Keynote · Agentic AI

AI Keynote Speaker for Union and Labor Organizations

From labor federations to industry unions, Alex Goryachev equips organizations with tailored keynotes and workshops that balance innovation with worker advocacy.

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Union leaders don't need anyone to convince them that AI affects jobs. They already know it does. What they need is a clear-eyed, independent briefing on what agentic AI actually does, so they can walk into the next negotiation with facts instead of just anxiety.

Why union and labor organizations are different

This audience has legitimate, often justified skepticism toward AI messaging, because most of what reaches them comes from management or vendors with an interest in downplaying job impact. A speaker who shows up sounding like a management consultant loses the room instantly, and rightly so. The only version of this talk that works here is one that treats worker concerns as valid data, not an obstacle to manage around.

Bargaining leverage is the practical stakes underneath the concern. Union leadership needs to understand where AI genuinely changes job content, task composition and staffing needs well enough to negotiate specific, enforceable protections, retraining commitments, notice periods, task-scope language, rather than vague reassurances that AI is "just a tool." Precision here isn't academic, it shows up directly in contract language.

There's also a real difference between industries and roles that this audience needs acknowledged rather than flattened: AI's effect on a call center role looks nothing like its effect on a skilled trade or a healthcare role, and a union representing members across different sectors needs a framework flexible enough to handle that variation honestly.

A practical addition for this audience is a short list of questions worth bringing into any AI-related bargaining conversation: what specific tasks does the tool change, what training or transition support comes with that change, and what happens to members whose roles shrink faster than attrition allows for. Precise questions like these produce better contract language than general anxiety does.

Union leadership representing members across multiple sectors often want the talk calibrated to their specific bargaining calendar, and a discovery call ahead of the event lets Alex tailor examples to the negotiations your local or international actually has coming up.

What this keynote delivers

  • An independent, non-management briefing on what agentic AI actually does to job tasks and staffing
  • A framework union leadership can use to identify where specific, negotiable protections make sense
  • Language that treats worker concerns about AI as legitimate input, not resistance to be managed
  • A candid look at how AI's impact varies meaningfully across different sectors and job types
  • A discussion of what retraining and transition support realistically looks like when AI changes a role

Why Alex for union and labor organizations

Alex's core themes include the future of work, and he sells nothing from the stage, which matters to an audience that has good reason to be wary of speakers brought in by management with an agenda.

Union leaders who've used this framework describe the clearest benefit as walking into bargaining sessions with specific language instead of general concern.

Frequently Asked Questions

What does an AI keynote for a union or labor conference cost?

Fees are five figures depending on format, with virtual sessions often under $10,000.

Is this keynote independent from management or employer sponsorship?

Yes, Alex sells nothing from the stage and the content is built to serve the union audience's interests directly, not a management agenda.

Does the talk address bargaining and contract language around AI?

Yes, it gives union leadership a framework for identifying where specific, negotiable AI protections make sense.

Can this keynote speak to members across very different job types in one union?

Yes, the content is built to acknowledge how AI's impact varies by sector and role rather than treating all jobs the same.

Work with Alex

To bring this to your next union or labor conference, reach out through /contact.

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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.