What’s the BUZZ? — AI in Business

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.
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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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Can you trust an AI agent to act in line with your values — and who’s responsible when it doesn’t?
In this episode, Andreas Welsch talks with AI ethics consultant Rebecca Bultsma about the pitfalls of rushing AI agents into business workflows and practical steps leaders should take before handing autonomy to software. Rebecca draws on her early ChatGPT experiments and academic work in data & AI ethics to explain why generative AI raises fresh ethical risks and how organizations can reduce harm.
What you’ll learn:
Why generative AI and agents amplify old AI ethics problems (bias, hidden assumptions, and Western-centric worldviews).
Why you should build internal understanding first: experiment with low-stakes, traceable use cases before deploying public agents.
The importance of audit trails, explainability, and oversight to trace decisions and assign accountability when things go wrong.
Practical red flags: agents that transact autonomously, weak logging, and complacency about vendor claims.
A legal reality check: new laws (like California’s chatbot rules) are emerging and could increase liability for organizations that deploy chatbots or agents prematurely.
The top takeaways:
Learn by experimenting personally and internally in your organization to discover where agents fail.
Start small with low-stakes, narrowly scoped tasks you can monitor and audit.
Don’t rush; rather, observe others' failures, train your people, and build governance before going public.
If you’re a leader evaluating agents or responsible for AI governance, this episode gives clear, actionable advice for keeping your organization out of the headlines for the wrong reasons. Tune in to hear the whole conversation and learn how to turn AI hype into safer 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:
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What actually changes when AI agents become part of your workforce — and which human skills still matter most?

In this episode, host Andreas Welsch talks with HR and talent-intelligence veteran Todd Raphael about the practical realities of bringing agentic AI into organizations. They move beyond proofs-of-concept to ask the tough questions: How do agents fit into daily workflows, what invisible human contributions should you protect, and how should HR and IT collaborate to redesign roles, org charts, and the employee lifecycle?

Listen for concrete thinking and strategic framing, including:
The hidden value humans bring: Why many critical contributions (trusted relationships, customer touchpoints, institutional memory) don’t appear on job descriptions — and what that means when you automate tasks.
Rethinking structure and advancement: How flatter org models and new measures of impact (knowledge, networks, influence) may change who gets promoted and how leadership is defined.
HR’s seat at the table: Why HR is uniquely positioned to plan holistically for hire-to-retire changes, from skills-based hiring to internal marketplaces, reskilling, and retention when agents handle more tasks.

You’ll also hear examples and practical prompts for leaders: identify the intangible work that must remain human, map tasks vs. relationships before automating, and start workforce planning that considers people and agents together.

If you’re an HR leader, people manager, or technology decision-maker trying to turn agent hype into durable business outcomes, this episode gives you a playbook to start redesigning work the right way.

Tune in now to learn how to protect human advantage and build an effective human+agent workforce.
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
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When AI agents can self‑spawn, act at machine speed and delete their own trails, identity and trust become business-critical.
In this episode, Andreas Welsch talks with Tim Williams—an experienced practitioner who’s helped organizations commercialize AI—about the security gaps agentic AI exposes and practical ways to close them. Tim explains why traditional username/passwords and persistent tokens won't cut it, how trust for agents should be treated like a credit score rather than a binary yes/no, and why observability and transaction-level controls are essential.
Highlights you’ll get from the conversation:
Why agents operate at a different scale and cadence than humans, and the new risks that creates.
Real breach lessons (e.g., persistent token compromises) that show why persistent access is dangerous.
The concept of sliding trust: using a trust score to gate actions (low-risk vs high-risk transactions).
Short-lived, transaction-based approvals and why persistent credentials must be replaced.
Why cryptographically verifiable, immutable identifiers (and why blockchain can help) matter for accountability.
Practical governance: observability, human-in-the-loop checkpoints, and preparing infrastructure in parallel with agent adoption.
Who this episode is for: business leaders deciding what to delegate to agents; security and identity teams rethinking access; product and platform builders designing safe workflows for autonomous systems.
If you want actionable guidance on how to let agents accelerate your business without exposing you to runaway risk, tune in and learn how to turn agent hype into reliable 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:
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Get a weekly thought-provoking post in your inbox:
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AI agents are reshaping how enterprises innovate, organize work, and experience disruption.
In the latest episode of “What’s the BUZZ?”, Andreas Welsch speaks with Christian Muehlroth, CEO of ITONICS, about how agentic AI will redefine innovation management and why many organizations remain structurally unprepared for it.

Here are the key insights from the conversation:
AI’s foundations were created decades ago, but recent advances in computing, interfaces, and delivery models have turned it into a scalable innovation engine.
Each technological wave builds on prior ones, accelerating change while large organizations slow down due to processes, politics, and legacy structures.
Agents function as tireless digital interns with expert-level capabilities in narrow domains, amplifying the output of teams that already demonstrate initiative and creativity.
Many place AI on top of legacy processes or rely too heavily on public LLMs, resulting in misaligned outputs and “AI tourism” instead of measurable impact.
Clean enterprise data, secure deployment setups, and redesigned processes are essential to making agentic AI operational and strategically valuable.
Key takeaways:
Focus on real-value use cases: innovation begins with a business problem, not with experimenting for its own sake.
Prioritize structural readiness: clean data, redesigned workflows, and enterprise-grade AI infrastructure determine whether agentic systems deliver results.
Empower motivated teams: the highest return comes from equipping individuals who seek change with advanced tools that amplify their capacity, rather than attempting blanket adoption across the organization.

Leaders need to take disruption seriously, double down on strategic intelligence, empower the people who want change, and invest in data and platform foundations before scaling agents.

Is Agentic AI already disrupting businesses (or can we just not see it yet)?
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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