When AI learns from your employees, your customers and your partners, three questions follow close behind. Who agreed, who benefits and who gets a say? Here in Los Angeles, the entertainment industry has already written consent and compensation for digital replicas into its agreements, and every other industry is now facing its own version of the same conversation. California's rules on automated decisionmaking, which apply from January 2027, add a legal edge to it.

This opening keynote explores how to build consent into AI programs from the start. How to be clear about what data and decisions AI touches, how to treat employee voices, faces and expertise with respect, and why the organizations that get this right earn a trust that becomes its own competitive advantage.

Here is a simple test for any AI program. If your main model provider doubled its price, changed its terms or became off limits in one of your markets, how long would it take to move? For many organizations the honest answer is months, because prompts, evaluations, fine tuning and workflows were all built around one vendor without anyone deciding that on purpose.

This keynote panel treats portability as a discipline rather than a hope. Our panelists share how they run switching drills, which parts of the stack they insist on owning, the contract clauses that protect their exit, and how they balance the convenience of one provider against the freedom to leave.

The race for ever larger models makes the headlines, but inside many Southern California aerospace, healthcare, retail and financial companies a quieter story is unfolding. Smaller models trained for a single domain are proving faster, cheaper and easier to govern, especially for precise work like forecasting, pricing, quality control and risk, where a confident guess is worse than no answer at all.

Our panelists share where they swapped the giant for the specialist, what it did to accuracy and cost, and how to decide which problems truly need the biggest brain in the room.

The first experiments were cheap. Running AI across the whole company is a different story. As agents work around the clock and usage spreads into every function, AI spend grows like ivy, quietly and then all at once. Finance wants predictability, teams want freedom, and the CIO sits in the middle holding an invoice nobody forecast.

This panel brings the discipline of cloud cost management to AI. How to see where the money actually goes, set budgets without strangling innovation, route each task to the right model, and build a cost story you can defend in front of the CFO.

The phone call never died. It is still the channel customers reach for when something truly matters, and in Los Angeles that call often moves between English and Spanish in the same breath. For years, automation there meant endless menus and the familiar plea to speak to a human. A new generation of voice AI reasons directly on speech, following context, tone and intent across an entire conversation, in more than one language at once.

This session explores what that means for customer service, sales and internal support. Where it already works, how to serve bilingual customers with real warmth, and how to keep trust when the voice on the line is not a person.

Some of the most valuable data in the enterprise is the data you are not allowed to touch. Patient records, customer conversations, fraud cases, the rare failure that happens once a decade. Synthetic data offers a way through, realistic records that carry the patterns without the people, which matters all the more under California's privacy rules.

This fireside chat separates the promise from the pitfalls. Where synthetic data is already speeding up projects in regulated industries, how to prove it is both useful and truly private, and what happens to models that learn too much from machine made examples and too little from the real world.

Your agents are starting to call tools, negotiate with other systems and hand tasks to agents built by partners and vendors. Behind every one of those conversations sits a new layer of protocols and connectors that most enterprise architectures never anticipated.

This session demystifies the emerging standards that let agents work together, and shows how to adopt them with clear rules for trust, logging and accountability from the very first day.

Most of the AI conversation has lived on screens, in chat windows, documents and dashboards. The next chapter steps into automated port terminals, aerospace and manufacturing plants, warehouses, labs and hospitals. World models help machines understand space, time, cause and effect, so robots and autonomous systems can rehearse an action before they take it.

Our panel explores where physical AI is already creating value across Southern California, what it demands from data and infrastructure, and how leaders prepare their operations, safety teams and people for machines that move.

Every organization has a few people who simply know. The aerospace engineer who remembers why a design choice was made decades ago, the underwriter who senses a bad risk before the numbers show it, the operations lead who knows why a rule was written twenty years ago. Much of what they know was never written down, and many of them are approaching retirement.

This closing conversation explores how leaders are using AI to listen to, record and preserve that expertise while those experts are still in the building. How to invite people to share what they know rather than feel replaced by it, how to turn stories and judgment into something a new colleague or an agent can learn from, and how to honor the people whose wisdom built the company.