Eva Ponce

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.

The recap reports two audience polls: 482 responses ranked critical thinking highest among skills for future supply chain professionals, at 75%, ahead of technology and AI literacy at 57%; 538 responses put current AI use mainly in general productivity (67%) and data analysis and decision support (60%).

• Eva Ponce also urges professionals to become "learning machines," an idea attributed to Amazon CEO Andy Jassy.
• A later reflective post with the same guest asks where humans remain in the loop as AI becomes more embedded in work.

The invitation post frames agentic AI as an industry shifting "faster than ever" toward autonomous systems. The recap tempers that framing: foundations and problem definition still determine whether the technology helps.

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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.

The webinar put that stance into practice: Eva Ponce hosted Vijay Sankararaman, Chief AI Officer at Novant Health and a former technology leader at Lowe's and Walmart, and advertised cases in forecasting, inventory management, and procurement rather than a technology tour. Almost 900 people attended live, according to the recap.

The promotion post hints at a problem-first stance by promising to go beyond talk about the technology. The recap states it outright as a takeaway, suggesting the audience discussion reinforced rather than softened the position.

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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.

The seminar was an interactive experience credited to an invitation from Dimitris Bertsimas and hosted by Alex Shvonski, designed to make a listener see the decision differently after returning an item. For a buyer evaluating a speaking engagement, ask for details on the seminar's content: Eva Ponce's posts do not describe it.

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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.

The National Online Learning Day post is the clearest example: it credits thousands of learners who invested time and effort to advance their careers and tags the program's MIT homes — MIT Center for Transportation & Logistics and MIT Open Learning — which recur across the webinar posts.

Across posts, the emphasis moves from announcing a session to reporting on it, then reflecting on the program's longer arc. That is where the community framing is strongest.

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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.

The follow-up post briefly reflects on a conversation with Vijay Sankararaman about AI reshaping the workforce and the evolving role of humans as AI becomes more embedded in work. It revisits the guest relationship established in the webinar and points readers to the fuller discussion.

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This post invites readers to an MITx MicroMasters Program in Supply Chain Management webinar with Vijay Sankararaman, Chief AI Officer at Novant Health and a former technology leader at Lowe's and Walmart.

• Eva Ponce says the session will move beyond technology talk to real-world case studies in forecasting, inventory management, and procurement, and discuss how supply chain roles and skills are changing.
• The stated event date is September 10, 2026, at 14:00 UTC.

For brands planning a campaign

A supply chain education company can point to Eva Ponce hosting and framing webinars on the shift from analytics to agentic AI, with a named industry guest and concrete supply chain functions. Ask for a teaching sample to assess delivery; this post is an invitation, not a transcript.

In this recap of the MITx MicroMasters webinar with Vijay Sankararaman, Eva Ponce highlights two takeaways: supply chain foundations such as analytics, forecasting, optimization, and fundamentals still matter because AI builds on them; and teams should start with the business problem rather than the technology.

• The post also reports poll responses from 482 people on critical future skills: critical thinking at 75%, creativity and problem-solving at 65%, technology and AI literacy at 57%, analytical skills at 55%, and adaptability at 49%.
• A second poll of 538 responses found the top current AI uses were general productivity tasks at 67% and data analysis and decision support at 60%.
• The post mentions almost 900 live attendees.

For brands planning a campaign

This offers specific talking points and audience-interest signals for an analytics-to-agentic AI program, especially the problem-first framing and the gap between future skill priorities and current AI use. The poll reflects a webinar audience; ask for representative market research before treating it as a wider market signal.

Eva Ponce describes an MIT Learn Open Seminar called Free Returns Are Not Free, which explores what happens after a customer clicks return.

• The post says the project makes hidden operational, financial, and environmental trade-offs more visible, treats returns as an optimization problem, and considers how technology and AI can reduce unnecessary returns while improving customer experience.
• It credits Dimitris Bertsimas for the invitation and Alex Shvonski for hosting.

For brands planning a campaign

Ponce's hosted learning experience makes reverse logistics and AI-assisted returns reduction accessible.

• It supports a campaign angle around returns, reverse logistics, or consumer-facing supply chain education.
• The actual seminar experience is not shown in the posts here.

In a National Online Learning Day post, Eva Ponce celebrates the global community around the MITx MicroMasters Program in Supply Chain Management. They describe the program as starting as an experiment in making graduate-level supply chain education accessible worldwide and say it has grown into a large learning community, with thousands of people investing time and energy to learn and advance their careers.

For brands planning a campaign

Useful for a supply chain education company seeking a partner who can speak about global online learning communities and accessible graduate-level education. The webinar and seminar posts offer stronger evidence of technical AI content.

Eva Ponce reflects on a recent webinar conversation with Vijay Sankararaman about how AI is transforming the workforce and where humans remain in the loop. They call it an insightful conversation on the evolving role of humans as AI becomes more embedded in work and invite readers to share their thoughts in the comments.

For brands planning a campaign

This supports a webinar or course segment on human-in-the-loop decision-making and workforce change. Because it is a brief reflective post, use it as a signpost to the fuller webinar discussion, not as standalone analysis.

In the September 10, 2026 MITx MicroMasters in Supply Chain Management webinar, "From Supply Chain Analytics to Agentic AI," they spoke with Vijay Sankararaman, Chief AI Officer at Novant Health and a former technology leader at Lowe's and Walmart.

