Stop building the same capabilities over and over when everyone builds agents. Standardize and reuse common features across your business.

In this episode of “What’s the BUZZ?”, Andreas Welsch sits down with Samantha McConnell to discuss how large enterprises can build reusable AI agents that create real business value. The conversation moves beyond vendor claims to examine how organizations operationalize agentic AI, manage rapid innovation cycles, and balance empowerment with governance.

Samantha shares how Cox approaches AI through centralized hubs, agent registries, and differentiated governance models for individual productivity agents versus enterprise-scale solutions. The discussion also highlights why adoption is critical, and why many AI agents will have much shorter lifecycles than traditional software products.

Catch the BUZZ:

• Preventing reinvention through AI hubs and agent registries
• Governing enterprise AI agents without slowing innovation
• Managing the lifecycle of rapidly evolving AI agents
• Measuring adoption and business impact, not just usage
• Connecting agent initiatives to clear business success metrics
• Using a land-and-expand approach to scale agentic AI responsibly

Key Takeaways:

• Balance innovation and control by tailoring governance to agent scale and risk
• Design for faster time-to-value and shorter solution lifespans
• Define outcome-based success metrics before deploying AI agents

A practical episode for leaders focused on turning agentic AI from experimentation into repeatable, enterprise-ready impact.

Questions or suggestions? Send me a Text Message.

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Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.

Level up your AI Leadership game with the AI Leadership Handbook (https://www.aileadershiphandbook.com) and shape the next generation of AI-ready teams with The HUMAN Agentic AI Edge (https://www.humanagenticaiedge.com).

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Imagine shrinking a one-hour code review to under ten minutes—and using that same agentic approach to boost sales, reduce fraud, and make branch and call‑center staff far more productive.

In this episode, Andreas Welsch interviews Mo Jamous, CIO at U.S. Bank, who has taken agentic AI from experiments into real production at a major financial institution. Mo walks through what worked, what surprised him, and the practical guardrails banks (and other regulated companies) need to adopt agents safely and effectively.

Episode highlights:

• A clear three‑bucket strategy: persona‑driven productivity, revenue/growth use cases, and operational excellence (fraud, security, DevOps, resilience).
• A concrete win: an agentic code‑review tool built in weeks that reduced review time from ~1 hour to <10 minutes and scaled to hundreds of thousands of reviews per year.
• How to instrument agents for measurement: attach metadata to agents, count executions, and map successful runs to dollar or productivity impact so you can report ROI.
• People, process, platform: upskill teams with hackathons and brown‑bags, put a governance council (risk, security, compliance) in place, and build an orchestration/registry layer to track many agent implementations.
• Common pitfalls: getting stuck on “one tool” decisions, underestimating change management and adoption, and failing to bake monitoring and guardrails into deployments.
• Practical starting advice: pick high‑value, low‑complexity pilots (e.g., developer or call‑center assistants), measure outcomes from day one, and scale using an observability dashboard rather than betting on a single vendor.

Who should listen: business and tech leaders who want actionable guidance for moving beyond demos and into production-ready agentic AI that creates measurable business outcomes.

Want step‑by‑step lessons from an operator who’s done it? Listen to the full episode now to learn how to turn agent AI hype into real business value.

Questions or suggestions? Send me a Text Message.

Support the show

***********
Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.

Level up your AI Leadership game with the AI Leadership Handbook (https://www.aileadershiphandbook.com) and shape the next generation of AI-ready teams with The HUMAN Agentic AI Edge (https://www.humanagenticaiedge.com).

More details:
https://www.intelligence-briefing.com
All episodes:
https://www.intelligence-briefing.com/podcast
Get a weekly thought-provoking post in your inbox:
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Stop chasing flashy multi‑agent demos. The big gains in enterprise AI are coming from focused, context‑driven systems, not agents in a room.

In this year‑end conversation host Andreas Welsch and analyst Jon Reed cut through the noise to explain where AI is failing in the wild and where it's producing measurable business value. Jon lays out the vendor‑customer gap, the real risks of agentic experiments, and the practical architectures that are working today: compound systems, context engineering, RAG/knowledge graphs, evaluation and observability, and right‑time data layers.

What you’ll learn:

• Why multi‑agent orchestration rarely works at scale today and the narrow exception where it does
• How vendors are ahead of buyers, and how leaders should close the gap with clear communication and upskilling
• The difference between treating AI as a worker vs. a tool, and why that choice matters for people and projects
• Practical, enterprise‑ready wins: document intelligence, procurement RFP automation, AP/AR, hyper‑personalization, and focused assistants
• Why explainability, audit trails, and granular autonomy toggles are essential for trust and compliance
• How to approach AI readiness: clean data, metadata/annotation, and composing smaller specialized models into reliable workflows

If you build or buy AI in the enterprise, this episode is full of real examples and honest advice on where to invest, what to avoid, and how to design systems that produce results now, while preparing for broader scale.

Tune in to hear the full conversation and get actionable guidance for turning AI hype into business outcomes.

Questions or suggestions? Send me a Text Message.

Support the show

***********
Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.

Level up your AI Leadership game with the AI Leadership Handbook (https://www.aileadershiphandbook.com) and shape the next generation of AI-ready teams with The HUMAN Agentic AI Edge (https://www.humanagenticaiedge.com).

More details:
https://www.intelligence-briefing.com
All episodes:
https://www.intelligence-briefing.com/podcast
Get a weekly thought-provoking post in your inbox:
https://www.intelligence-briefing.com/newsletter