An Executives Off-Site Session Built for What Won't Be Said Elsewhere
From board retreats to senior planning sessions, Alex drives alignment and vision
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Executives say one version of their AI opinions in a board update and a different version once the door closes and it's just peers in the room. An off-site is one of the few places that second version gets to exist out loud. The version of the conversation that happens after the doors close is rarely the version anyone would put in a memo.
Why this executives off-site is different
Away from the office, away from direct reports and note-takers, executives tend to admit things they wouldn't in a normal meeting: genuine uncertainty about AI, doubts about their own company's readiness, private worry about being behind competitors. That candor is valuable precisely because it doesn't happen anywhere else on the calendar.
Protecting that candor takes deliberate design. If the session feels like it could be repeated outside the room, or summarized in a memo, executives revert to the same guarded, board-ready answers they give everywhere else, and the off-site setting stops mattering.
The actual output of a session like this isn't a set of slides. It's a more honest shared understanding among the executive group of where the company truly stands on AI, which tends to produce better decisions later than a polished but guarded conversation ever would.
Executives calibrate what they say based on who's listening and what might get repeated, which is a reasonable habit everywhere except the one setting specifically designed to get past it.
Protecting that setting means being explicit, early, that nothing said in the room becomes a talking point outside it, and then actually holding that line rather than quietly summarizing the discussion in a follow-up email anyway.
What this keynote delivers
- A closed-room framing of agentic AI and governance that doesn't need to survive outside the room
- Space for executives to voice doubts about their own company's AI readiness without it becoming a permanent record
- An honest comparison of where the group's real AI position sits versus its public messaging
- A candid read on competitive AI moves, separating genuine threats from posturing
- A private forum for questions executives wouldn't raise with direct reports present
Why Alex for this executives off-site
Alex sells nothing from the stage and holds no vendor relationships, which is exactly why executives tend to speak more freely with him in the room than with an internal facilitator or a vendor-aligned advisor. He also advises the California State University system's AI Working Group in closed sessions, where the same rule applies: candor requires knowing nothing said will leak.
Frequently Asked Questions
Is this session kept confidential?
Yes, closed executive sessions are treated as off the record by default, with an NDA available if your team requires one. That coordinator can also help identify a private space away from the main offsite agenda for this specific segment.
Who should attend this part of the off-site?
The executive group only; this format works best without direct reports or outside note-takers present. The format works equally well early in an offsite, before fatigue sets in, or as a closing session.
How long does this typically run within an off-site agenda?
Most run 60–90 minutes to leave real room for candid discussion beyond the initial framing.
What's the typical cost for this kind of closed-door session?
Fees depend on length and location, and you get availability and a fee range within one business day. Scheduling for this format typically happens directly with the executive assistant coordinating the off-site. Some executive groups also use part of this time to pressure-test a position before it's shared more broadly outside the room.
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To create real candor at your next executives off-site, reach out 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.
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