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 available. 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?
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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