Enterprise Leader AI Accelerator

Wednesday, 9:00 AM EST

This one-day leaders program builds practical AI literacy for managers, project leaders, and business stakeholders who need to make informed decisions about AI—without diving into technical implementation. Participants learn the core concepts and current AI landscape in plain language, practice using AI to improve everyday leadership workflows (writing, planning, analysis, and decision support), and leave with concrete artifacts they can use to sponsor and scope real initiatives.

The day is structured around four 90-minute sessions that balance concise instruction with hands-on exercises. Leaders will develop a shared vocabulary (models, assistants, agents, RAG, inference), build an intuition for where AI is genuinely useful versus where it creates risk, and learn a few simple verification habits to improve output quality. A practical workshop segment focuses on turning a real artifact—such as a project update, policy draft, or stakeholder communication—into a leader-ready deliverable with an executive summary, action list, and risk/assumption check, emphasizing clarity and accountability.

The second half of the day shifts from understanding to sponsorship: how to select AI use cases worth piloting, define success metrics, and right-size scope so teams can prove value quickly. Participants work in small groups to complete a use-case canvas and then translate it into a sponsor-ready one-pager that includes constraints, risks, required controls, and measurement plans. The program closes with a lightweight governance and rollout playbook, helping leaders coordinate with technical teams and set expectations for what a reasonable pilot (and a responsible scale-up) looks like in their organization.

AI Demystified for Tech Leaders

Thursday, 9:30 AM EST

This two part executive briefing helps leaders, managers, and decision-makers understand the real technologies behind today’s AI movement — in clear, practical terms.
Rather than avoiding key terms, the session translates them: LLMs, RAG, Copilots, Agents, and the Model Context Protocol (MCP) — showing how each fits into the way organizations build and use AI.

Participants gain an intuitive understanding of how AI systems think, retrieve, and act — and how those capabilities are already showing up in tools across the enterprise.
Through relatable analogies, visuals, and examples, attendees will learn how to talk confidently with technical teams, evaluate AI initiatives, and lead with insight and accountability.

The presentation blends conceptual clarity, leadership relevance, and visual storytelling. It’s designed for executives and non-technical professionals who need to grasp how AI fits into their organization’s strategy, operations, and governance.

1.How Modern AI Really Works
Understand how Large Language Models (LLMs) learn patterns from data and generate responses. See why they don’t “know” — they predict — and why context and validation are essential for business use.

2.Retrieval-Augmented Generation (RAG): Making AI Current
Learn how RAG extends an AI’s capabilities by connecting it to trusted enterprise data sources. Understand how this approach keeps responses accurate, relevant, and policy-compliant.

3.Copilots and AI Assistants
Explore how copilots combine AI reasoning, enterprise context, and workflow integration to support human work. See how GitHub Copilot, Microsoft 365 Copilot, and internal copilots assist teams without replacing them.

4.Agents and AI Autonomy
Examine how AI agents can plan, call tools, and make structured decisions using the “Thought → Action → Observation” loop. Understand how this differs from static chatbots — and how to govern it.

5.MCP (Model Context Protocol): Standardizing AI Connections
Discover how MCP enables AI systems to safely discover and use tools, APIs, and data through a shared protocol — simplifying integration and improving control across departments.

6.Security, Guardrails, and Governance
Discuss the emerging field of AI security: preventing prompt injection, protecting data, and enforcing responsible use. Learn how leadership shapes trust and compliance in AI-enabled operations.

7.The Leadership Playbook for AI Adoption
Gain a framework for evaluating AI initiatives.

AI Demystified for Tech Leaders

Thursday, 11:00 AM EST

This two part executive briefing helps leaders, managers, and decision-makers understand the real technologies behind today’s AI movement — in clear, practical terms.
Rather than avoiding key terms, the session translates them: LLMs, RAG, Copilots, Agents, and the Model Context Protocol (MCP) — showing how each fits into the way organizations build and use AI.

Participants gain an intuitive understanding of how AI systems think, retrieve, and act — and how those capabilities are already showing up in tools across the enterprise.
Through relatable analogies, visuals, and examples, attendees will learn how to talk confidently with technical teams, evaluate AI initiatives, and lead with insight and accountability.

The presentation blends conceptual clarity, leadership relevance, and visual storytelling. It’s designed for executives and non-technical professionals who need to grasp how AI fits into their organization’s strategy, operations, and governance.

1.How Modern AI Really Works
Understand how Large Language Models (LLMs) learn patterns from data and generate responses. See why they don’t “know” — they predict — and why context and validation are essential for business use.

2.Retrieval-Augmented Generation (RAG): Making AI Current
Learn how RAG extends an AI’s capabilities by connecting it to trusted enterprise data sources. Understand how this approach keeps responses accurate, relevant, and policy-compliant.

3.Copilots and AI Assistants
Explore how copilots combine AI reasoning, enterprise context, and workflow integration to support human work. See how GitHub Copilot, Microsoft 365 Copilot, and internal copilots assist teams without replacing them.

4.Agents and AI Autonomy
Examine how AI agents can plan, call tools, and make structured decisions using the “Thought → Action → Observation” loop. Understand how this differs from static chatbots — and how to govern it.

5.MCP (Model Context Protocol): Standardizing AI Connections
Discover how MCP enables AI systems to safely discover and use tools, APIs, and data through a shared protocol — simplifying integration and improving control across departments.

6.Security, Guardrails, and Governance
Discuss the emerging field of AI security: preventing prompt injection, protecting data, and enforcing responsible use. Learn how leadership shapes trust and compliance in AI-enabled operations.

7.The Leadership Playbook for AI Adoption
Gain a framework for evaluating AI initiatives.