AI Keynote Speaker for a Leaders Brown-Bag
From informal conversations to big-picture thinking, Alex makes brown-bags meaningful
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A people manager raises her hand at the brown-bag and asks what she is actually supposed to tell her team about AI tomorrow morning. That is the question a leaders brown-bag is built to answer, not strategy, not vision, just the practical, tomorrow-morning version of the conversation. That's a fair question, and a brown-bag is built to answer it without the abstraction a bigger session tends to default to. Most leadership development budgets never account for a session this specific, which is exactly the gap it fills. It also gives leaders a place to compare notes with peers who are managing the exact same questions on their own teams, which a one-on-one conversation with a manager never provides.
Why leaders brown-bags are different
People managers deal in specifics: performance conversations, workload decisions, one-on-ones. A brown-bag informal, discussion-heavy format suits that reality better than a keynote does, because leaders can bring their actual, current management questions instead of absorbing a generic overview.
There is also a peer-support element unique to this format. Leaders hearing how other leaders in the room are handling the same AI-related questions, team pushback, tool adoption, skill gaps, often get as much value from each other as from the speaker.
Consistency across leaders matters too. When each people manager improvises their own answer to the same AI question, teams compare notes and notice the inconsistency, which undermines trust faster than admitting uncertainty would. A shared, practical grounding across the leader group prevents that drift.
There's a scheduling reality worth acknowledging. People managers rarely get uninterrupted time for anything that isn't urgent, and a brown-bag only works if it respects that constraint, delivering real value inside a tight window rather than assuming leaders can extend their lunch hour for the cause.
There's a compounding value to running this more than once. A single brown-bag answers today's questions; a recurring one becomes a place leaders know they can bring whatever AI question came up that week, which builds a habit of asking rather than guessing.
What this keynote delivers
- Direct, tactical answers to the AI questions people managers are actually fielding day to day
- A working understanding of agentic AI pitched at management-level decisions, not strategy
- Peer discussion time built into the format, not just one-way delivery
- Guidance on team-level AI adoption decisions leaders can act on immediately
- A relaxed setting that makes it easier for leaders to admit what they are still figuring out
Why Alex for leaders brown-bags
Future of work is one of Alex's core themes, grounded in the practical, day-to-day version of management questions rather than executive-level abstraction, the register a leaders brown-bag actually needs. His future-of-work work is built around exactly these day-to-day management questions, which is why the session translates so directly into what leaders say in their next one-on-one.
Frequently Asked Questions
Will this cover tactical, day-to-day questions or stay high-level?
Tactical, the format is specifically built around the practical questions people managers are fielding right now.
Can leaders bring their own specific team situations to discuss?
Yes, that is encouraged, the informal format works well with real, current management scenarios brought into the room.
What is a typical length for this session?
45-60 minutes including discussion, though it can run shorter for a strict lunch-hour window.
Is a virtual format available?
Yes, and virtual sessions are often under $10,000. If your organization runs multiple leader cohorts, this format can also be repeated for each group rather than combined into one larger session.
Work with Alex
For practical AI answers your leaders can use tomorrow, get in touch to schedule a brown-bag.
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Frequently asked questions
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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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