Retail operates on tight margins, with many businesses managing EBIT margins of just 3-5% in strong markets. This means AI implementation must be strategic, addressing the most critical pain points first rather than adopting technology for its own sake. At the 2025 RLC Global Forum, panelists Adriano Araujo (President, APAC & MEA, Ocado Group), Bobby Rajendran (CEO, Tamimi Markets), and Abdel-Salam Bdeir (CEO, SACO), moderated by Catherine Brien (Partner & Managing Director, AlixPartners, United Kingdom), explored how AI is reshaping retail operations.
For grocery and e-commerce businesses, AI is optimizing supply chains, improving product selection, and driving operational efficiencies. For example, in online grocery, AI has reduced fulfillment labor time from 74 minutes to 15 minutes per order, and with robotic picking, this has been cut in half again.
Retailers must identify high-impact areas such as labor productivity, inventory optimization, and pricing strategies before investing in AI solutions. Without this focus, companies risk spreading resources too thin and failing to achieve meaningful returns.
Many companies struggle to move beyond the proof-of-concept stage when implementing AI. Executives often feel that their organizations lack the agility to adapt at scale, and data fragmentation is a major barrier. A critical lesson from AI pioneers is that data integrity is the foundation of AI success. Early mistakes in data collection, structuring, and integration can delay AI deployment and reduce its effectiveness.
Successful AI-driven companies have invested in:
- Integrated data ecosystems that enable seamless decision-making.
- Automated insights that allow managers to make faster, data-driven choices.
- Predictive analytics that optimize pricing, promotions, and inventory management.
Retailers that overcome these structural challenges can unlock AI’s full potential in improving customer engagement, operational efficiency, and profitability.
While AI enhances automation and decision-making, human intuition remains irreplaceable in key areas. A fully AI-driven retail model risks losing differentiation, as companies relying on external data sets and machine-led decision-making may end up looking the same.
The key is keeping humans in the loop:
- AI suggests trends, but human expertise refines product selection and assortment curation.
- AI analyzes customer behavior, but personal interactions still define loyalty and brand affinity.
- AI optimizes supply chains, but experience and intuition guide strategic business decisions.
Companies that combine AI insights with human judgment create a powerful competitive advantage, ensuring they remain customer-centric while benefiting from technological efficiencies.
AI and innovation only succeed in businesses that foster a culture of experimentation. Organizations that struggle with AI adoption often fear failure, which stifles progress. Retailers must embrace a “fail small, learn big” mindset, where small-scale AI trials provide quick wins before wider implementation. Additionally, AI adoption requires:
- Cross-functional collaboration between IT, marketing, and operations teams.
- Transparent communication on AI successes and failures.
- Training programs that equip employees with AI literacy to maximize its value.
Without a supportive innovation culture, even the most advanced AI solutions will fail to deliver meaningful transformation.
AI in retail is no longer an optional investment—it is a competitive necessity. However, success lies in strategic implementation, cultural readiness, and balancing AI with human expertise. Businesses that approach AI with clear objectives, structured data, and a culture of innovation will be best positioned to thrive in an increasingly digital marketplace.
Key Statistics
- 67% of CEOs report feeling more disrupted in 2025 than the previous year, showing the increasing urgency for innovation.
- 70% of retail executives are prioritizing AI investments in customer experience over cost-cutting, signaling a shift toward growth-focused AI strategies.
- 35% of executives cite internal skill gaps as a major barrier to AI implementation, highlighting the need for training and upskilling programs.
“Technology and AI are a must, but they are not the objective. The goal is to serve customers, optimize operations, and drive real value—AI is just the tool to get us there.”
– Abdel-Salam Bdeir
