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?
You get availability and a fee range within one business day. 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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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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