An AI Keynote for Continuing Education Programs
From evening classes to professional certificates, Alex makes continuing education future-ready
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Continuing education units survive on one promise: relevance right now. A degree program can coast on prestige for a while; a CE catalog cannot, and AI is moving faster than most catalogs can be revised on their normal cycle.
Why continuing education programs are different
CE offices usually operate like a business unit inside an academic institution, self-funded or revenue-sharing, with enrollment decided course by course each term. Adult learners paying out of pocket, or spending an employer's tuition benefit, expect a course to pay off almost immediately. A catalog that lags what the market actually wants loses enrollment within a term or two, not gradually, and a slow revenue slide is much harder to explain to a dean than a single bad term.
The competitive set has changed too. Bootcamps, online certificate providers, and corporate learning vendors now pitch AI skills content directly to the same working adults a CE office serves, often with slicker marketing and a narrower, faster promise. A traditional degree program never had to prove its worth course by course against that kind of competition; continuing education always has, and AI has only sharpened the comparison. The institution's brand still matters, but it no longer wins the decision on its own.
Staffing is the quiet constraint behind all of it. Most CE offices run lean, a handful of program managers supported by a large pool of adjunct and industry-practitioner instructors recruited as needed. That instructor pool is an asset when the office can identify and vet practitioners quickly, and a liability when course quality swings wildly from section to section because vetting has not kept pace with demand. Marketing a fast-moving topic like AI makes that inconsistency more visible, not less, because word of mouth among working adults travels quickly.
What this keynote delivers
- A realistic read on which AI-related course content is actually selling to working adults right now
- How to tell practitioner-grade instructors from instructors riding AI enthusiasm without depth
- A catalog refresh cadence that keeps pace with a fast-moving subject without abandoning quality control
- What employer-funded learners expect from an AI-adjacent course versus what marketing promises them
- How to compete on credibility against bootcamps making bigger, faster claims — plus where a CE office should partner with degree programs on AI content rather than duplicate their work
Why Alex for continuing education programs
Alex is Innovator-in-Residence at Tulane University's A.B. Freeman School, a role built around exactly this kind of applied, career-relevant learning, and he is a practitioner, not a futurist, having served as former Managing Director of Innovation Strategy and Head of Global Innovation Centers at Cisco before taking the stage. He brings a working professional's frame of reference, not an academic one, to a working professional's audience.
Frequently Asked Questions
Can the keynote double as a launch event for a new AI-related course?
Yes. Many CE offices use the session to open enrollment for a new AI-adjacent offering, with the keynote itself doing double duty as the marketing moment.
What does a continuing education keynote typically cost?
Virtual sessions suit evening CE audiences, and you get availability and a fee range within one business day.
Do you customize examples for our specific CE course catalog?
Yes. A short discovery call covers your current catalog and enrollment patterns so the session speaks to courses your learners already recognize.
Is a virtual format available for evening or weekend adult learners?
It is, and it is a common choice for CE audiences who attend around work and family schedules rather than during a standard business day.
Work with Alex
If your CE catalog needs an AI anchor event that actually draws enrollment, get details at /contact.
Explore more AI keynotes
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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?
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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