Speaking

AI systems can now reason, access data, call tools, make decisions and take action. But most organizations are still governing them as if they were chatbots.

This provocative keynote explores the new questions leaders must answer as AI becomes an actor inside the enterprise: What can the agent access? How autonomous should it be? What actions can it take? And who is accountable when it gets something wrong?

Using Tiarne's 4A Framework — Access, Autonomy, Action and Accountability — and her M0–M6 model of agentic autonomy, audiences leave with a practical way to think about the opportunity, risk and governance of agentic AI.

For decades, enterprise technology has been designed around humans opening applications, navigating interfaces and moving information from one system to another. Agents change that.

An AI agent does not need a dashboard. It can communicate directly with systems, APIs, data and other agents to accomplish an outcome.

This keynote explores what happens when the traditional enterprise interface begins to disappear — and what that means for software, architecture, workflows, operating models and the future of the digital enterprise.

The question is no longer simply “How do we add AI to the business?” It is: what would we build differently if the enterprise were designed for intelligence from the beginning?

The future workforce will not be human or AI. It will be both. Employees will increasingly work alongside copilots, specialist agents, autonomous systems and digital workers capable of performing entire portions of a workflow.

But adding AI workers to an organization designed entirely around humans creates an entirely new set of questions. Who manages an agent? What decisions can it make? When should it escalate? How do humans supervise it? How do you measure its performance? And where should human judgment remain non-delegable?

This keynote moves beyond the simplistic debate about whether AI will “replace jobs” and explores the much bigger transformation ahead: the redesign of work itself.

Drawing on Tiarne's Human + Agent Operating Model, Agentic Modes and Work → Decision → Action framework, audiences learn how to start designing the hybrid workforce.

For generations, knowledge and expertise were scarce. AI is changing that. Analysis, writing, research, coding, design and increasingly execution can now be produced at extraordinary speed and scale.

So when intelligence becomes abundant, what becomes scarce?

This forward-looking keynote explores the capabilities that become more valuable — not less — as AI improves: judgment, curiosity, taste, courage, empathy, imagination, trust and the ability to decide what matters.

Rather than asking what humans will lose to AI, Tiarne asks a more powerful question: what becomes uniquely valuable about being human in a world of abundant machine intelligence?

We know how to test software. We know how to secure networks. We know how to evaluate models. But what happens when the system we are deploying can reason, remember, use tools, interact with other agents and take actions inside the real world?

Traditional AI governance is not enough. This keynote introduces a new way of thinking about AI trust: not as a principle or policy, but as infrastructure.

Tiarne explores why organizations must move beyond testing the model and begin evaluating the entire AI ecosystem — models, agents, data, tools, memory, permissions, workflows, humans and runtime behavior.

Using her work in TEVV-A — Testing, Evaluation, Verification, Validation and Assurance — she shows how organizations can move from “trust us” to “prove it.”

Most of the AI revolution so far has happened behind a screen. The next one will happen in the physical world.

Robots, autonomous vehicles, drones, industrial systems, defense platforms and intelligent machines are beginning to combine AI reasoning with the ability to physically act. That changes the stakes dramatically.

A bad chatbot response is inconvenient. A bad decision made by a machine operating in the physical world can have very different consequences.

This keynote explores the emergence of Physical AI and what leaders need to understand about autonomy, simulation, synthetic environments, safety, security and assurance as intelligence moves from software into machines.

Nearly every organization has experimented with AI. Far fewer have transformed the way the business actually operates. The reason is simple: AI transformation is not fundamentally a technology problem. It is an operating model problem.

This keynote explores why organizations become trapped in endless pilots and what leaders need to change to turn AI experimentation into measurable business value.

Using her AI Transformation Roadmap and AI Operating Model, Tiarne shows how organizations can rethink workflows, data, decision rights, people and platforms around AI.

Organizations have spent decades protecting their most sensitive systems from unauthorized users. Now they are deliberately giving AI agents access to them.

Agents may hold credentials, interact with APIs, retrieve sensitive information, initiate workflows, generate code and take actions across the enterprise. And unlike traditional software, they can reason about what they encounter.

This keynote explores the new security frontier created by agentic AI — and why identity, permissions, autonomy and behavioral monitoring are becoming foundational cybersecurity issues. Using the 4A Framework — Access, Autonomy, Action and Accountability — Tiarne gives security and technology leaders a practical model for understanding agentic risk.

As AI becomes embedded into the operating system of the enterprise, a new strategic question is emerging: who owns your intelligence?

Organizations are beginning to reconsider where their AI runs, which models they depend on, where proprietary knowledge lives and how much strategic capability they are willing to outsource.

This keynote explores the rise of private AI, sovereign AI, specialized models and proprietary intelligence — and why the next competitive advantage may come from controlling the data, models, knowledge and infrastructure that make your organization uniquely intelligent.

Every major technology revolution changes the economics of something. The internet changed the cost of distribution. Cloud changed the cost of computing. AI is changing the cost of intelligence itself.

Research, analysis, software development, content creation and increasingly decision-making can now be performed at a fraction of their historical cost. That creates an extraordinary question for business leaders: if intelligence becomes cheap, what becomes valuable?

This keynote explores how AI changes the economics of expertise, organizational scale, software, services and competitive advantage — and why the organizations that win may be those that understand what remains scarce.