Zach Giglio AI Strategist with Implementation and Training Experience Across 33+ States; U.S. Chamber IOM AI Faculty; TEDx Speaker

Select Keynotes

• A Culture of Innovation: Building Employee-Led AI Adoption
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  A Culture of Innovation: Building Employee-Led AI Adoption

  Successful AI adoption depends on leaders creating the conditions for employees to contribute ideas, test applications, and improve how work gets done.

  Zach Giglio brings firsthand insights from being in the room with executives, managers, and frontline employees, helping them apply AI to everyday business challenges. His implementation and training work spans more than 33 states and thousands of professionals. That ongoing experience gives audiences a practical view of the leadership decisions, employee behaviors, and working habits that help adoption take hold.

  In this keynote, Zach introduces four conditions for building a culture of innovation: innovation readiness, leadership conditions, shared ownership, and lasting momentum. Through stories and examples from his work inside organizations, he shows how leaders can help employees apply their expertise, build confidence through practice, and turn successful experiments into improvements that teams can sustain.

  Key takeaways:

  • Innovation readiness: Identify everyday workflows where AI can save time, improve the quality of work, and create capacity for higher-value responsibilities.
  • Leadership conditions: Build the clarity, trust, and permission teams need to experiment, with clear expectations for human judgment, review, and accountability.
  • Shared ownership: Help employees recognize opportunities, shape solutions, and share what they learn with colleagues.
  • Lasting momentum: Connect early successes to business priorities, measure progress, and build repeatable practices that support continued adoption.
• Moving from AI Curiosity to AI Adoption
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  Moving from AI Curiosity to AI Adoption

  Building consistent AI use starts with relevant applications, employee confidence, and opportunities to practice.

  Zach Giglio works alongside executives, managers, and employees to answer that question inside their organizations. Drawing on implementation and training experience across more than 33 states and thousands of professionals, he shares how teams identify useful starting points, build confidence, and make AI part of everyday work.

  This keynote gives leaders a practical approach to getting adoption underway. Through examples from his ongoing implementation work, Zach shows how to choose manageable applications, engage the people closest to the work, and create opportunities to practice. Audiences leave with a clearer understanding of where to begin and how to help their teams take the next step.

  Key takeaways:

  • Start with real work: Identify recurring tasks where AI can reduce effort, improve clarity, or support better decisions.
  • Choose a useful first application: Select a manageable use case with a clear purpose and a straightforward way to assess its value.
  • Build team confidence: Help employees develop familiarity through relevant examples, guided practice, and shared learning.
  • Establish consistent use: Create expectations and routines that help successful applications become part of everyday work.
• The Human + AI Partnership
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  The Human + AI Partnership

  Your people bring the expertise, context, and judgment that make AI useful.

  Through his work implementing AI with leaders and employees, Zach Giglio sees how people apply their professional knowledge to get better results from the technology. From executive discussions to hands-on sessions with frontline teams, his experience reveals practical opportunities to improve communication, support decisions, and create capacity for the work that matters most.

  This keynote explores how people and AI can work effectively together. Zach shows audiences how to recognize tasks where AI can help, guide it with their own expertise, and evaluate its output thoughtfully. His message helps people see their role clearly and approach AI with confidence, curiosity, and a sense of ownership.

  Key takeaways:

  • Apply human expertise: Use professional knowledge, context, and clear direction to guide AI toward useful results.
  • Create capacity: Identify repetitive tasks where AI can support drafting, organizing, summarizing, and preparing information.
  • Strengthen judgment: Evaluate AI output for accuracy, relevance, and suitability before acting on it.
  • Improve collaboration: Build shared practices for using AI responsibly and exchanging useful approaches across a team.
• AI That Works for Construction and the Built Environment
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  AI That Works for Construction and the Built Environment

  AI is creating practical opportunities to improve estimating, project documentation, safety planning, and everyday construction operations.

  Zach Giglio brings firsthand insights from implementing AI alongside construction executives, project managers, and field teams. His work takes him from leadership meetings to construction-site trailers, helping people use readily available AI tools to address the demands of their actual projects and responsibilities.

  Built around practical examples across estimating, project management, safety, documentation, and operations, this keynote shows how construction organizations can identify valuable applications and help employees use them confidently. Zach connects the tools to the people and processes that determine whether adoption succeeds. Audiences leave with a practical approach to selecting a starting point, reviewing results, and building momentum across the office and the field.

  Key takeaways:

  • Recognize useful applications: Explore how AI can support project documentation, estimating, safety planning, communication, and daily operations.
  • Choose a starting point: Identify a recurring workflow where an improvement in time, clarity, or consistency would have measurable value.
  • Support adoption across teams: Make applications relevant to employees’ responsibilities and build confidence through practice.
  • Keep expertise central: Establish human review and accountability when applying AI to project information and decisions.
  • Measure and share progress: Assess the results of an initial application and use those lessons to guide broader adoption.