Technology leaders are now operating where strategy, risk, and transformation collide. AI is moving from experimentation to enterprise infrastructure, and the leaders responsible for it — CIOs, CTOs, and CISOs — are being asked to make decisions that shape revenue, operating models, and trust at scale. The challenge isn’t understanding the technology. It’s turning momentum into execution inside complex organizations.
The Technology Leaders Exchange is a curated forum built for the moment. Convened by the Executives’ Club of Chicago in partnership with KOIOS, the Applied Intelligence: Leading AI in the Enterprise series brings together a cohort of 10–12 senior enterprise technology leaders for candid, outcomes-focused dialogue.
This isn’t a stage-driven speaker series. It’s a confidential working room where peers pressure-test real decisions, share what’s actually working inside their organizations, and leave with concrete moves to make inside their own companies. Over four sessions, the cohort moves from calibration to execution — tackling AI adoption, operating models, governance, and enterprise value creation.
The goal is simple: help the leaders shaping the future of enterprise technology move faster, together.
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Monday, April 20, 2026 |12 – 1 p.m. CT | Virtual
The Exchange begins by aligning the people in it. In this virtual kickoff session, the cohort establishes the principles that make the forum work — confidentiality, peer contribution, and an outcomes-first mindset. Leaders will calibrate their organization’s AI maturity, surface the enterprise decisions they are actively trying to move forward, and identify the real blockers slowing progress.
By the end of the session, the group will have a shared understanding of what “value” means for this cohort — whether that’s revenue generation, operational speed, risk management, or operating model transformation. Each leader will leave with a clear decision statement they want to advance over the next 90 days and a commitment to test progress before the cohort reconvenes.
Tuesday, May 19, 2026 | KPMG Ignition Center
The biggest constraint in enterprise AI isn’t awareness — it’s adoption. Many organizations are running pilots and experiments, but very few have cracked the code on scaling usage in ways that create measurable business value. This session focuses on closing that gap.
Through structured peer problem-solving, the cohort will examine where adoption gets stuck inside large organizations — whether the barriers are people, process, governance, data readiness, or leadership alignment. Leaders will bring real challenges into the room and pressure-test solutions together. The session concludes with each participant committing to a targeted 30-day adoption experiment designed to move one critical use case forward inside their organization.
Tuesday, June 9, 2026 | KPMG Ignition Center
As AI evolves from a tool that assists work to systems that can execute workflows, the enterprise operating model begins to change. The question is no longer whether to deploy AI — it’s where autonomous and semi-autonomous systems actually create enterprise value and where they introduce unacceptable risk.
In this session, the cohort will identify and evaluate potential enterprise workflows for agentic AI deployment. Using a shared decision rubric, leaders will assess impact, operational feasibility, governance implications, and control requirements such as human-in-the-loop oversight. By the end of the session, each participant will leave with a defined agentic pilot charter — a specific workflow to test, success metrics, and a clear path toward implementation.
Tuesday, June 23, 2026 | KPMG Ignition Center
Governance is often framed as the brake on innovation. In reality, the organizations moving fastest with AI are the ones that have built governance systems leaders trust. When decision rights, model risk principles, and approval pathways are clear, experimentation scales faster — not slower.
In the final session, the cohort will design a minimum viable governance framework that enables responsible AI deployment without slowing innovation. Participants will also map the lifecycle of an “AI product” — from idea to proof of concept to scaled deployment — creating a practical blueprint they can apply inside their own organizations. Leaders will leave with a governance checklist, a repeatable AI product model, and a concise narrative they can use with executive teams and boards to move initiatives forward.
