What if you could get your executive's feedback before your big presentation to them (with zero effort)? Agentic AI makes it possible.

In the latest episode of “What’s the BUZZ?”, host Andreas Welsch sits down with Elise Neel, SVP of Global Strategy and Strategic Partnerships at Panasonic, to explore what it really takes for executives to lead in an era of Agentic AI.

This conversation goes beyond the hype and gets into a far more important question: How does leadership evolve when intelligence is no longer scarce?

Catch the BUZZ:

- Why the best leaders are the best orchestrators

- How Agentic AI reshapes operating models in addition to productivity

- Why executive leaders need hands-on experience beyond theoretical understanding

- How sparring agents scale executives’ time and feedback

Leaders looking to move from AI curiosity to real organizational impact find examples and inspiration in this episode to evolve their own leadership approach.

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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What does it actually take to build AI governance that enables innovation instead of slowing it down?

In this episode of “What’s the BUZZ?”, host Andreas Welsch sits down with Walter Haydock, CEO of StackAware, to break down how leaders can move from reactive AI usage to structured, scalable governance without killing momentum.

Together, they discuss why most organizations get AI risk wrong, where governance efforts typically fail, and how to design a program that balances speed, security, and business value. He shares practical insights on defining risk appetite, simplifying policies, and avoiding the extremes that derail AI adoption.

Highlights you’ll get from the conversation:

• Why most companies fall into two traps—“ban AI” or “anything goes”—and how to find the middle ground.
• The three risks every AI leader must address: data confidentiality, IP ownership, and reputation.
• What ISO 42001 actually provides and how it helps operationalize AI governance at any scale.
• The only four ways to handle risk—and why AI doesn’t change these fundamentals.
• How to define risk appetite in real business terms to guide faster, better decisions.
• Why overly complex data classification policies fail—and what to do instead.
• The #1 mistake organizations make when implementing governance programs: unrealistic timelines.

If you want a clear, practical approach to managing AI risk while still moving fast, this episode delivers actionable guidance you can apply immediately.

Listen now to learn how to turn AI governance from a bottleneck into a competitive advantage.

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).

More details:
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What do you do when AI takes the junior roles, and attention becomes your most valuable resource?

Steven Puri and host Andreas Welsch map a practical path from distraction and short-term thinking to sustainable high performance.

In this episode, Steven, a former studio exec, serial founder, and the mind behind a focus app, explains why entry-level jobs are changing, where real human value is rising, and how individuals and teams can design work around attention, not just task lists. He shares concrete techniques for getting into flow, beating the "cold start" procrastination loop, and using AI as a force multiplier rather than a replacement.

Highlights you’ll get from the conversation:

• Why the bottom rungs of traditional career ladders are evaporating and what that means for talent development.
• The new premium on deep work: what humans still do better than LLMs and how to protect that time.
• Practical habits to find your best creative windows (chronotype + simple tracking exercise).
• A productivity hack that actually works: hide everything but your top 3 tasks to defeat paralysis.
• How to use AI tools to prototype, learn, and ship faster — and why that can accelerate career growth.
• Leadership blind spots: the danger of short-term cost cuts and why planning for multi-year development still matters.

If you want actionable ways to reclaim your attention, structure your day for meaningful output, and turn AI into an enabler of skill growth, this episode is full of concrete, repeatable tactics.

Listen now to learn how to turn AI hype into habits and outcomes that actually move your work and career forward.

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).

More details:
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The uncomfortable trust for leaders is this: AI is changing how leadership works, or is it?

In the latest episode of the “What’s the BUZZ?” podcast, host Andreas Welsch sits down with Sadie St. Lawrence, founder of Human Machine Collaboration Institute and author of Becoming an AI Orchestrator, to discuss what it really takes to lead in the age of AI.

Sadie introduces a powerful idea: the future of work belongs to AI orchestrators. They are leaders who know how to guide AI systems the way a conductor leads a symphony.

Here are a few key insights from our conversation:

- The shift from doing to orchestrating
Work is moving from execution to coordination. Instead of completing every task ourselves, professionals will increasingly guide AI systems—asking the right questions, refining outputs, and turning rough drafts into real business value.

- Managers and individual contributors must evolve
Managers often know how to delegate—but may not be using AI themselves. Individual contributors may use AI—but lack experience delegating work. The future requires both groups to develop leadership-level thinking, even without a formal leadership title.

- AI success starts with systems thinking
Many organizations want AI outcomes without the right foundations. Leaders need to understand their data, tech stack, and workflows so that AI can support real business strategy rather than becoming another disconnected tool.

- AI is an opportunity for everyone to lead
You don’t need to be a technical expert to start. The most important step is simple: get your hands on the keyboard and start experimenting. That’s how leaders begin to see what’s possible.

If you want to understand how your role and your organization must evolve in the AI era, this conversation is for you.

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).

More details:
https://www.intelligence-briefing.com
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Stop chasing the rainbow—this episode shows how to turn AI pilots into repeatable programs that actually deliver business value.

Host Andreas Welsch talks with Ivo Strohhammer about the hard work behind scaling AI adoption: moving from experiments to production, building a community that learns together, and helping small and medium businesses avoid the same pitfalls large enterprises faced. Ivo shares hands-on approaches from his work at Siemens and his new local ecosystem: how to enable people, provide secure playgrounds, and balance fast experimentation with the governance and standards needed to scale.

Highlights from the conversation:

• Why employees are your most powerful lever: democratize access, offer secure tools, and create tiered learning paths so people can progress from curious user to local AI champion.
• How to balance speed and structure: let teams experiment but create standards to avoid reinventing the wheel; use short, adaptive planning cycles and measure impact early.
• The difference between everyday AI vs. process AI vs. new AI—and why rethinking processes often produces far larger gains than just layering models on existing workflows.
• Practical ways to help SMEs: open local labs, shared trainings, and a three-stage approach (Awareness → Ability → Application) so smaller orgs can punch above their weight without huge budgets.

Three quick takeaways:

1. Put people first—train, enable, and give secure spaces to experiment.
2. Find the sweet spot between experimentation and standardization—pilot widely, scale selectively.
3. Stay agile—test fast, keep what works, fail fast, and move on.

If you want a practical playbook for making AI stick—whether you lead a global program or run a local SME—this episode is full of examples and actionable advice. Tune in now to hear the full conversation and start turning your AI pilots into lasting programs.

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).

More details:
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All episodes:
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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).

More details:
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All episodes:
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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.

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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).

More details:
https://www.intelligence-briefing.com
All episodes:
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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