Strategies to integrating AI into existing systems

Talabat’s journey to integrate AI into its systems was filled with invaluable lessons,  marked by both challenges and revelations. From this experience, we distilled six key  learning points we think are essential for successful AI adoption. We hope that these  insights, derived from hands-on experiences and iterative refinements, can guide other  organisations on a similar path.

Key Takeaways

• Start from your strategy rather than the technology itself. Emerging thinking vs. Design  thinking in the case of integrating Gen AI in consumer products
• Measure it: On the importance of building a Measurement Foundation: Your  experimentation strategy is not only about the platform, it is also about clear ways of work  and processes
• Your AI integration requires building trust as well as a prior alignment with people and  their incentives. On designing the appropriate incentives and OKR structure to facilitate AI  integration and ensuring that models complement human creative decision-making  processes

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Bio

Walid Lassoued | Senior Director of Data Science | Talabat Delivery Hero | Dubai

Walid Lassoued is a seasoned data  science leader with vast tech industry  experience, having worked across Silicon  Valley, Europe, and the Middle East. He’s  held senior roles at renowned companies  like Talabat and Meta/Facebook, leading  data scientist and manager teams to craft  innovative data strategies. Walid is  passionate about growing data organizations to align with business  demands through innovation, top talent  recruitment, and strategic data and AI  implementations. A Stanford GSB  graduate, he excels at connecting complex  data insights with practical business  needs, producing significant results. As Talabat’s Director of Data Science and  Analytics, Walid oversees a 60+ team,  managing all product and business  analytics. At Meta/Facebook, he was a key  figure in expanding the Facebook  Marketplace ecommerce experience,  significantly boosting sales and shaping  FB’s commerce strategy through data  analytics. His work emphasized scientific  and data-informed decision-making,  leveraging experimentation and machine  learning to address critical analytical  challenges.