# Eva Ponce

Eva Ponce works on online supply chain education at MIT, including webinars and learning experiences about supply chain analytics, AI, and topics such as returns and reverse logistics.

- Profile: https://b2binfluencer.marketing/creators/eva-ponce/
- LinkedIn: https://www.linkedin.com/in/eva-ponce
- LinkedIn followers: 11,449
- Topics: artificial-intelligence, supply-chain, agentic-ai
- Based on 12 dated posts, latest 2026-10-06

## Summary

Eva Ponce is most useful for supply chain education webinars and courses on analytics, AI, and reverse logistics.

- Best for: A supply chain education company planning a webinar or course on analytics to agentic AI.
- Not for: A B2B agentic AI software vendor seeking product endorsement, implementation proof, or lead generation.
- Check first: Confirm audience makeup and request teaching materials or a sample before contracting.

### Takeaways

- Ponce says teams should start with the business problem, not the technology.
- A webinar recap reports almost 900 live attendees and poll responses on AI use.
- A returns seminar uses a familiar purchase return to show operational, financial, and environmental trade-offs.

## Main ideas

- **AI builds on supply chain fundamentals; it does not replace them**: In the recap of the September 10, 2026 MITx MicroMasters webinar "From Supply Chain Analytics to Agentic AI," Eva Ponce names two takeaways. First, a strong foundation in analytics, forecasting, optimization, and supply chain fundamentals remains essential: AI builds on those foundations rather than removing the need to understand the underlying problem. The shift from predictive analytics and machine learning to generative and agentic AI changes the tools applied to decisions, not the need for the analysis behind them.
- **Start with the business problem, not with the technology**: The second stated takeaway from the webinar recap is a question order: rather than asking where a new tool such as AI can be used, start with the business problem and ask what approach will help make a better decision. Supply chain teams should sequence their work problem first, method second, technology last. Eva Ponce also describes the session as applied rather than abstract, saying it covered real-world case studies in forecasting, inventory management, and procurement, alongside changes to supply chain roles and skills.
- **Make hidden operational complexity something a general audience can feel**: Eva Ponce describes an MIT Learn Open Seminar, "Free Returns Are Not Free," built around what happens after a customer clicks return. The post names the significant operational, financial, and environmental trade-offs behind that click and frames returns reduction as an optimization problem, with technology and AI considered as ways to cut unnecessary returns while improving the customer experience. The goal was to make a complex supply chain challenge relatable to a broad audience, not only practitioners.
- **Online supply chain education as a global community, not only a credential**: A parallel thread is the reach and community of MIT's online supply chain education. Marking National Online Learning Day, Eva Ponce describes the MITx MicroMasters Program in Supply Chain Management as an experiment in making graduate-level supply chain education accessible worldwide that grew into a large learning community. They point to the people behind the enrollment figures, not just the figures. The same program identity runs through the webinar promotion, recap, and follow-up posts.
- **AI's effect on jobs is an open question about human judgment**: Eva Ponce returns to how AI changes supply chain work and where people still belong in the process. The recap closes on continuous learning as a career requirement; a shorter follow-up post asks how AI is transforming the workforce and where humans stay in the loop, inviting readers to answer in the comments rather than asserting a conclusion.

## Work to read

- [Webinar invitation: From Supply Chain Analytics to Agentic AI](https://www.linkedin.com/posts/eva-ponce_supplychain-supplychainmanagement-supplychainanalytics-activity-7500660273389920256-8Bif)
- [Webinar recap: foundations, problem-first AI, and audience poll results](https://www.linkedin.com/posts/eva-ponce_supplychain-supplychainanalytics-ai-activity-7505646198368927747-QrvY)
- [Free Returns Are Not Free: making reverse logistics tangible](https://www.linkedin.com/posts/eva-ponce_free-returns-are-not-free-with-eva-ponce-activity-7513345059883257856-UKZg)
- [National Online Learning Day: MITx MicroMasters community](https://www.linkedin.com/posts/eva-ponce_onlinelearning-mitx-micromasters-activity-7505806952694829056-hGOv)
- [AI, workforce change, and humans in the loop](https://www.linkedin.com/posts/eva-ponce_onlinelearning-lifelonglearning-activity-7507071235604987904-99G6)

## Brand relationships

- **MITx MicroMasters Program in Supply Chain Management** (mention)
- **MIT Center for Transportation & Logistics** (mention)
- **MIT Open Learning** (mention)

## Partnerships

The posts show a repeatable collaboration pattern for Eva Ponce: MITx MicroMasters program webinars pairing them with an outside industry practitioner. Two promote a session with Vijay Sankararaman, described as Chief AI Officer at Novant Health and a former technology leader at Lowe's and Walmart, on the shift from supply chain analytics to agentic AI. A third recaps the session and reports audience poll results on skills and current AI use. A separate post points to an MIT Learn Open Seminar, Free Returns Are Not Free, and credits the invitation to Dimitris Bertsimas, with Alex Shvonski hosting. These are educational collaborations, not a published commercial offer. For a commercial role in a similar session, ask who controls registration, whether a sponsor can hold airtime or lead an agenda segment, what audience or lead data is shared, what production lead times apply, and whether any fee changes hands.

## Alternatives

- Chris Hammond: For a course on designing enterprise AI products or leading design teams in complex supply chain-adjacent software, Chris Hammond is the better choice if the education company narrows the course to that topic. Their posts describe direct work with IBM designers in the Bangalore software lab through a Studio Ambassador program covering career growth, product development lifecycle, epics and requirements, playbacks, and presenting. The domains named include enterprise asset and facility management, supply chain, and sustainability performance management. Another post draws leadership lessons from Trek Bicycle about building products teams love, making every job feel important, and running the play rather than the score. Those examples would suit a module on how enterprise software teams deliver supply chain and sustainability products.
- Anthony Jasso: For a course on transportation business development, consultative selling, or customer discovery rather than analytics-to-agentic AI, Anthony Jasso is the better choice if the education company reframes the course around that topic. Their posts describe transportation conversations that began with questions about growth, customer pressures, and what breaks if the business doubles. Another post describes prospecting by observing trailers, researching the business, and arriving with a business conversation instead of a cold call. Those examples could inform a course on how supply chain sellers earn attention and qualify opportunities.
- Scott Marintsch: For a course that needs a technical builder to show how optimization and agentic automation work in practice, Scott Marintsch is the better choice. Their posts describe graduate research on a Stockout Response Optimization Engine presented at the MIT Supply Chain Management Symposium, using a mixed-integer linear programming model in Python with Gurobi and a dashboard so planners can simulate recovery scenarios across a hub-and-spoke network. The model balances stockout penalties, early transfer costs, and trailer underutilization, prioritizes SKUs and customer locations by business impact, and is framed as a foundation for more agentic business process automation. They also describe their MIT master's work as bridging technology with best practices and avoiding the shiny-object or hammer-in-search-of-a-nail approach.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/