What’s the BUZZ? — AI in Business
“What’s the BUZZ?” is a live format where leaders in the field of artificial intelligence, generative AI, agentic AI, and automation share their insights and experiences on how they have successfully turned technology hype into business outcomes.
Each episode features a different guest who shares their journey in implementing AI and automation in business. From overcoming challenges to seeing real results, our guests provide valuable insights and practical advice for those looking to leverage the power of AI, generative AI, agentic AI, and process automation.
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“What’s the BUZZ?” is hosted and produced by Andreas Welsch, top 10 AI advisor, thought leader, speaker, and author of the “AI Leadership Handbook”. He is the Founder & Chief AI Strategist at Intelligence Briefing, a boutique AI advisory firm.
What’s the BUZZ? — AI in Business
When AI Agents Order Faster Than You Can Ship (Stefano Osteria)
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Your customers' agents are starting to send requests that no person typed. At the same time, your own agents can order raw materials and chase demand faster than any planner. Orders can now be generated faster than your suppliers, your warehouse and your people can fulfil them. How do you keep demand and delivery in step when machines drive both?
In this episode of "What's the BUZZ?", host Andreas Welsch sits down with Stefano Osteria, Global Vertical Leader, Warehousing and Logistics at Belden, to work through what happens when AI agents create demand faster than operations can deliver it. Stefano focuses on the link between demand forecasts, inventory, suppliers and fulfilment in manufacturing and logistics.
Key insights from this conversation include:
- Consumer agents shift prices. B2B agents shift operations. Stefano expects agents that follow fixed rules to make demand easier for manufacturers to forecast. For standard products with no differentiation, he expects prices to converge, because an agent can always find the best one. The real change, he says, happens on the B2B side.
- Link the agent to the forecast, and inventory shrinks. Stefano describes connecting an agent that buys raw materials to the sales demand forecast, with clear governance. The payoffs are lower inventory, leaner manufacturing and faster reaction to demand changes. The caution is that reacting too fast to demand swings can put suppliers in danger or force you to keep backup suppliers.
- Governance decides whether the agent helps or hurts. Without it, Stefano warns, a hallucinated demand forecast can be passed to your suppliers as a hallucinated order. He mentions a Harvard Business Review article he read that advises treating an agent like an intern: basic actions first, more freedom as you learn to govern it.
- Systems have to talk before agents can act. Stefano says most plants run isolated systems built to turn the same input into the same output. At the software level, an API is not enough: you also need a data layer that stays consistent, or your execution system works on wrong data. At the machine level, different industrial protocols and variable definitions get in the way.
- Fulfilment is where the pressure lands. Stefano points to Amazon as the reason shoppers expect delivery in one or two business days, which puts service level agreements at the center of warehousing. Third-party logistics providers spread goods across many warehouses, so aligning the forecast with where goods ship lets you anticipate the shipment cycle. Andreas asks whether this comes down to a classic ABC analysis, and Stefano agrees, with more options to store goods in third-party warehouses.
- Automation fails when the outcome is unclear. Machine builders and integrators tell Stefano they must deliver projects without clear outcomes. His advice is to break a big problem into steps, find where you lose the most time, and hand that specific outcome to an automation vendor.
What leaders can do now: start small with agent governance and widen it as the tasks grow more complex; connect your software and machines so agents work on consistent, real-time data; and define one clear, specific outcome before you invest in automation.
Stefano's line to write down: "It all goes back to what kind of governance do you implement into this agent."
If your customers' agents doubled their orders next month, which part of your chain would break first?
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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