As businesses increasingly turn to AI and machine learning (ML) to enhance their operations, the challenge of scaling these technologies has become more apparent. A study by MIT Sloan reveals that while 85% of organizations acknowledge the importance of AI, only 20% have successfully implemented it at scale. Companies often face insurmountable hurdles in integrating ML models into broader business functions due to technical complexities, prohibitive costs, and a critical shortage of skilled professionals.
In this landscape, Timofey Popov emerges as a trendsetting professional. He has established himself as a distinguished Product Manager and CX Awards jury member, driving transformative changes at global giants like McDonald's and SberMarket. One of his notable achievements has been at Avito, one of the world's largest classified platforms, where his innovative approaches have not only set industry benchmarks but fundamentally revolutionized how businesses approach AI scaling.
Timofey, scaling AI across large organizations is complex, yet your contribution at Avito increased ad revenue by over 30% through machine learning models. How did you address the leadership challenges involved?
The challenge at Avito wasn't just about implementing AI—it was about solving a fundamental business problem that had plagued the industry for years. As the world's largest classified platform, we faced a critical issue: how to effectively monetize our vast inventory while maintaining user experience quality. This wasn't just a technical challenge; it was a complex business problem that required unprecedented solutions.
What made my role crucial was the ability to bridge the gap between cutting-edge technology and tangible business outcomes. I introduced a novel approach that transformed how we handle promotion services, which represent a vital revenue stream for Avito. By implementing advanced transformer models and deep learning architectures, we didn't just improve ad delivery—we revolutionized it. These models analyze platform events in real time, predicting optimal ad placements with exceptional accuracy, something that had never been achieved at this scale before.
How does the implementation of innovations, including deep learning methods, impact the system as a whole? Corporate systems are complex and multi-layered—sometimes, improvements in one area can lead to negative effects in another. How do you ensure the overall health of the system?
This question touches on one of the most critical challenges in AI implementation. At Avito, we faced a complex balancing act: maximizing revenue while preserving the quality of buyer experience (BX) metrics. The conventional approach of training models to maximize revenue often leads to short-term gains but long-term platform degradation.
I introduced a paradigm shift in how we approach this challenge. Instead of treating revenue and user experience as competing priorities, I developed a holistic framework that integrates both objectives. This required not just technical expertise but also strategic vision to align various stakeholders—from data scientists to business leaders.
"Making Avito better for buyers" is our core principle. I consistently emphasized that our task wasn't just about short-term revenue uplift generation with further stagnation but about preserving and enhancing the buyer experience. This balanced approach has become a model for how large platforms can scale AI while maintaining system health and ensuring stable long-term revenue.
The deep learning models you've implemented at Avito have set industry standards, particularly in recommendation systems. Can you share how this has transformed your work?
What sets our approach apart is its unprecedented scope and effectiveness. Previously, promotion services were a critical focus area, but their optimization was largely manual, requiring extensive human intervention from product managers, analysts, and business experts.
I recognized this as a critical bottleneck and developed an innovative solution using advanced deep learning methods. A new approach revolutionized how we handle recommendations, including similar items and complementary offers. The uniqueness lies in our ability to seamlessly combine relevant promoted offers into user journeys while maintaining engagement quality.
This breakthrough wasn't just about implementing existing solutions—I created entirely new methodologies that have since been adopted as industry standards. The fact that other corporations are now adopting similar approaches validates not just the effectiveness of our solution but its revolutionary nature in the industry.
Many businesses struggle to scale AI. You've focused on scalability from the outset, managing to decrease scaling costs through AI optimizations. What advice would you give to leaders facing integration challenges?
Based on my experience leading complex AI initiatives, I've developed a structured framework that transforms how organizations approach AI integration. This framework addresses the critical gaps that cause many businesses to fail in their AI scaling efforts.
The framework consists of five essential components: defining clear objectives, leveraging expertise, assessing organizational readiness, setting realistic timelines, and proactively managing risks. What makes this approach unique is its focus on practical implementation rather than theoretical ideals.
At Avito, this framework enabled us to achieve something remarkable: decreasing scaling costs while simultaneously improving AI performance. This achievement has made our approach a blueprint for other organizations facing similar challenges.
You've spoken about AI's role in decision-making. With the success you've seen in real-time insights and operational improvements, how do you see AI transforming leadership in the future?
The future of AI in leadership is transformative. Through my experience at Avito, I've seen how AI can revolutionize decision-making at all levels. Machine learning models now provide real-time insights, enabling quicker and more informed decisions. Leaders no longer need to wait for periodic reports—AI offers a continuous flow of insights for instantaneous course corrections.
In the boardroom, AI serves as a trusted advisor, offering data-driven forecasts and recommended actions. However, my approach has always emphasized that while AI provides data and predictions, it complements rather than replaces human intuition and experience.
Looking ahead, what future AI projects or goals excite you the most?
I'm focused on pushing the boundaries of what's possible with AI, particularly in real-time decision-making across various industries. My vision extends beyond traditional applications to transformative solutions in sectors like healthcare and logistics, where AI's potential remains largely untapped. The optimization strategies we pioneered at Avito have inspired similar approaches across the industry, demonstrating the far-reaching impact of our innovations.
My goal is to continue leading transformative AI initiatives while mentoring the next generation of AI leaders. This combination of innovation and leadership development is crucial for advancing the field and ensuring sustainable growth in AI implementation.
Conclusion
Through his exceptional leadership and innovative approaches, Timofey Popov has not only transformed the companies he's worked with but has also set new standards for AI implementation in the industry. His unique ability to solve complex business challenges through cutting-edge technology, combined with his strategic vision for scaling AI solutions, makes him an invaluable asset in the rapidly evolving landscape of digital transformation.
