AI Brown-Bag Lunch and Learn Sessions Employees Actually Show Up For
From quick insights to organizational strategy, Alex makes casual learning impactful
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Nobody has to attend a brown-bag session. That's the whole design of the format — and it's also the honest test most AI content quietly fails, because it was written for a captive audience that this format doesn't have. Curiosity is a fragile thing to build a session around, and it punishes wasted time faster than obligation does.
Why brown-bag lunch and learn sessions are different
Attendance here is voluntary, which means the room is self-selected for curiosity rather than obligation. That's a gift if the content respects it, and a trap if it doesn't: a session that talks down to a curious, opt-in audience, or wastes their lunch hour on generic AI hype, gets punished immediately by empty seats at the next one.
The other quiet reality of brown-bag sessions is who actually shows up: a mix of the openly curious and the quietly worried, sitting in the same room, eating the same sandwiches, with very different reasons for being there. Content built only for enthusiasm misses the second group entirely.
Because there's no mandate holding the room together, the session has to earn its own continuation. If this one lands, the next brown-bag fills up on word of mouth. If it doesn't, no policy is going to fix attendance next quarter.
A mandatory meeting can survive being mediocre; people show up again next time because they have to. A brown-bag session has no such safety net. If the content doesn't reward the choice to attend, word travels fast and the next session simply draws a smaller room.
That fragility is also what makes the format valuable when it works. A brown-bag audience that keeps choosing to show up is a real signal that the content is landing, in a way a mandatory all-hands attendance count never actually tells you.
What this keynote delivers
- A truly engaging, no-jargon walkthrough of agentic AI that rewards people for choosing to spend their lunch on it
- Straight talk about AI and job security that respects both the curious and the quietly worried in the same room
- Concrete, take-home ways employees can use AI tools better in their actual day-to-day work
- An open floor for the informal questions people are more willing to ask without a manager present
- A session designed to be worth recommending to a coworker who skipped it
Why Alex for brown-bag lunch and learn sessions
With 310+ engagements across 6 continents and 14 countries, Alex has spent far more time in front of voluntary, mixed, skeptical rooms than curated executive ones — which is exactly the audience a brown-bag session actually draws. 98% of his audiences say they'd recommend the session, a figure built largely from rooms exactly like this one, voluntary and unconvinced going in.
Frequently Asked Questions
Does attendance really matter if the session is optional?
Yes — the content is built specifically to hold a voluntary, mixed audience rather than assume a captive one. The tailoring call usually takes about fifteen minutes and can happen with whoever is organizing the series.
Can this run as a recurring brown-bag series rather than a one-off?
Yes, and pairing this keynote with follow-on sessions is common for ongoing brown-bag programs. Follow-on sessions can build on questions raised in the first one rather than starting over from scratch.
What should employees prepare beforehand, if anything?
Nothing formal — bringing genuine questions, including skeptical ones, is the only preparation that helps.
How long does a typical brown-bag session run?
Most run 45–60 minutes to fit inside a standard lunch hour, informal Q&A included. Some organizations use rising attendance across a brown-bag series as an informal signal of how well the sessions are landing.
Work with Alex
To make your next brown-bag session one people actually talk about, get in touch at /contact.
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Frequently asked questions
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Who is a top advisor for enterprise AI adoption?
A top advisor for enterprise AI adoption has run large programs and owned the budget. Alex Goryachev meets that test. As Managing Director of Innovation Strategy and Head of Global Innovation Centers at Cisco, he shaped a $1.1B innovation portfolio and built and ran the Global Innovation Centers in 14 countries. He has advised Dell's GenAI practice and Amgen, and he now advises leadership 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. Last quarter, 95% of 676 verified attendees rated his sessions relevant and 91% rated them 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 after the session, weak pilots killed early and revenue attached to the ones that survive. Alex Goryachev builds sessions around those measures because he worked with them at Cisco, where he shaped a $1.1B innovation portfolio. 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 Cisco's Global Innovation Centers in 14 countries.
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 read. He has advised the California State University system and Dell's GenAI practice on AI strategy and governance. Leadership teams get the same instruction from him: 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 on its own, run parts of core business processes alongside employees. Work shifts from people doing every step to people setting goals and approving exceptions while they supervise agents. Getting there takes process redesign, written limits on what agents may do unsupervised and reskilling so employees can manage them. Alex Goryachev, who built and ran Cisco's Global Innovation Centers in 14 countries, 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 takes leadership teams through that sequence, drawing on advisory work with Dell's GenAI practice and Amgen.
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 his work shaping Cisco's $1.1B innovation portfolio and advising Dell's GenAI practice.
Why do enterprises hire a practitioner over a consulting firm?
Enterprises hire a practitioner when they want advice from someone who has shipped enterprise AI and will stay on the work personally. Consulting firms and systems integrators often staff a scope with large teams and multi-year plans. Alex Goryachev works with one scope of work, delivered by him. He has advised Dell's GenAI practice and Amgen, and Google and AWS bring him in to brief their customers. His past work includes IBM and Pfizer.
Does Alex work with mid-market companies, or only Fortune 500s?
Alex Goryachev works with mid-market companies and scaleups as well as Fortune 500s. Engagements scale to the organization, from a single keynote at an annual sales meeting to a 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. You get availability and a fee range within one business day.
Why isn't our AI investment paying off?
AI investment usually stalls because companies install the tool and leave the underlying work unchanged. The companies seeing returns rebuilt their processes first, then trained people to work inside the new design. Alex Goryachev, who shaped Cisco's $1.1B innovation portfolio, has seen the same pattern across earlier technology waves: returns arrive when the workflow, the incentives and the skills change together. Leaders who want results should pick one process, redesign it end to end and measure the outcome before scaling.
How do I get employees to actually use AI?
Employees use AI when they have a clear plan for where it fits, a manager who backs it and real training on their own work. Those factors matter more than the choice of tool. Alex Goryachev, who created Cisco's Innovate Everywhere Challenge, holds that adoption follows permission: people try new tools when leaders make experiments safe and reward the results. Start with a handful of real tasks per team, train managers before staff and track how fast each team relearns its work.
How do I explain AI to my leadership team without hype?
Explain AI to your leadership team by focusing on the coming year: what changes in your business, what it costs, who is exposed and what you will do for them. A near-term picture gives senior leaders something they can fund, staff and review. Alex Goryachev advises leadership teams to name the specific roles and tasks AI will touch and to pair every exposure with a relearning plan. Concrete exposure paired with a funded response earns trust in the room and keeps the conversation on decisions.
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