• The discussion used case studies in forecasting, inventory management, and procurement rather than staying abstract.
• Ponce's recap reports almost 900 live attendees and poll results: of 482 responses on skills, 75% put critical thinking first; of 538 responses on current AI use, 67% cited general productivity and 60% data analysis and decision support.
• Their two takeaways: analytics, forecasting, optimization, and supply chain fundamentals still matter, and teams should start with the business problem rather than asking where the technology can be applied.

A discussion built around a named practitioner guest, applied cases in forecasting, inventory, and procurement, and live audience polls that turn a webinar into usable benchmark data.

For brands planning a campaign

For a webinar or course on analytics-to-agentic AI, the tested format is clear: a practitioner guest, concrete cases, and polling that yields shareable findings. A brand should expect Ponce to steer the content toward decision-making and foundations rather than model hype, so the session should name the business problem it addresses.

Examples: Source 1 · Source 2 · Source 3

Their post describes the hidden operational, financial, and environmental trade-offs and frames returns reduction as an optimization problem, considering technology and AI as ways to cut unnecessary returns while improving the customer experience. They credit Dimitris Bertsimas for the invitation and Alex Shvonski for hosting, and say the goal was to make a complex supply chain challenge relatable to a broad audience.

Translating a technical supply chain problem into an interactive learning experience for a general audience, not only practitioners.

For brands planning a campaign

For a reverse-logistics, returns-reduction, or sustainability brief, Ponce has shown they can make an operational topic accessible without losing the underlying trade-offs. The approach suits consumer-facing and executive-awareness content, with a narrative that starts from an everyday action and works backward into operations.

Examples: Source 1

Marking National Online Learning Day, they describe 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 focus on the people behind the enrollment numbers, not just the numbers.
• The same program identity frames their webinar promotion and recap posts, tagged to MIT Center for Transportation & Logistics, MIT Open Learning, and related MIT units.

For brands planning a campaign

For a company selling programs, cohorts, or learning products, Ponce's angle is community and access, not prestige alone. Co-marketing around a cohort launch, open enrollment period, or learner milestone fits how they already frame this work.

Examples: Source 1 · Source 2 · Source 3

The webinar recap reports audience rankings of future-critical skills: critical thinking at 75%, creativity and problem-solving at 65%, technology and AI literacy at 57%, analytical skills at 55%, and adaptability at 49%.

• Their closing takeaway urges professionals to become "learning machines," an idea they attribute to Andy Jassy.
• A later post asks how AI is transforming the workforce and where humans stay in the loop.

For brands planning a campaign

For learning-and-development or skills-positioning content, Ponce brings survey-style audience data and a workforce-readiness argument tested with a large live audience.

• A brand can use this in a skills-gap or upskilling campaign.
• The poll figures come from one webinar; ask for independent labor-market research if that evidence is needed.

Examples: Source 1 · Source 2

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Hammond's post on IBM's Bangalore Studio Ambassador program walks designers through career growth, a product development lifecycle framework, epics and requirements, and playbacks across products including supply chain and sustainability. Ponce frames the shift from analytics to agentic AI as a sequence of decisions, with fundamentals first.

Hammond focuses on design leadership and product experience in enterprise software for an audience of designers. Ponce focuses on supply chain analytics, optimization, and AI, delivering academic webinars and open seminars for supply chain professionals and general learners.

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Jasso recounts a customer meeting where transportation barely came up because growth and demand mattered more—a problem-first stance Ponce also shares as a webinar takeaway. Both teach through first-person narratives and specific scenes rather than abstract advice.

Jasso focuses on sales and customer conversations in transportation, with lessons on prospecting and business development. Ponce focuses on analytics, AI, and formal education, addressing learners and supply chain practitioners rather than sellers.

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Marintsch describes a stockout response optimization engine built with a mixed-integer linear program and connects it to agentic business process automation. Ponce explores the same analytics-to-agentic direction with their webinar guest.

Marintsch shares his graduate research and the technical modeling behind a tool, writing for people who want to understand the method. Ponce runs education programs and webinars, framing the field for a broad audience by describing the work rather than presenting their own model.

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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.

Choosing Chris Hammond over Eva Ponce means giving up the specific analytics-to-agentic AI transition, the MITx MicroMasters webinar format, and evidence of a large live education audience.

• Their posts do not show teaching webinars on AI, forecasting, inventory, or procurement, or developing a supply chain analytics curriculum.
• The education company would gain an enterprise design and leadership perspective, but would need to provide the AI and supply chain analytics subject matter.
• Ask for evidence of relevant teaching experience before choosing them for that content.

Examples: Source 1 · Source 2

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.

Choosing Anthony Jasso over Eva Ponce trades away the analytics-to-agentic AI topic, the MITx MicroMasters platform, and Eva Ponce's posts showing nearly 900 live attendees with poll participation.

• Eva Ponce's posts do not cover predictive analytics, machine learning, generative AI, agentic AI, or supply chain education program delivery.
• The education company would gain a field-tested transportation sales and customer-discovery perspective, but would need another instructor for the technical AI and analytics transition content.

Examples: Source 1 · Source 2

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.

Choosing Scott Marintsch over Eva Ponce means giving up the established webinar host role, evidence of nearly 900 live attendees, and the broad analytics-to-agentic AI framing already packaged for an education audience.

• Their posts show deep technical work and a clear agentic automation direction, but not large-audience teaching or course delivery.
• The education company would gain a hands-on optimization and automation example, but should ask for evidence of teaching experience or pair them with an experienced instructor or host.

Examples: Source 1 · Source 2