AI Keynote Speaker for Teacher Training Workshops
From pedagogy to digital innovation, Alex helps educators embrace AI in teaching
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Most professional development on AI hands teachers another tool to try; this workshop hands them a way to think that outlasts whichever tool is popular next year. That distinction is why districts keep bringing this session back for a second and third cohort.
Why teacher training workshops are different
Teachers have sat through more one-off PD days than almost any other profession, and they can tell within ten minutes whether a session respects their time. A workshop about AI has to clear a higher bar than most: it's competing with genuine skepticism from teachers who've seen tool fads come and go, and with genuine anxiety from teachers worried about what AI means for their own job security and classroom authority.
The room is also unusually mixed. Some teachers are already using AI daily to draft lesson plans and differentiate materials; others haven't touched it and don't trust it. A workshop that assumes everyone starts at zero loses the advanced group; one that assumes fluency loses everyone else. The workshops that land are the ones that meet teachers where their actual practice sits, not where a curriculum vendor assumes it sits.
The sustainment problem is real too. A single PD day, however well received, tends to fade against the rhythm of grading periods, testing windows, and everything else competing for a teacher's attention once the workshop ends. Districts that see lasting change usually pair the initial session with some ongoing structure, a coaching cycle, a follow-up check-in, a teacher-led practice group, rather than treating the workshop itself as the finish line. A workshop that's honest about this upfront, and helps a district plan for it, tends to earn more trust than one that implies a single afternoon will change practice on its own. Grade-level and subject differences matter more than most PD planning accounts for. What counts as reasonable AI use in a high school English classroom looks nothing like what counts as reasonable in an elementary math class or a career and technical education shop, and a workshop that treats every teacher as one undifferentiated audience tends to feel abstract to everyone in the room. Building in time for subject-specific application, not just general principles, is often what makes the difference stick.
What this keynote delivers
- A shared vocabulary for AI that works across a mixed-skill teaching staff
- Practical judgment calls for AI in grading, lesson planning, and student work
- Honest discussion of what AI means for teacher workload and job security
- Facilitated discussion time, not just a lecture, for teachers to work through real scenarios
- A framework teachers can apply immediately without waiting on a district policy update
Why Alex for teacher training workshops
Alex's core themes include agentic AI and innovation culture, and he brings the same practitioner grounding from running a real innovation portfolio at Cisco into a room of educators. He sells nothing from the stage, which matters to teachers who are tired of PD that doubles as a product pitch.
Frequently Asked Questions
Who should attend a teacher training workshop on AI?
Classroom teachers across grade levels and subjects; mixed-experience rooms work well because the format adapts to both ends.
Is this a keynote, a hands-on workshop, or both?
Both formats exist — a keynote opens the day, and a facilitated 60–90 minute workshop lets teachers work through real classroom scenarios.
Will this turn into a pitch for a specific AI classroom tool?
No. Alex is independent with no vendor relationships and doesn't sell or endorse specific products from the stage.
How far ahead should we book a teacher training day?
Popular PD dates fill early in the school calendar, so reaching out a semester ahead gives the most flexibility.
Work with Alex
To give your teaching staff a PD day they'll actually reference later, check availability at /contact.
Explore more AI keynotes
- Teachers’ Associations / Unions
- Technical & Vocational Institutes
- University
- University Board Retreats
- Team Engagement
Or browse the full directory: AI Keynotes for Education.
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Frequently asked questions
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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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