A Leadership Lunch-Learn Before the Company-Wide AI Rollout
From practical insights to strategic clarity, Alex makes lunch-learns impactful
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Rolling out an AI initiative to the wider company before the leadership team itself is aligned is a reliable way to generate confusion at scale. A leadership lunch-learn, held early enough, is the cheapest insurance against that mistake — and one of the most frequently skipped steps. Once the announcement goes out, disagreements that were private become public, whether the team meant for that or not.
Why this leadership lunch-learn is different
Most AI rollout plans focus energy on the announcement to the broader organization: the all-hands, the memo, the FAQ document. Far less energy goes into making sure the leadership team itself is internally aligned before any of that goes out, which means the rollout often surfaces leadership disagreements in public, in front of the very people it was supposed to reassure.
A lunch-learn positioned before the rollout is a private rehearsal for that public moment. It's where leaders can disagree, get corrected, and settle on a position while the stakes are still internal, instead of finding out in a company-wide Q&A that two leaders are telling contradictory stories.
This only works if it happens early enough. A leadership lunch-learn scheduled after the rollout has already started is a debrief, not an alignment session, and it can't fix messaging that's already gone out the door.
Rollout plans are usually built by a small group and then handed to the wider leadership team late, as a briefing rather than a working session. That sequencing means the first time some leaders truly engage with the plan's weak points is in front of the employees the rollout was meant to reassure.
Running this earlier costs a lunch hour. Running it after the rollout has already gone sideways costs weeks of confused follow-up meetings trying to walk back a message that shouldn't have gone out inconsistent in the first place.
What this keynote delivers
- A pressure-tested AI narrative the leadership team can align on before it goes to the wider organization
- Identification of the specific disagreements likely to surface once the rollout goes public, while there's still time to resolve them
- A realistic view of what agentic AI will and won't change for employees, so the rollout doesn't overpromise
- A rehearsal for the hard questions employees are likely to ask once the initiative is announced
- A short checklist for what still needs to be decided before the broader rollout can proceed
Why Alex for this leadership lunch-learn
Alex advises the California State University system's AI Working Group on governance and rollout questions at a scale involving many campuses and stakeholders, which is the same alignment-before-launch problem this session is built to solve at your company. He is also a WSJ-bestselling author of Fearless Innovation, built on the same premise: a message only works if it survives being repeated by someone else.
Frequently Asked Questions
How far ahead of our company rollout should this be scheduled?
Ideally two to four weeks before the wider announcement, so disagreements surface with time to resolve them. That two-to-four-week window also gives time to circulate a short pre-read if the leadership team wants one.
Does this replace our internal change-management planning?
No — it complements it by aligning the leadership narrative before your change-management team builds materials around it. Change-management teams often sit in on this session so their materials reflect the same aligned language from the start.
Can the session be run virtually if leaders are distributed?
Yes, and virtual delivery is often priced under $10,000.
Is what's discussed kept confidential ahead of the public rollout?
Yes, pre-launch discussions are treated as confidential by default. Scheduling with that lead time also gives your internal communications team room to build materials around the aligned message.
Work with Alex
Before your AI rollout goes company-wide, align your leadership team first at /contact.
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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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