A Leaders Off-Site Session for Aligning Functional Leaders on AI Execution
From Fortune 10 boards to leadership teams, Alex inspires off-site transformation
FREQUENTLY FEATURED IN:
ALEX, BY THE NUMBERS
Can your functional leaders currently describe your company's AI execution plan the same way? Ask five of them and a leaders off-site usually reveals five plans that were never actually the same one. Five functional leaders can each be executing reasonably and still be executing five different plans.
Why a leaders off-site is different
Functional leaders, unlike executives, are the ones actually running AI implementation inside their own departments day to day. A leaders off-site is where their different, function-specific versions of the AI plan get compared directly, often for the first time, and where the gaps between them become visible.
Those gaps are rarely about disagreement on strategy. They're about execution: which workflows get touched first, how fast to move, what "success" looks like in each function. Left unresolved, these gaps show up later as inconsistent AI rollouts across departments that confuse employees and slow adoption everywhere.
A leaders off-site earns its time when it treats this comparison as the actual agenda, not a byproduct of a general AI keynote. The value is in the room actively reconciling different execution plans, not just hearing the same content in parallel.
Execution misalignment rarely announces itself. It shows up months later as one department's AI rollout looking nothing like another's, with employees comparing notes and concluding, not unreasonably, that nobody was actually coordinating.
Catching that mismatch early, while leaders are already in the same room for other reasons, is far cheaper than untangling it after each function has already built its own version of the plan.
What this keynote delivers
- A structured comparison of how different functional leaders are actually executing on AI right now
- A framework for sequencing AI implementation consistently across departments without forcing identical timelines
- Direct facilitation of the execution disagreements this specific group of leaders hasn't resolved on its own
- A realistic view of where agentic AI truly changes function-specific workflows this year
- A shared reference point leaders can use to keep their execution plans aligned after the off-site ends
Why Alex for a leaders off-site
Alex ran a $1.1B innovation portfolio that generated $400M+ in revenue spanning multiple functions at Cisco, which required reconciling exactly this kind of execution misalignment across departments that a leaders off-site now has to solve for your organization. His core themes, agentic AI, the future of work, and innovation culture, all sit at this same execution layer where misaligned functional plans usually surface first.
Frequently Asked Questions
How is this tailored to our specific functional leaders?
A short pre-session intake gathers where each function's AI execution plan currently stands, and the session is built around reconciling those directly. That intake can happen individually with each leader ahead of time rather than in a group setting.
How long should we plan for this session for a leaders off site?
Most run 60–90 minutes to leave real time for leaders to compare and align their execution plans. The summary produced afterward is written so any leader who missed a specific discussion can still follow the agreed plan.
What should leaders bring to get the most value?
A short summary of their function's current AI rollout plans is the most useful thing to bring.
Can this be one segment of a longer leaders off-site agenda?
Yes, it works well as a focused session within a broader off-site. A brief written summary of the reconciled execution plans is also typically provided for leaders to reference afterward. Some groups also use this time to flag where one function's execution timeline depends on another's, so sequencing gets fixed before it becomes a bottleneck.
Work with Alex
To get your functional leaders executing from the same AI plan, connect at /contact.
Explore more AI keynotes
Or browse the full directory: AI Keynotes by Event Format.
310+ Keynotes, Workshops & Advisory Engagements
.svg.webp){kind=logo}
Turn your next event into AI and innovation action.
These aren't just better ways to use ChatGPT, or create short-term buzz. This is what the most influential organizations on earth use to shape the future.
Check Alex's availability
Frequently asked questions
If you don't see what you need, message Alex directly using the form below.
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.
.svg)
