Podcast Summary: "AI Rewrites the Retail Playbook"
Podcast: Thoughts on the Market (Morgan Stanley)
Date: December 5, 2025
Live from: Morgan Stanley's Global Consumer and Retail Conference, New York City
Panel:
- Host (A)
- Simeon Gutman, U.S. Hardlines, Broadlines and Food Retail Analyst (B)
- Megan Clapp, U.S. Food Producers and Leisure Analyst (C)
- Aruna Masinha, Global and U.S. Economics Team (D)
Episode Overview
This episode dissects the evolving role of artificial intelligence (AI) in reshaping consumer companies, drawing on fresh insights from Morgan Stanley analysts and live examples from leading retail and consumer packaged goods (CPG) brands. The discussion ranges from frameworks for assessing AI’s business impact, to real-world deployment across supply chains, marketing, and even emerging “agentic” commerce models. The experts spotlight both current applications and forecasted large-scale societal effects, especially regarding labor and productivity.
Key Discussion Points & Insights
1. Assessing AI Adoption in Retail
Speaker: Simeon Gutman
- Methodology:
- The team surveyed disclosures and communications from covered companies, using AI tools as part of the process.
- Developed a six-category framework for AI use cases:
- Personalization and refined search
- Customer acquisition
- Product innovation
- Labor productivity
- Supply chain and logistics
- Inventory management
- Ranking Approach:
- Companies ranked 1–10 on:
- Breadth (how widely deployed),
- Depth (quality of implementation),
- Proprietary initiatives (e.g., AI partnerships).
- Companies ranked 1–10 on:
- Notable Example:
- Walmart is cited as an AI leader:
- Integrated AI tools across the business
- Introduced GenAI (Generative AI) like “Sparky” shopping assistant
- Partnered with OpenAI for ChatGPT-powered search and checkout
- Employing computer vision for shelf monitoring, LLMs (large language models) for inventory, augmented reality for in-store shopping, and autonomous lifts
- Result: 25% increase in average shopper spend
[02:00]
- Walmart is cited as an AI leader:
- Quote:
- "Walmart has full scale AI deployment. ... It covers all the functional categories in our framework." – Simeon Gutman [02:00]
2. Real World Use Cases and Step Changes
Speaker: Simeon Gutman
- Marketing and Cataloging:
- AI enables quicker, more efficient product cataloging (images, info, assortment), relieving resource burden.
- Personalization:
- AI-driven product suggestions to consumers are expected to make a significant leap by 2026.
- Quote:
- "It sounds like we're on the cusp of a step change in personalization." – Simeon Gutman [03:40]
3. State of AI in Food and Staples
Speaker: Megan Clapp
- Early Adoption:
- Most companies are just standing up data infrastructure and running pilot projects.
- Food and staples have an advantage due to high-frequency consumption data.
- Opportunities:
- Top line: Marketing, innovation, R&D (early AI use cases visible)
- Cost savings: Supply chain efficiency, productivity gains (easier to quantify)
- Winners:
- Large companies (due to scale and resources) and nimble smaller firms.
- Quote:
- "The opportunity I think going ahead lies in ... scaling those pilots to become more impactful." – Megan Clapp [04:41]
4. Success Stories in Food, Staples, and Leisure
Speaker: Megan Clapp
- Hershey:
- Uses AI algorithms to reallocate ad spend by zip code based on real-time sales; more targeted, more efficient. [06:30]
- General Mills:
- Deployed “digital twins” for better forecasting.
- Boosted productivity savings structurally from 4% to 5% annually.
- "Seeing real tangible benefits that are showing up in the P and L." [07:05]
- Leisure / Direct-to-Consumer (DTC): SharkNinja
- Optimizing DTC websites for LLMs like ChatGPT and Gemini.
- CEO anticipates AI-driven commerce will be “meaningful” by Christmas next year (late 2026).
- OpenAI already experimenting with curated product transactions.
- Quote:
- “Brands will win, but you gotta get ahead of it.” – SharkNinja CEO, relayed by Megan Clapp [07:50]
5. Agentic Commerce: Expansion and Cannibalization Threats
Speaker: Simeon Gutman
- Agentic Commerce:
- AI agents could independently execute commerce (shopping, checkout, etc.), opening opportunities for incremental sales, but also risks eroding existing sales channels and retail media income.
- Protecting from Cannibalization:
- Framework focuses on five “I’s,” especially infrastructure and inventory.
- Retailers with strong inventory positions and robust supply chains are likely to remain preferred partners for AI agents.
- Framework focuses on five “I’s,” especially infrastructure and inventory.
- Retail Media Models Unsettled:
- Data control and transaction models are in flux; consumer trust in data sharing with AI agents is still developing.
- Long-term Winners:
- “Forward-positioned inventory is still going to win that agent's business.” – Simeon Gutman [10:23]
6. Macro Perspective: AI’s Impact on Growth and Labor
Speaker: Aruna Masinha
- Growth Forecast:
- Two key influences from AI for GDP growth:
- Investment (data centers, chips, infrastructure)
- Productivity (human capital enabled by AI)
- Expected to add 40–45 basis points to U.S. growth in 2026–27.
- 2026 GDP forecast: 1.8%
- 2027 GDP forecast: 2.0%
- Two key influences from AI for GDP growth:
- Labor Market Implications:
- Macro-level AI adoption is still “fairly low”—mid-teens percentage of companies use AI tools
- AI is, for now, a complement to labor; some demographic groups may be impacted more, but no large-scale disruption expected by 2026.
- Quote:
- "For now, we think it is going to be a complement to labor…" – Aruna Masinha [12:00]
Notable Quotes
-
“Walmart has full scale AI deployment… The list goes on and on, but it covers all the functional categories in our framework.”
— Simeon Gutman [02:00] -
“It sounds like we're on the cusp of a step change in personalization.”
— Simeon Gutman [03:40] -
“The opportunity I think going ahead lies in ... scaling those pilots to become more impactful.”
— Megan Clapp [04:41] -
“Brands will win, but you gotta get ahead of it.”
— SharkNinja CEO, as recounted by Megan Clapp [07:50] -
“For now, we think it is going to be a complement to labor...”
— Aruna Masinha [12:00]
Timestamps for Key Segments
| Timestamp | Segment | |-----------|-----------------------------------------------------------| | 00:02 | Episode introduction, panelist introductions | | 00:56 | Simeon outlines AI assessment framework | | 03:17 | Real world AI use cases in marketing, personalization | | 04:22 | Megan discusses AI adoption in food and staples | | 06:23 | Success stories: Hershey, General Mills, SharkNinja | | 08:31 | The rise of agentic commerce and retail cannibalization | | 10:51 | Macro impacts: labor market and productivity, GDP | | 13:07 | Closing remarks |
Episode Takeaways
- AI is rapidly evolving from pilot to scaled deployment in retail and CPG, with clear early wins in personalization, supply chain efficiency, and DTC commerce.
- Companies succeeding are those with data infrastructure, scale, or agility to act quickly.
- The “agentic” commerce model could reshape online shopping, though business models and data control issues remain unsettled.
- Macro impacts are beginning to show, but AI remains a productivity enhancer rather than a labor replacement—for now.
This summary captures the substance and spirit of the discussion, highlighting expert insights into how AI is currently transforming (and will soon redefine) consumer-facing industries.