An AI Keynote for Your Strategy and Planning Off-Site
From retreats to strategy rollouts, Alex makes planning off-sites meaningful
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Compare, candidly, how most organizations handle AI in strategic planning to how they handle every other major input: market shifts get built into the roadmap from the start, while AI often gets bolted on as a separate slide near the end. This keynote is built to fold AI into the planning process itself, not treat it as an afterthought appended to a finished plan.
Why a strategy and planning off-site is different
A planning off-site is where an organization decides what it's actually going to do for the next year or more — where to invest, what to deprioritize, which bets matter. AI has to compete for space in that plan against every other priority, and it rarely gets evaluated with the same rigor as, say, a new market entry or a product line decision.
Part of the problem is sequencing. Many planning processes finalize the roadmap and then ask how AI fits in, which guarantees AI stays peripheral. The organizations that do this well ask the AI question earlier, at the same time they're deciding overall priorities, so it can actually reshape the plan rather than decorate it.
The other part is ownership. Without someone responsible for making sure AI gets a fair, rigorous hearing in the planning process — not an inflated one, not a dismissive one — it tends to get whatever attention the most vocal person in the room pushes for that day.
There's a knock-on effect too. When AI enters the plan late and underexamined, it often gets a placeholder budget line rather than a reasoned one, and that placeholder has a way of becoming permanent simply because revisiting it feels like reopening a settled conversation. What starts as a rough guess in a rushed final slide can end up governing actual spend for the next four quarters.
What this keynote delivers
- A framework for evaluating AI initiatives with the same rigor as any other roadmap item
- Guidance on when to introduce AI into the planning sequence so it shapes the plan, not just decorates it
- A candid view of where agentic AI truly changes the calculus for next year's priorities
- A way to avoid both overinvesting in hype and underinvesting out of unfamiliarity
- Questions your planning team should be asking about AI that a standard roadmap template won't surface
Why Alex for a strategy and planning off-site
Alex ran a $1.1B innovation portfolio that generated $400M+ in revenue at Cisco, work that required constant, rigorous prioritization against every other strategic priority the company had. His core themes — agentic AI, innovation culture, and AI governance — map directly onto what a planning off-site needs covered. He's delivered 310+ keynotes and engagements across 6 continents and 14 countries, and the framework he brings has been pressure-tested against very different planning cultures, not built around one company's process.
Frequently Asked Questions
When in our planning process should this session happen?
Earlier is better — ideally before priorities are finalized, so the AI discussion can actually influence the roadmap rather than react to it.
Can this session help us actually prioritize competing AI proposals?
Yes, especially when paired with 60–90 minutes of facilitated discussion applying the framework to your real list of proposals.
What should we prepare before the session for a strategy and planning off site?
A rough draft of your current planning priorities, so the AI discussion can reference real tradeoffs instead of hypotheticals.
Is this available as a virtual session for distributed planning teams?
Yes, virtual delivery works well here and is often under $10,000.
Work with Alex
To make AI part of the plan instead of a footnote to it, reach out at /contact.
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Or browse the full directory: AI Keynotes by Event Format.
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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.
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