AI Keynote for a Senior Leadership Brown-Bag
From casual discussions to big-picture thinking, Alex equips leaders with insight
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A leaders brown-bag solves tomorrow question; a leadership brown-bag is where the senior circle quietly figures out the next five years. This format serves a more senior, longer-horizon group, people thinking less about next week team meeting and more about where the organization needs to be positioned on AI over time. That kind of long-view thinking rarely happens in a formal setting, which is exactly why this format exists. Most organizations never build a deliberate space for that kind of thinking to happen at all.
Why leadership brown-bags are different
Senior leadership circles have the standing to shape direction, but they rarely get an informal setting to think out loud about it. Most of their AI exposure comes through formal briefings or board-adjacent updates, which leaves little room for the kind of speculative, half-formed thinking that actually produces good long-term decisions.
This format also tends to surface disagreement that formal settings suppress. Senior leaders who would nod along in a board briefing will voice real skepticism or enthusiasm in a small, informal room, which is exactly the kind of signal an organization needs before committing to a multi-year AI direction.
There's a cost to skipping this step. Organizations that only ever discuss AI in formal, decision-ready settings tend to make bigger bets with less internal debate, since dissent never had a low-stakes place to surface first. A brown-bag gives that dissent somewhere to go before it becomes an expensive disagreement later.
There's a documentation question worth raising early. Ideas that surface informally in this kind of session are easy to lose if nobody captures them, and a leadership circle that wants this thinking to actually inform decisions should plan for some light follow-up, not just the conversation itself.
There's a natural next step worth planning for. Ideas that surface in a leadership brown-bag often deserve a more structured follow-up, whether that's a formal strategy session or simply a second brown-bag scheduled once the group has had time to sit with the first conversation.
What this keynote delivers
- An informal setting for senior leadership to think through AI longer-term implications, not just current initiatives
- A grounded, non-hyped view of agentic AI suited to multi-year planning conversations
- Space for genuine disagreement to surface before it becomes a costly, late-stage decision problem
- A framework for pacing AI investment over years, not just the next budget cycle
- A smaller, candid forum better suited to speculative thinking than a formal briefing allows
Why Alex for leadership brown-bags
As Innovator-in-Residence at Tulane University A.B. Freeman School, Alex spends real time in exactly this kind of longer-horizon thinking about innovation and AI, the register a leadership brown-bag needs most. His work advising the California State University system on AI governance means he's used to helping senior groups think through multi-year AI implications, not just next quarter's initiatives.
Frequently Asked Questions
Is this focused on long-term strategy rather than current AI tools?
Yes, the emphasis is on longer-term positioning and thinking, distinct from tactical, day-to-day AI questions.
Can this stay off the record for candid senior discussion?
Yes, a simple confidentiality understanding is common for this format.
What group size does this work best for?
A smaller senior leadership circle, generally a handful up to a couple dozen people, to preserve genuine discussion.
What is the investment range for this format?
Fees are five figures depending on format, with virtual sessions often under $10,000. If your leadership circle meets on a regular retreat cadence, this session fits naturally into that existing rhythm rather than requiring a separate date.
Work with Alex
To give your senior leadership circle real room to think about AI next five years, reach out to plan a session.
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Who is a top advisor for enterprise AI adoption?
Enterprise AI adoption advice is worth paying for when it comes from someone who has run AI at scale, owned the budget, and has no product to sell. Alex Goryachev meets that test. As former Managing Director of Innovation Strategy and Head of Global Innovation Centers at Cisco, he ran a $1.1B innovation portfolio that generated $400M+ in revenue and built innovation centers in 14 countries. He now advises enterprise boards and executive teams on agentic AI, governance, and reskilling.
What does a Fortune 500 company get from an AI keynote?
