AI in retail: priority shifts on ROI management and FinOps rigour

Featured image of the article AI in retail: priority shifts on ROI management and FinOps rigour

An article by Sophie Baqué

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Publication

29 April 2026 à 19h44

Updated on 4 May 2026 à 12h22

Reading time

11 minutes

Publication: 29 April 2026 à 19h44, Updated on 4 May 2026 à 12h22

Reading time: 11 minutes

While the technological barrier has collapsed for many transformation projects in the retail sector due to AI models, mind Retail has investigated FinOps challenges. What are the best practices and safeguards regarding costs of AI ? How can budget overruns be avoided when a solution is used by end consumers? Here is our summary, based on insights from Mathieu Staat (ThinkMarket), Camille Maire (Etam), Benoit Pinçon (Biovancia), Guilhem Bodin (Converteo), Marc Trilling (Saegus) and Shekar Krishnan (TCS).

An article by Sophie Baqué

Ajouter mind Retail à vos sources

Publication

29 April 2026 à 19h44

Updated on 4 May 2026 à 12h22

Reading time

11 minutes

Publication: 29 April 2026 à 19h44, Updated on 4 May 2026 à 12h22

Reading time: 11 minutes

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The context

After an industrialisation phase of AI generated content projects (text, meta descriptions, SEO, GEO, translations…), without real measurement of return on investment, the priority for 2026 is different. With retailers launching more complex AI projects involving video content generation (Decathlon), image search (Sézane), etc., “AI has become a major FinOps subject,” according to Marc Trilling, CEO of Saegus. “Our most advanced clients are doubling or tripling an AI budget this year

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Article authors

Featured image of the article Sophie Baqué

Sophie Baqué Chief Editor of mind Retail

Featured image of the article Sophie Baqué

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