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. Virtual delivery reaches the whole leader group without anyone traveling.
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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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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