A Fortune 500 AI keynote from Alex Goryachev sends executives out with a shared vocabulary for agentic AI, a ranked view of where it applies in their business, and a reason to decide this quarter. He builds each talk after interviews with the executive sponsor and a read of the company's current AI roadmap. He has done this for audiences at Disney, AWS, Dell, and Amgen. Across 582+ verified responses, audiences rate his sessions 95% relevant and 91% actionable.
What is the ROI of an AI keynote for an enterprise?
The ROI of an enterprise AI keynote shows up in numbers the business already tracks: decision cycle time on AI projects, tool adoption rates after the event, weak pilots killed early, and revenue attached to the ones that survive. Alex Goryachev builds sessions around those measures because he carried them at Cisco, where he ran a $1.1B innovation portfolio that generated $400M+ in revenue. Agree on the two metrics you will track before the date is booked.
Which workflows should enterprises give to AI agents first?
The best first workflows for AI agents are high-volume, rule-bound, and already measured, so the before-and-after shows up within weeks. Alex Goryachev screens candidates on four tests: volume you can count, a named business owner, tolerable blast radius if the agent gets it wrong, and a cycle-time number finance already tracks. Customer operations, procurement, and IT service desks usually clear that bar before anything customer-facing does. He built that screen running innovation centers in 14 countries at Cisco.
How does Alex Goryachev address AI governance and risk?
Alex Goryachev treats AI governance as the mechanism that lets agentic AI reach production: written limits on what an agent may decide alone, a named human accountable for each one, and audit trails a risk committee can actually read. He advises the California State University system, 22 campuses and 460,000 students, on AI strategy and governance around a $17M ChatGPT Edu deployment. Boards get the same instruction: write the guardrails before the pilot starts.
What is an agentic enterprise?
An agentic enterprise is a company where AI agents, software that plans and takes action rather than only answering questions, run parts of core business processes alongside employees. Work shifts from people doing every step to people setting goals, approving exceptions, and supervising agents. Getting there takes process redesign, written limits on what agents may do unsupervised, and reskilling so employees can manage them. Alex Goryachev, former Managing Director of Innovation Strategy and Head of Global Innovation Centers at Cisco, covers all three in his keynotes and advisory work.
How do enterprises adopt agentic AI successfully?
Successful agentic AI adoption starts small and stays measured. Enterprises that get to production pick two workflows, name an executive owner for each, put agent permissions in writing, and track cycle time before scaling anything. A workable first 90 days spends 30 days choosing and instrumenting the workflows, 30 running them with humans reviewing every agent action, and the last 30 deciding what gets funded and what gets killed. Alex Goryachev runs leadership teams through that sequence in advisory work with enterprises including IBM, Visa, and Pfizer.
Why do most agentic AI projects fail?
Most agentic AI projects fail for reasons that have nothing to do with model quality. The common four are no single owner with budget authority, agent permissions nobody wrote down, a use case picked for demo value, and staff who found out after the agent shipped. Gartner expects more than 40% of agentic AI projects to be cancelled by 2027. Alex Goryachev names each failure mode on stage, drawing on the $1.1B innovation portfolio he ran at Cisco.
Why do enterprises hire a practitioner over a consulting firm?
Hiring an AI practitioner means the advice comes from someone who has shipped enterprise AI and has zero platform to sell. Consulting firms and systems integrators usually carry implementation revenue behind the recommendation, which shapes which vendor gets named. Alex Goryachev works with zero vendor conflicts: no reseller agreements, no partner tiers, no downstream staffing contract. Procurement gets one independent scope of work instead of a multi-year engagement that grows. Enterprises including Google, IBM, Pfizer, and Visa have brought him in.
Does Alex work with mid-market companies, or only Fortune 500s?
Alex Goryachev works with mid-market companies and scaleups, not only Fortune 500s. Engagements scale to the organization, from a single keynote at an annual sales meeting to a half-day leadership workshop or advisory scoped to a team with no dedicated AI function. Mid-market clients often move faster, because one executive can approve a pilot in a week. Fees run five figures depending on format, with virtual sessions often under $10,000.
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