Team Development Keynote on Working Alongside AI
From professional growth to future readiness, Alex equips teams with practical strategies
FREQUENTLY FEATURED IN:
ALEX, BY THE NUMBERS
Picture a newly formed cross-functional team on day one of a project kickoff: half the room already uses an AI assistant for drafting and research, the other half doesn't trust it, and nobody has agreed on which is the team's actual working norm. That silent split shapes the next six months more than the project plan does. Nobody schedules a meeting to resolve it, so it hardens into habit before anyone names it as a problem worth solving.
Why team development is different
Team development used to be about communication styles, conflict norms, and trust-building exercises. Now a team also has to agree on something new: how much of the work an AI tool should touch before a human reviews it, and who owns the outcome when it's wrong. Skip that conversation and the team defaults to whoever is loudest, which is rarely the right answer.
There's a quieter risk too. Teams that adopt AI tools unevenly develop a two-speed culture, where some members move fast and others feel left behind or suspicious. That imbalance erodes the psychological safety team development programs are supposed to build, and it does so faster than most facilitators are trained to notice.
Finally, teams are being asked to redesign their own workflows in real time, without a playbook. Development sessions that stay abstract about "the future of work" don't help a team decide what to actually change in next week's standup. The fix isn't a policy document nobody reads; it's a conversation the team actually has together, out loud, early enough that norms form on purpose instead of by accident. Teams that skip this step end up relitigating the same disagreement every few weeks, dressed up as a different argument each time.
What this keynote delivers
- A shared vocabulary for how the team talks about AI-assisted work, so debates stop being personal
- A practical way to set team-level norms for what AI touches first and what stays human-reviewed
- Guidance on closing the confidence gap between early adopters and holdouts on the same team
- A model for redesigning a workflow together, rather than each person adapting alone
- A grounded read on which team habits need to change now versus which can wait
Why Alex for team development
Alex has led innovation tracks for three Olympic Games, environments where teams under real time pressure had to align fast or fail publicly. That experience shapes how he frames team-level AI adoption: as a coordination problem first, a technology problem second. He has also delivered 310+ keynotes and engagements across six continents, which means the coordination patterns he describes have been tested against a genuinely wide range of team cultures, not one company's playbook. That upfront conversation costs one meeting; the alternative costs months of quiet friction that eventually surfaces in a much less convenient setting.
Frequently Asked Questions
Does this work as part of a multi-day team development retreat?
Yes, it's often used as the opening session that sets shared language before smaller breakout exercises later in the retreat.
Can the session be virtual for distributed teams?
Yes, virtual sessions are common for distributed teams.
Will you speak to our specific tools or stay general?
Alex references how teams generally use agentic AI in workflows rather than naming specific vendors, since he doesn't sell or endorse any tools from the stage.
How far in advance should we book for a team offsite?
There's flexibility, but earlier booking gives more room for a tailoring call and calendar fit; reach out as soon as your offsite date is set.
Work with Alex
If your team needs shared ground rules for working with AI before the next sprint, get in touch.
Explore more AI keynotes
- Team Dynamics Insights
- Team Engagement
- Upskilling for the Future of Work
- Workforce Planning
- Team Meeting
Or browse the full directory: AI Keynotes by Audience & Topic.
310+ Keynotes, Workshops & Advisory Engagements
.svg.webp){kind=logo}
Turn your next event into AI and innovation action.
These aren't just better ways to use ChatGPT, or create short-term buzz. This is what the most influential organizations on earth use to shape the future.
Check Alex's availability
Frequently asked questions
If you don't see what you need, message Alex directly using the form above.
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.
.svg)
