Bryce Goodman

Bryce Goodman Speaking Topics

• The End of “Too Expensive”: What Becomes Possible When Intelligence Gets Cheap?

  A £250 dispute is rarely worth a £10,000 mediator. A small business cannot hire a strategy department. A teacher cannot give thirty children an hour of individual attention each day. Much of our world is organized around things we know how to do but cannot afford to provide. AI could redraw that boundary. Moving from systems that answer questions to agents that carry out work opens possibilities far beyond making existing businesses more efficient. Bryce Goodman explores the needs we have learned to leave unmet, the markets that could form around them and the choices that determine who benefits. The opportunity begins with a question: what would you offer if the expertise it required were no longer the expensive part?

  Key Takeaways:

  • Find opportunities among customers and problems your industry has priced out.
  • Understand how agentic AI can turn scarce expertise into services delivered at scale.
  • Identify the constraints that remain when intelligence becomes cheaper.
  • Rethink products, pricing and delivery around newly viable customer needs.
  • Distinguish efficiency gains from opportunities to create an entirely new market.

• Your Next Employee Might Be Software. Who Will Be Its Boss?

  We built organizations on the assumption that anything capable of exercising judgment would be a person. AI agents challenge that assumption. They can be given objectives, access to systems and permission to act, which makes their deployment a question of authority as much as technology. Who can commit the organization to a decision? When should an agent ask for help? Who notices when it pursues the wrong goal exceptionally well? Bryce Goodman explores the emerging organisation in which people and software share the work, but responsibility cannot be shared so easily. Through the lens of delegation, trust and power, he shows why the arrival of AI agents demands a fresh look at what management is for.

  Key Takeaways:

  • Understand what changes when AI moves from making recommendations to taking action.
  • Treat agent deployment as a decision about authority, permissions and accountability.
  • Identify where autonomy creates value and where supervision consumes it.
  • Recognise how agents could change management roles, team structures and coordination costs.
  • Define the decisions people must retain and the conditions under which agents can act.

• Be Careful What You Optimize For: AI as a Trojan Horse for Better Leadership

  Imagine an AI that does exactly what your organization rewards. It maximizes engagement, cuts costs, hits every target and makes the business worse. The problem begins with a familiar gap: the difference between what we can measure and what we actually value. AI makes that gap harder to ignore because it gives organizations greater power to pursue whatever they specify. Bryce Goodman argues that introducing AI can expose the unresolved questions at the heart of leadership: what success means, which trade-offs are acceptable and who has the authority to choose. Drawing on philosophy and practical AI strategy, he shows how those uncomfortable moments can become the most valuable part of transformation.

  Key Takeaways:

  • Spot the gap between your stated purpose and the behaviour your metrics reward.
  • Understand why more capable AI makes clarity about objectives more consequential.
  • Identify hard choices that better prediction alone cannot settle.
  • Use AI adoption to surface conflicting priorities and misplaced incentives.
  • Build accountability around the decisions leaders make about what to optimize.

• When Answers Are Free, What Is Worth Knowing?

  An apprentice learns by doing work an expert could finish faster. A leader develops judgment by making decisions before the outcome is known. A writer discovers what they think through the effort of putting it into words. AI offers to remove much of that effort. But some of the work it removes is also how we become capable. Bryce Goodman explores a paradox at the heart of the AI age: we may gain access to extraordinary intelligence while weakening our ability to judge its results. What should we continue learning, practising and doing ourselves? This talk examines how businesses and individuals can benefit from AI while preserving the expertise, independence and curiosity needed to direct it.

  Key Takeaways:

  • Distinguish work that produces an output from work that also develops a capability.
  • Recognize where AI assistance strengthens judgment and where it encourages dependence.
  • Rethink apprenticeships and career development as entry-level tasks become automated.
  • Decide which forms of expertise your organization must retain internally.
  • Design human–AI collaboration that makes people more capable over time.

• High Stakes, Big Value: AI Where Getting It Right Matters Most

  The places where AI could create the greatest value are often the places where we are least comfortable letting it act. A missed diagnosis, a disrupted supply chain or a flawed investment decision can carry enormous costs. But so can delay, scarce expertise and leaving an overwhelmed person to decide alone. Drawing on experience bringing AI into consequential settings, Bryce Goodman explores how organizations can move beyond the choice between trusting machines and keeping humans in charge. The challenge is to design a decision process that performs better than either could alone. This talk examines how to judge whether AI is good enough, give it useful authority and build the evidence needed to expand its role.

  Key Takeaways:

  • Find opportunities where better decisions create substantial, measurable value.
  • Compare AI with the actual performance of existing processes, including the costs of delay and inaction.
  • Evaluate systems against the consequences of their mistakes, rather than average accuracy alone.
  • Design human oversight that improves decisions instead of simply adding a sign-off.
  • Build a path from bounded trials to greater authority as evidence of performance grows.