowly on one technology. It is misreading how several converging forces will combine to reshape a sector before the organisation has positioned itself to respond.
Most boards now have an AI strategy on paper and almost no honest read on which parts of it are real. The signals coming out of Silicon Valley are loud, contradictory, and shaped by people with money to raise. Leaders need someone who has watched this exact pattern repeat through the PC, the internet, the cloud, and now generative AI, and who will say plainly which bets are durable and which are theatre.
Leaders keep treating digital as a channel when it is now the substrate of their industry. The pattern is consistent: software, data and networks erode the unit economics of physical products, intermediaries and distribution before the incumbent sees the shift. By the time the financial impact lands, the strategic options have already narrowed.
Most large organisations cannot decide whether to back radical bets or defend the core, and the result is a portfolio of pilots that never become businesses. Founders who have actually built and scaled creative ventures think differently about risk, talent, and what an early signal of traction looks like. That perspective is rare inside corporates and increasingly valuable as AI and gaming logic reshape how products get made.
Boards are making capital decisions inside the most disordered macroeconomic environment in a generation. Inflation has not behaved as the textbooks said it would, monetary policy is fighting itself, and structural shocks from AI to Brexit to deglobalisation are landing on top of cyclical pressure. Leaders need a reading of the economy that connects rates, prices, productivity and policy into a single coherent view they can act on.
Customer behaviour rarely follows the logic that marketing plans assume. Small points of friction quietly suppress conversion, loyalty, and adoption while leadership chases bigger strategic levers. The harder question is which behavioural mechanics actually move buyers, and which spend is theatre.
The operating assumptions most organisations still use for strategic planning come from a more predictable century. Leaders are running multi-year capital plans, technology roadmaps and workforce strategies against scenarios that are now changing inside the planning cycle. The real discipline is no longer long-range forecasting; it is anticipation, antifragility and agility, and most leadership teams are not yet trained to reason that way.
Most organisations watch the same trend reports as their competitors and reach the same conclusions. The signals that actually move markets sit one layer deeper, in the cultural shifts and behavioural changes that have not yet been named. The cost of missing them is not a bad quarter, it is a flat decade.