An AI Keynote for Executive MBA Programs, From Someone Who Ran the Budget
From business schools to boardrooms, Alex connects AI with leadership education
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Executive MBA students have read the case studies. What most AI sessions in these programs don't offer is someone who actually had budget authority over the decisions the case studies describe after the fact. Cohorts can tell within minutes whether a speaker has actually made a call like this or is only describing one secondhand.
Why executive MBA programs are different
Executive MBA cohorts are unusual audiences: working professionals, often already senior, sitting through material during hours carved out of demanding jobs. They have low tolerance for theory that doesn't connect to a decision they'll actually face, and they can tell when a speaker has never had to defend an AI budget in front of a board.
These programs also carry a specific credibility problem with AI content. Faculty expertise tends to be strong on frameworks and light on lived operating experience, while outside speakers often bring energy but no real accountability track record. Cohorts notice the gap immediately, and it shapes how much of the content they actually trust enough to use later.
What executive MBA students actually want from a guest session is different from what a conference audience wants: less inspiration, more judgment. Fewer principles, more of the reasoning behind a real decision that went a certain way, including the parts that didn't work.
Case studies are written after the fact, with the messy parts smoothed out and the uncertainty removed. Executive MBA students already know this, which is why a session built entirely around polished case material tends to generate polite attention rather than real engagement.
What holds a room of working professionals is the reasoning behind a decision while it was still uncertain, including the version of events that didn't make it into any published case, and the tradeoffs that looked different in the moment than they do in hindsight.
What this keynote delivers
- A practitioner's account of agentic AI and innovation strategy grounded in a real $1.1B portfolio, not a hypothetical case
- Direct, classroom-ready reasoning about how AI decisions actually get made and defended inside a company
- An honest look at where innovation initiatives fail, not just the ones that make it into a case study
- Discussion-ready material cohorts can debate and apply to their own current employers
- A model of AI governance thinking useful to students who will sit on boards or in the C-suite themselves
Why Alex for executive MBA programs
Alex is Innovator-in-Residence at Tulane University's A.B. Freeman School of Business, and a WSJ-bestselling author of Fearless Innovation — credentials built specifically at the intersection of business education and operating experience that this format needs. He also ran a $1.1B innovation portfolio that generated $400M+ in revenue as former Managing Director of Innovation Strategy and Head of Global Innovation Centers at Cisco, the operating experience behind the classroom reasoning.
Frequently Asked Questions
Can the session be tailored to a specific MBA course or module?
Yes, a short discovery call with faculty can align the session to a specific course theme, such as innovation strategy or the future of work.
Is this delivered as a lecture, a workshop, or a roundtable discussion?
All three are available; many programs choose a keynote followed by a facilitated roundtable discussion with the cohort.
Can this session run virtually for an online or hybrid cohort?
Yes, virtual delivery works well for hybrid executive MBA formats and is often priced under $10,000.
How long does a typical classroom session run?
Most run 60–90 minutes to allow for real classroom discussion, though shorter formats are available. Programs can also request a shorter guest-lecture format if the course schedule only allows a single class period.
Work with Alex
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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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