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.
Boards are being asked to commit capital and credibility to AI before anyone has a settled view of what the technology will and will not do. The reflex is either to over-promise or to wait. Both positions are expensive, and neither produces the judgment a senior team needs to set policy on adoption, risk, and public trust.
Innovation inside large organisations rarely fails for lack of ideas. It fails because there is no shared method for finding the right ones, no way to repeat the process, and no language that connects a creative breakthrough to the operating plan. Most companies still treat innovation as a personality trait of a few teams rather than a capability the whole business can build.
When an AI system causes harm, most organisations cannot say who is accountable for it. Agentic AI sharpens the problem, because software now takes actions no one explicitly authorised. The legal and governance structures most companies rely on were built for tools that wait to be told what to do.
Most large organisations are still optimised for the linear era: long planning cycles, hierarchical control, fixed assets, internal R&D. The companies eating their margins run on a different operating logic, smaller headcount, leveraged external resources, data feedback loops, community-driven distribution. The strategic question is not whether to adopt new technology. It is whether the organisation itself is structured to compound on it.
Most marketing budgets are run as a performance machine that can be measured, with brand work tolerated as overhead. When growth slows, the brand half is cut first and the performance half stops working. Leaders need to defend why both layers exist, on grounds a CFO will accept.
Boards are being asked to make capital, supply and technology decisions inside a system that no longer behaves the way the textbooks said it should. Macro shocks transmit through opaque networks of banks, regulators and policy elites, and the same leadership team is now expected to translate AI capability into operating advantage without losing its workforce in the process. The strategic question is no longer which trend matters, but which combination of financial, geopolitical and technological pressure will hit the business first.
Organisations deploying AI in high-stakes decisions typically believe their governance frameworks are adequate. The evidence says otherwise: most widely used bias detection tools do not satisfy the legal standards they are meant to address, and explainability is frequently promised but rarely delivered in a form that holds up to regulatory scrutiny. Boards are making accountability commitments about AI that the technical systems underneath those commitments cannot actually keep.
Leadership events convene senior executives at significant cost. The conversations they produce rarely justify it. When a moderator lacks genuine knowledge of the subject – AI adoption, fintech disruption, geopolitical risk – executives default to rehearsed positions. The insight the event was supposed to surface never arrives.
Most boards can name the headline technologies. Few have a serious view on which of them will actually reshape their industry, and on what timeline. Without that judgment, capital and talent get committed against the wrong bet.
A handful of companies now sit between every business and its customers, and the rules of competition no longer reward operational excellence alone. Leaders are being asked to build durable strategy inside an economy where scale, data, and distribution compound for a few and erode for everyone else. The question is no longer how to compete, but where the next defensible position actually exists.
Leadership teams know disruption is constant. The harder question is how to make decisions today that hold up against a future they cannot yet see. Most foresight work stalls in the slide deck, never reaching the operating choices about products, talent, and customers where the value actually sits.