Jim Markunas
Technical Product Leader, The Austin Consulting Group
Chicago, Illinois, United States
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Jim Markunas is a senior digital product and technology leader with more than 20 years of experience delivering complex enterprise platforms across digital commerce, media, streaming and regulated industries. He has led product strategy, platform modernization and systems-integration initiatives involving AI-enabled workflows, cloud platforms, ERP, order management and customer-facing digital products.
His current work focuses on the operational governance of AI-enabled systems: defining clear decision ownership, escalation paths, auditability, monitoring and human accountability before automation reaches production. Jim brings a practitioner’s perspective on how weak operating models, fragmented data and poorly controlled integrations can turn promising AI initiatives into material operational and security risks.
He regularly writes and speaks about responsible AI adoption, enterprise modernization and the leadership practices required to deploy emerging technologies safely at scale.
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From the Graveyard to AI Assembly Line: How Real Work Will Actually Flow in 3 Years
No more tickets, specs, tests, or endless status meetings. In three years, PMs issue natural-language commands to agent fleets that handle research, prioritization, spec writing, testing, and deployment, while humans audit outputs, escalate edge cases, and own final accountability.
Jim paints this concrete picture of day-to-day work in the agentic world, then exposes what breaks without operating-model redesign: context loss across agent handoffs, brittle API connectors, accountability gaps when no human owns the outcome. Drawing from early production pilots, he walks through workflow patterns that actually scale: dynamic task routing (right agent for right job), confidence scoring (when to escalate to humans), structured audit trails, and governance that keeps humans in control without micromanaging. Jim shares the escalation protocols, monitoring dashboards, and decision frameworks that turn chaos into assembly-line predictability.
When Agentic AI Becomes an Attack Surface: Governance, Control Failures, and Operational Risk
Agentic AI systems promise speed, scale, and automation, but without the right operating model they create new risk faster than most organizations can see it. I will explain how weak governance turns AI initiatives into fragile systems defined by accountability gaps, brittle integrations, activity-based metrics, and decisions that look efficient while increasing operational exposure.
Drawing on my existing frameworks for auditing AI programs, I will tell how to identify governance voids, weak data foundations, and missing strong criteria before they become real business and security problems. I will also walk through practical patterns for production-safe agentic workflows, including confidence scoring, escalation rules, structured audit trails, monitoring dashboards, and controls that keep humans accountable for outcomes. After te session listeners will have a concrete way to evaluate whether their AI program is building resilience.
Cloud-Native Delivery: How to Modernize Enterprise Platforms Without Breaking the Business
Cloud-native adoption usually does not stall because teams lack familiarity with Kubernetes, containers, or microservices. It slows down when modernization has to happen inside large operating environments where commerce, fulfillment, finance, tax, partner, and back-office systems are tightly connected and cannot evolve independently.
In this talk, I will share a practical approach to bringing cloud-native delivery discipline into complex enterprise platforms without turning modernization into a risky rewrite program. Drawing on work across eCommerce, fintech, OTT, utilities, and pharma-related environments, I will show how teams can reduce delivery friction by clarifying system boundaries, sequencing dependencies, coordinating vendors and internal teams, and keeping platform decisions grounded in business continuity.
The session also looks at the issues large organizations tend to underestimate: invisible coupling between systems, unclear ownership, architecture choices disconnected from delivery constraints, and weak observability across integration points. I will outline execution patterns that improve predictability, strengthen trust across teams, and make modernization measurable in operational terms rather than aspirational in slides.
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