What’s the BUZZ? — AI in Business

AI adoption is often treated as a one-size-fits-all approach. But individual employees and users have individual needs and preferences that successful AI programs consider.

In the latest episode of "What's the BUZZ?", host Andreas Welsch sits down with Christina Fischer, principal AI consultant and founder of Human Pattern Works, to unpack why so many AI transformations quietly fail the people meant to carry them, and what an actually inclusive AI playbook looks like.

Here's what you'll walk away with:
1) The real reason most AI initiatives fail
Christina puts the number at around 70%, and by her account, the common thread isn't the technology. It's leaders running a business problem like a software rollout, skipping the work across process, culture, and compliance that decides whether any of it sticks.

2) Your edge cases are your early-warning system
The employee who needs clarity on objectives or flexibility in how they work is often the first to feel friction nobody else has noticed yet. Listen to them early, Christina argues, and you catch what's breaking before it costs you the rest of the team.

3) Trust beats surveillance, every time
Keystroke logging and return-to-office mandates measure the easy thing, not the valuable one. Christina expects the flexibility of the pandemic years to come back, because it's what lets companies keep the specialized people AI transformation actually depends on.

Actionable takeaways you can implement this week
- Score before you scale: run Christina's four-dimension audit,  process, work culture, compliance, technology, on your own team before you greenlight another AI pilot.
- Build one real feedback loop: swap a status update for an open conversation about what's actually working, and treat what you hear as signal, not noise.
- Check on your middle managers: ask the people absorbing pressure from both directions how they're doing, before they become your next regretted departure.

Who on your team is the canary in the coal mine right now, and are you actually listening to them?
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.

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Your next customer might not be a person. It might be an agent that searches, compares, and negotiates on someone else's behalf. So what happens to advertising, to pricing, and to trust when that becomes normal?
In this episode of "What's the BUZZ?", host Andreas Welsch sits down with Michael Carroll, Strategic Advisor and Fellow at LNS Research, to work through what actually changes when the customer is an AI agent. Michael spends his time on advisory boards and AI research, focused on what this technology should do for people, not only on what it can do.
Key insights from this conversation include:
The web was built for clicks. Agents are built for intent. Michael frames the shift as moving from a click-based architecture and economy to one organized around what you want. Today you do most of the orchestration yourself to get it. Reasoning at the edge flips that: the agent handles the orchestration, and the effort left to you is working out why you want what you want.
Ads do not disappear. They change target. Michael expects ads to keep running on TV and on your phone, but their job changes. Instead of persuading you to buy, they work to bias you into telling your agent what your preference is. The emotional pull advertising relies on does not land on an agent, so it gets aimed one step earlier, at you.
Intermediation will go autonomous. Mediation needs permission. Michael splits organizational work into intermediation, the moving and translating of information, and mediation, changing something from one state to another in a way that requires approval. The first is largely reversible and a strong candidate for autonomy. The second carries responsibility, and a machine never bears responsibility.
Causal reasoning is the trust architecture, not explainability. His verdict on the alternative is blunt: "Explainable AI is an abomination. It's an invitation to re-litigation." A causal chain of reasoning, he argues, is auditable and defensible, and it is not the same thing as deterministic.
Whoever closes the triad holds the influence. The reasoning agent at the edge, the platform you view the world through, and the architecture of trust. Close all three and you have something controllable, which raises the question of who is positioned to do it.
The collapse of distance points back at the individual. Michael cites Stanley Milgram's six degrees of separation from the 1960s and LinkedIn's own figure of roughly three today, and argues agents take it to one. His read is that this pulls people closer to everything rather than further apart.
What leaders can do now: make your business legible to agents and not only to people, with structure, schema, and clear answers to the questions an agent will ask on a buyer's behalf; sort your processes into intermediation and mediation, treating the first as candidates for autonomy and the second as needing a permission and audit trail before an agent goes near them; and work out, for a vendor agent and a customer agent transacting with each other, what each side is authorized to do, what information it is acting on, and whether it can be swayed.
Michael's line to write down: "If you can't trust it, it won't happen."
If your customer's agent evaluated you today, what would it find?
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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Most organizations are sprinkling agentic AI on top of a legacy, heterogeneous stack — and calling it a strategy. That works until the low-hanging fruit runs out, because it rests on a flawed assumption: that the business will keep operating exactly as it always has, only faster.
In this episode, host Andreas Welsch sits down with Grant Ecker, Chief Architect at Ecolab and founder of the Chief Architect Network — a 682-member nonprofit collaborative of Fortune 500 architecture executives. Drawing on architecture leadership roles at Danaher, Walgreens Boots Alliance, Medtronic, Lowe's, and General Mills, Grant lays out what it actually takes to make an enterprise architecture — and an architecture organization — ready for agentic AI.
Key insights from this conversation include:
Start with capability-based planning, not use cases. Decompose your strategy into the capabilities you have to be great at, map the gaps, and build a heat map of transformation opportunities. Some will be exciting (product innovation); some won't (order management). Both determine whether the strategy lands.
Earn the seat at the table through IT first. Architects get invited into strategy conversations because IT leadership trusts them — not in spite of it. Go to the business first and you risk undermining the partners who own that relationship, and losing the invitation entirely.
Move from T-shaped to pie-shaped. Technical depth alone no longer sustains an architecture career. Add a second point of depth in business understanding and communication, and become the connector and strategist for your part of the ecosystem.
Rethink "if it ain't broke, don't fix it." If something is fixed and sitting in the middle of a transformation, that's precisely the moment to challenge it — when a business outcome justifies the disruption. The prize is refactoring decisions so agents can make them with the right guardrails, governance, trust, and permissions.
Treat AI FinOps as a budgeting discipline, not an afterthought. Meter consumption by department, forecast token spend before the sticker shock arrives, and tie the next wave of investment to demonstrated ROI. Consumption is not a proxy for value.
Centralize, then federate. Pilot and learn centrally with safe off-the-shelf tools, then embed capabilities into the organization as maturity grows — the same curve cloud followed, and the one quantum will follow next.
Peer communities beat published best practice. By the time an approach is written up, it's six to nine months old. A trusted relationship with a peer in a non-competing industry is the fastest way to stay ahead of a market moving this quickly.
Whether you're a chief architect building the agentic reference architecture, a CIO deciding who holds the keys to AI adoption, or a technology leader working to be in the room where strategy gets set, this conversation offers a grounded view of the organizational work that makes agentic AI possible.

