Keynote · Agentic AI

An AI Briefing for Your Board Retreat

From Fortune 10 boardrooms to executive retreats, Alex Goryachev equips leaders with tailored keynotes and workshops that help boards thrive in the AI era.

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Verified Attendees Last Quarter

Boards are now expected to oversee AI the way they oversee financial risk — but most directors built their careers before this technology existed, and management's AI updates tend to arrive pre-polished. A board retreat is the rare setting where directors can close that gap honestly, and this session is built precisely for it.

Why board retreats are different

A board's job with AI is not to run it — it's to govern it, and those require different knowledge. Directors don't need to know how models are trained; they need to know whether management's AI strategy is coherent, whether the risk framework is real or decorative, and whether the company is moving at the right speed for its industry. That distinction — oversight fluency versus operator fluency — is what most AI briefings get wrong.

The stakes for directors are becoming personal. AI now touches nearly every domain the board oversees: cybersecurity, financial reporting, workforce strategy, competitive positioning, legal exposure. Regulators and courts are raising expectations for what informed oversight looks like. "We didn't understand the technology" is aging badly as a defense.

There's a dynamic unique to the boardroom: directors hesitate to ask basic AI questions in front of management, and management naturally presents its AI story in the best light. An independent outside voice resets that — a shared, unfiltered baseline and license to ask the naive-sounding questions that are usually the most important.

What this keynote delivers

  • A director-level understanding of AI and agentic AI — enough to govern confidently, with zero technical prerequisites
  • The oversight questions boards should ask management about AI strategy, spend, risk, and talent — and how to recognize evasive answers
  • A pragmatic view of AI governance: what belongs at the board, in committees, and with management
  • How AI shifts the risk landscape the board already owns, from cyber to disclosure to workforce
  • Candid closed-session Q&A where directors can ask anything

Why Alex for board retreats

AI governance is one of Alex's core themes — he serves on the AI Working Group advising the California State University system, one of the largest public enterprises in the country, on exactly these oversight questions. He brings operator credibility boards respect (a $1.1B portfolio that generated $400M+ in revenue at Cisco; featured in Forbes and The Wall Street Journal) and is fully independent, with no product or upsell behind the talk.

Frequently Asked Questions

Can part of the session run as an executive session without management present?

Yes — boards often find that segment the most valuable.

Our directors range from AI-curious to AI-skeptical. How does the session handle that?

By starting from governance, not technology, so no director feels behind.

How long does a board session run?

Typically 60–120 minutes, fit to the retreat agenda with the chair or corporate secretary.

Does Alex provide anything the board can use afterward?

Sessions can include a one-page set of oversight questions directors bring into future management reviews.

Work with Alex

If your next board retreat needs an independent AI briefing, contact the team 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.