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Retail and consumer goods companies are ramping up AI and analytics investment, particularly in predictive and generative tools, but constrained budgets, unclear strategies, talent gaps, and data integration issues continue to limit the impact of these technologies on core business operations.
Key Takeaways
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AI adoption is accelerating: Retailers and consumer goods firms are dedicating more IT budget and staff to AI and analytics, with strong near-term plans for analytic, predictive, and generative AI despite many still operating with relatively small analytics budgets.
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Use cases are broadening: Assortment planning leads AI applications, including inventory and category management, social media analytics, digital commerce, and emerging areas like digital shelf analytics, as companies seek more data-driven decision-making.
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Strategy and capability gaps persist: Difficulty integrating multiple data sources and a shortage of AI-savvy leaders are key barriers, prompting a focus on platform upgrades, data quality, and governance improvements.
