An Executives Offsite Session Built to Survive the First 90 Days After
From retreats to global strategy sessions, Alex guides executives toward future-focused action
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The energy in the room at the end of an executives offsite is not the problem. What happens to that energy by the time everyone's back in their normal Monday meetings usually is. Momentum has a half-life, and most offsite AI conversations don't survive past the first two weeks back at the office.
Why this executives offsite is different
Offsites are good at producing a feeling of alignment that rarely survives contact with the calendar back at the office. Executives leave energized, agree the AI conversation mattered, and then get pulled immediately into whatever was waiting for them, and the offsite's momentum quietly evaporates within a couple of weeks.
The reason isn't lack of sincerity. It's that most offsite sessions are built to produce a good day, not a plan that survives the return to normal operating rhythm. Without something concrete enough to check on later, an offsite's AI conversation becomes a memory rather than a driver of what actually happens next.
What makes a session's impact last is building the follow-through into the session itself: specific commitments, a realistic timeline, and a built-in reason for the executive group to revisit progress instead of assuming the offsite conversation was the finish line.
The usual failure isn't a bad offsite; it's a good one that never gets translated into anything the calendar actually protects afterward, so competing priorities simply reclaim the time and attention the AI conversation briefly held.
A plan without a checkpoint is just a hope. Building an actual date to revisit progress into the session itself is what keeps the offsite's AI commitments from quietly becoming last quarter's good intentions.
What this keynote delivers
- A session on agentic AI that ends with a specific, realistic 90-day plan rather than general alignment
- Named commitments the executive group can be held to once they're back at their normal calendars
- A built-in checkpoint structure for revisiting progress instead of letting the offsite's momentum fade
- An honest view of which AI commitments are realistic given competing priorities already on the calendar
- A framework the group can reuse to keep the AI conversation alive without needing another offsite
Why Alex for this executives offsite
Alex's engagement approach is built around a 90-day plan rather than a one-time event, drawing on his experience running a $1.1B innovation portfolio that generated $400M+ in revenue where follow-through, not the kickoff meeting, determined whether initiatives actually happened. He is also a WSJ-bestselling author of Fearless Innovation, a book built on the same premise as this session: ideas only matter once they survive contact with follow-through.
Frequently Asked Questions
Do we get a written follow-up plan after the offsite?
Yes, the session is designed to produce a specific, realistic plan the executive group can reference in the following months. That review can happen by phone and rarely requires the full group to reconvene in person.
Is there a way to check progress after the offsite ends?
Some groups schedule a short follow-up call at the 90-day mark to review what actually moved. The plan itself is kept short and specific enough that progress against it is easy to check without a formal report.
How long does the full offsite session run?
Most run 60–90 minutes, with the follow-through plan built into the close of the session.
Can this pair with other strategic planning sessions at the same offsite?
Yes, it works well alongside broader strategy or planning agenda items. The follow-up call, where scheduled, is typically 20 to 30 minutes and focused specifically on what moved and what didn't.
Work with Alex
To make your next offsite's AI momentum actually last, reach out at /contact.
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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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