AI Keynote Speaker for a Team Brown-Bag
From casual discussions to big ideas, Alex helps teams learn and adapt in the AI era
FREQUENTLY FEATURED IN:
ALEX, BY THE NUMBERS
Ten people around a table talk about AI differently than three hundred people in an auditorium. A team brown-bag is small enough that the conversation can be about this specific team's workflow, not a general AI overview that everyone has to translate into their own context afterward. A talk built for a stadium doesn't survive first contact with a table this size, and everyone in the room knows it immediately. Most teams never get asked directly what they think before a new tool shows up.
Why team brown-bags are different
At this scale, generic content fails immediately, a room of ten people doing the same job every day can tell within minutes whether the talk actually understands their work or is reciting a version built for a much bigger, less specific audience.
The intimacy also changes what people are willing to say. A team member who would not challenge an AI rollout decision in a company-wide setting will say plainly, in a ten-person brown-bag, that a particular tool does not fit how the team's actually works, and that feedback is far more useful here than anywhere else.
There's a payoff to getting the scale right. A team that feels heard in a small session is far more likely to actually adopt whatever comes out of it, compared to a team that received the same content as a footnote in a much larger, less specific meeting.
There's a manager dynamic worth naming. A team brown-bag works best when the manager participates as a peer in the conversation rather than as an observer waiting to see how the team reacts, since that posture shift is often what gives quieter team members room to speak up.
There's a practical case for running this before any larger AI rollout, not after. A team that's had an honest brown-bag conversation before new tools arrive tends to adopt them with less friction than a team encountering the same tools cold.
What this keynote delivers
- A workflow-specific conversation about agentic AI, built around this team's actual day-to-day work
- Room for direct, unfiltered feedback on current or planned AI tools
- Concrete, small-scale examples rather than enterprise-level abstraction
- A relaxed setting that surfaces honest reactions a bigger session would smooth over
- Practical next steps sized to a single team, not a company-wide rollout
Why Alex for team brown-bags
Alex has delivered 310+ engagements across formats ranging from large keynotes to small, intimate sessions, and treats a ten-person brown-bag with the same substance as a stage keynote rather than a scaled-down version of it. His willingness to treat a ten-person session with the same preparation as a large keynote is part of why the format works as well as it does.
Frequently Asked Questions
Is this really worth booking for just one small team?
Yes, Alex works at this scale regularly, and a smaller, tailored session often produces more useful discussion than a larger one would for a single team's needs.
What is a typical length for a team-sized brown-bag?
30-45 minutes plus open discussion is common for a group this size.
Can we bring our current AI tools into the conversation directly?
Yes, that is encouraged, bring specific tools or workflows and the discussion can address them directly.
Is a virtual format available for a remote team?
Yes, and virtual sessions are often under $10,000, which fits a single team budget well. If several teams want the same conversation, it's often more effective to run it separately for each one rather than combining them into a single larger session.
Work with Alex
For an honest, team-specific AI conversation, reach out to set one up.
Explore more AI keynotes
Or browse the full directory: AI Keynotes by Event Format.
310+ Keynotes, Workshops & Advisory Engagements
.svg.webp){kind=logo}
Turn your next event into AI and innovation action.
These aren't just better ways to use ChatGPT, or create short-term buzz. This is what the most influential organizations on earth use to shape the future.
Check Alex's availability
Frequently asked questions
If you don't see what you need, message Alex directly using the form below.
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.
.svg)
