An AI Keynote for Your Recurring Strategy Meeting
From executive teams to boardrooms, Alex ensures strategy meetings lead to results
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Here's a blunt question worth asking before your next strategy meeting: is the AI conversation actually moving forward, or does it restart from the same introductory point every time the topic comes up? Recurring strategy meetings are especially prone to this particular failure, since new attendees rotate in over time and old ground gets re-covered again instead of truly built upon.
Why a recurring strategy meeting is different
Unlike a once-a-year off-site, a standing strategy meeting happens often enough on its own that AI needs a real place in the regular rhythm rather than a single dedicated event. That's harder to design well — too little attention and AI stays an afterthought; too much and it crowds out every other strategic topic the meeting needs to cover.
These standing meetings also accumulate a strange, particular kind of staleness over time. The same three AI talking points get repeated meeting after meeting because nobody's updated the framing since the last time an outside voice weighed in, even as the technology and the competitive picture keep moving underneath the conversation.
A periodic outside session, rather than a permanent recurring slot on the agenda, tends to work noticeably better here — it resets the framing, brings in what's actually changed, and gives the standing meeting fresh material to work with for the next several sessions instead of running the same conversation on repeat.
There's a membership problem too. Standing meetings rotate attendees over time, and a periodic reset is one of the few moments where everyone, new and long-standing, is hearing the same current framing at once. Skip that reset for too long and the meeting quietly splits into people who understand where the AI conversation actually stands and people who are still working from a year-old mental model.
What this keynote delivers
- An updated framework for agentic AI that actually resets a stale, repetitive recurring conversation
- A practical way to fold AI into a standing strategy meeting without letting it dominate every single agenda
- Straight, current talk about what's actually changed in agentic AI and AI governance since your last outside briefing on the topic
- Clear guidance on what belongs in the standing meeting versus what deserves its own separate, dedicated session
- A simple framework the team can keep applying on their own, without outside help, between sessions
Why Alex for a recurring strategy meeting
Alex is a LinkedIn Top Voice and WSJ-bestselling author of Fearless Innovation who stays current on agentic AI and AI governance as ongoing, active work, not a topic he covered once. That currency is exactly what a recurring strategy meeting needs from an outside voice. He's delivered 310+ keynotes and engagements across 6 continents and 14 countries, staying current across very different industries and standing-meeting formats.
Frequently Asked Questions
Is this meant to be a one-time session or a recurring booking?
Either works — some organizations bring Alex in once to reset the conversation, others invite him back periodically as the topic evolves.
How much of our standing meeting agenda does this need?
Often a focused 45–60 minute segment is enough to meaningfully update the conversation without displacing the rest of your regular agenda that day.
Will this repeat what we've already covered in past meetings?
No — a short discovery call beforehand identifies what your team has already covered so the session builds forward instead of repeating it.
What's the cost for a session like this?
Fees depend on format, and you get availability and a fee range within one business day.
Work with Alex
To move your strategy meeting's AI conversation forward instead of in circles, 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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