Tune in now to learn how to prepare your architecture — and your architects — for a shift Grant frames as an age-like change on par with the printing press and the internet.
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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AI agents are everywhere in the headlines, but successful agentic AI is about much more than deploying the latest technology. The organizations that succeed will be the ones that build the right foundation across data, culture, and strategy.
In this episode of “What’s the BUZZ?”, Andreas Welsch welcomes Sebastian Wernicke, author of Data Inspired, to explore what it takes to turn AI ambition into business outcomes.
You will learn why data alone is not enough, why organizations need to become data-inspired rather than simply data-driven, and how leaders can create the culture and strategy required for AI agents to deliver real impact:
The three critical success factors for agentic AI: data, culture, and strategy
How data-inspired organizations use information to drive innovation and competitive advantage
Why culture and technology conversations must happen together
How AI agents will reshape organizational decision-making
What leaders should do today to prepare their organizations for an AI-powered future
Whether you are exploring AI agents, building an AI strategy, or leading organizational change, this conversation provides practical guidance for moving beyond AI hype and creating meaningful 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:
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All episodes:
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When your AI agents start transacting on your behalf, who’s protecting your interests — and how do they prove it?

In this episode, host Andreas Welsch sits down with Nitin Badjatia, enterprise software veteran and board member of Customer Commons, to explore one of the most consequential and least-discussed gaps in agentic AI adoption: the absence of enforceable, machine-readable contracts between autonomous agents and the commercial web. Together, they unpack why the digital commerce infrastructure we’ve built on surveillance and click-through consent is fundamentally incompatible with a world where agents act, negotiate, and commit on our behalf — and what the emerging IEEE 7012 “My Terms” standard proposes to do about it.

Discover the strategic and governance foundations that responsible agentic commerce requires:

Recognize that consent is not a contract — and build your agentic governance accordingly. The terms of service paradigm grants vendors expansive rights users never meaningfully agreed to. As agents multiply, that exposure compounds. IEEE 7012 proposes human-readable, machine-executable contract templates as the foundation for agent-to-agent and agent-to-vendor interaction.
Model your digital interactions on physical-world norms. You wouldn’t share your financial strategy with an uncredentialed stranger, and you wouldn’t accept lifetime tracking as the price of entry at a grocery store. Yet that’s the standard your agents are operating within today. Bridging that gap is both an ethical imperative and a governance requirement.
Understand the five contract tiers the My Terms standard introduces — from simple transactional exchanges (no data retained beyond the transaction) to more complex arrangements — and identify which tier is appropriate for each agent interaction in your commercial stack.
Build toward a neutral, nonprofit contract infrastructure, analogous to how Creative Commons standardized licensing for creative works. The goal is a library of pre-negotiated, legally coherent templates that agents can carry into transactions — giving both parties a verifiable, auditable “legal receipt” for what was agreed.
Treat data quality as a governance outcome. A surveilled customer shares guarded context; a customer operating under a mutual contractual arrangement shares richer, more accurate data willingly. Organizations that adopt contract-first agentic models early will generate a higher-fidelity customer signal — not just reduced legal exposure.
Whether you’re a Chief Digital Officer designing your agentic commerce strategy, a privacy or legal leader trying to get ahead of regulatory exposure, or an AI architect determining what rights your deployed agents should carry, this episode reframes the agentic opportunity through the lens that matters most: who is actually accountable when the agent acts?

Tune in now to understand why the infrastructure of trust — not the sophistication of the model — will determine which organizations can scale agentic commerce with confidence.
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:
https://www.intelligence-briefing.com/podcast
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