Keynote · Agentic AI

AI Keynote for Real Estate and Construction Leaders

From smart city projects to global property firms, Alex Goryachev equips leaders with tailored keynotes and workshops that transform how we build and live.

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Construction runs on schedules, margins and site safety, not software demos. Real estate runs on capital cycles and tenant demand. AI has to prove itself against those unglamorous realities before this industry cares what it can theoretically do.

Why real estate and construction is different

This industry has watched technology promises come and go, building information modeling, drones, smart building platforms, each arriving with big claims and a slower-than-promised payoff. Executives here have developed a healthy filter for anything pitched as transformative, and an AI keynote that doesn't acknowledge that history starts the conversation already behind.

The work itself is stubbornly physical. Construction schedules depend on weather, permitting, subcontractor coordination and site conditions that no model fully captures, and real estate decisions depend on local market dynamics that shift by submarket. Agentic AI's near-term value here sits in the paperwork and coordination layer, project scheduling, permit tracking, tenant communications, portfolio analysis, not in replacing the judgment calls made on a job site or in a lease negotiation.

There's also a generational and skills gap running through both industries. A workforce shortage in skilled trades sits alongside an aging leadership generation less comfortable with new software, while newer entrants expect digital tools as a baseline. Getting AI adoption right means building for both groups at once, not just the one closer to headquarters.

There's a sequencing insight worth adding here too: firms that start AI adoption in the coordination layer, scheduling, document management, permit tracking, build internal comfort and demonstrable wins before anyone asks AI to touch estimating or design decisions where the stakes and the skepticism are both considerably higher.

Developers and contractors in the same room often want different emphasis, one on portfolio strategy, the other on site-level execution, and a short discovery call ahead of the event lets Alex calibrate the balance to your specific audience mix.

What this keynote delivers

  • A grounded view of where agentic AI actually reduces friction in scheduling, permitting and portfolio management
  • A framework for evaluating AI and proptech claims against this industry's history of overpromised technology
  • A way to bridge the adoption gap between skilled-trades workforces and digitally native newer hires
  • A discussion of innovation culture that works inside project-based, subcontractor-heavy organizations
  • An honest look at what AI still can't replace on a job site or in a lease negotiation

Why Alex for real estate and construction

Alex ran a $1.1B innovation portfolio that generated $400M+ in revenue at Cisco, giving him direct experience separating technology that changes a P&L from technology that just changes a demo, and he sells nothing from the stage.

Leadership teams that have sat through this talk describe the biggest shift as simply having permission to say no to a pitch that doesn't clear the bar, rather than adopting every tool that promises efficiency.

Frequently Asked Questions

What does an AI keynote for a real estate or construction conference cost?

You get availability and a fee range within one business day.

Can the keynote speak to both developers and construction operators in the same room?

Yes, the content is built to be relevant to both sides of the industry without assuming either group's technical depth.

Does Alex address the skilled-trades workforce gap directly?

Yes, the talk includes a practical way to think about AI adoption across a workforce with very different comfort levels with new technology.

How far ahead should we book for an annual industry conference?

Booking several months ahead is ideal, though Alex's team can often work with shorter timelines depending on the calendar.

Work with Alex

To bring this to your next real estate or construction event, get in touch through /contact.

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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.