AI Keynotes for Marketing, MarTech and AdTech
From creativity to conversion, Alex equips leaders with AI marketing insights
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Marketing is the function where AI hype is loudest and clear thinking is scarcest. Every vendor in the stack now claims an AI feature, generative tools can produce endless content in seconds, and the question underneath all of it is uncomfortable: what human creative work is still worth paying for?
Why advertising, marketing and martech/adtech are different
Marketing lives closer to generative AI than almost any other function, because the technology directly produces the thing marketers make: copy, images, video, targeting decisions. That closeness cuts both ways. The upside is obvious and the threat is personal, and creative teams feel both at once. A session that only sells the upside loses the people whose craft is on the line.
The industry also has a vendor problem. Every martech and adtech provider has rebranded around AI, and separating a real capability from a repackaged feature is now a core skill marketing leaders lack the time to build. Budgets get spent on tools that promise intelligence and deliver dashboards. Meanwhile the flood of AI-generated content is driving down the value of average work and raising the premium on distinctive ideas.
There is a measurement wrinkle too. As AI reshapes how people search and consume content, the channels and attribution models marketers rely on are shifting under them, and last year's playbook quietly stops working.
There is a pace trap unique to this field. Because the tools are so easy to try, marketing teams can mistake constant activity for progress, spinning up experiments faster than they can learn from them. The result is a pile of half-finished pilots and a stack of subscriptions no one fully uses. The more useful discipline is choosing a small number of places where AI actually moves a metric that matters and going deep, rather than chasing every new capability the moment it appears. Knowing what to ignore is now as valuable as knowing what to adopt.
What this keynote delivers
- A clear line between AI capability that changes marketing and vendor features dressed up as intelligence
- Where generative tools help creative teams and where they erode the value of the work
- What still commands a premium when content becomes cheap and abundant
- How shifting search and discovery behavior changes the channels you rely on
- A practical stance for leaders deciding where to invest and where to hold
Why Alex for advertising, marketing and martech/adtech
Alex is the WSJ-bestselling author of "Fearless Innovation," and he brings that book's allergy to hype into a field drowning in it. Just as important, he is independent and sells nothing from the stage, with no vendor relationships, so his read on your stack and your strategy is not quietly steering you toward anyone's product.
Frequently Asked Questions
Is this for an agency, an in-house team, or a martech company?
All three, with the angle adjusted. Agencies focus on the value of creative, in-house teams on stack and strategy, martech firms on where the category is heading. Alex tailors it to who is in the room.
Does he favor particular platforms or tools?
No. His independence is the point. He helps you think clearly about the choices without an incentive to push any specific vendor.
Can the talk speak to both creatives and analysts?
Yes. He bridges the creative and data sides deliberately, since the AI shift lands on both and a marketing audience usually holds both.
Would this work better as a keynote or a working session?
Either. Alex can deliver a sharp keynote to reset how the team thinks, or add a facilitated block to work through your specific channels and stack. Teams deciding where to invest often find the discussion format most useful.
Work with Alex
To cut through the marketing AI noise with an independent voice, reach Alex at /contact.
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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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