The NeuralPod
The NeuralPod

Alberto Lumbreras - Defining the future of e-commerce with Agentic AI

04 November 2025 52:07 Chris Coyne

Listen to episode

About this episode

Future of AI in E-commerce and Ad Tech 

Join us for a discussion with Staff AI Researcher and Project Leader from Criteo, Alberto Lumbreras. We chatted about how Agentic AI will transform the AdTech and e-commerce experience. 

Alberto shares his unique career journey from telecommunications engineering to AI and machine learning, exploring his involvement in social network analysis and PhD studies. The conversation goes into the evolving landscape of AI in e-commerce, with a specific focus on shopping assistants and agent interfaces. Alberto also discusses the challenges in developing AI systems for commerce, the impact on the ad tech industry, and future predictions. Learn about his views on the importance of unique data, the advent of smaller, more efficient AI models, and how AI will become more autonomous and integrated into daily life.

00:00 Introduction and Welcome
01:02 Alberto's Career Journey
03:06 AI and Social Movements
03:53 Joining Criteo and Current Work
04:52 The Future of Shopping with AI Agents
08:25 Impact on Ad Tech Industry
10:48 Challenges and Opportunities in E-commerce
21:06 Data as a Competitive Moat
26:21 Challenges in Retail Catalogs for AI
27:15 Dynamic Data in Travel Industry
28:19 Importance of Comprehensive Data for AI
28:41 User Willingness to Share Data
29:07 Research, Engineering, and Talent Crossover
30:00 Essential Skills for ML Researchers
31:45 Impact of AI Tools on Engineering
32:46 Advice for Working with AI
38:19 Future Trends in AI Development
44:49 Research Directions and Influential Papers
48:18 Books That Shape AI Thinking
51:41 Conclusion and Farewell

Link to the first solo publication mentioned in the podcast: https://arxiv.org/pdf/2510.04871

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 The NeuralPod. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.