Ankit Agarwal's AI Leadership: Scaling Businesses & Future Tech Insights

The landscape of artificial intelligence is rapidly evolving, with a recent McKinsey report indicating that 78% of surveyed organizations now leverage AI in at least one business function, a significant jump from 55% in 2023. Yet, while many companies are still in the experimental phase of AI integration, a select group of visionaries has already harnessed this technology to fundamentally transform industries, generating substantial savings and serving hundreds of thousands of users daily.

Among these pioneers is Ankit Agarwal, an architect behind sophisticated AI systems that manage orders for global giants like McDonald’s and Starbucks, automate warehouse operations handling millions of Amazon packages, and have revolutionized the efficiency of over 450,000 restaurants, particularly during the challenging period for the hospitality sector. As a founding engineer of Voice AI at DoorDash and a former senior software engineer at Amazon, Agarwal has dedicated more than a decade to translating ambitious AI concepts into practical, real-world solutions that have generated billions in economic value. His journey raises critical questions: What does it truly take to build AI systems robust enough for global brands to entrust with their core operations? How does one scale a prototype into an enterprise-level deployment serving millions? And what common pitfalls do most companies encounter in AI implementation that prevent them from achieving transformative results?

In a recent interview, Agarwal offered an inside look at the strategies behind developing scalable AI solutions. He recounted invaluable lessons learned from leading teams of over 50 engineers on cutting-edge projects and elaborated on why the impending wave of AI adoption will be a decisive moment for small businesses, outlining steps leaders can take today to position themselves for success.

Agarwal observes that as AI adoption accelerates, its benefits become increasingly evident for both large enterprises and smaller businesses. AI-driven innovation, for instance, offers a broad spectrum of opportunities for optimizing complex processes, from meticulous warehouse inventory control to efficient handling of multiple orders. However, for AI integrations to be genuinely beneficial, businesses must adopt a deliberate and conscious approach. He emphasizes the necessity of thoroughly analyzing existing operational processes before implementing new technologies, ensuring that innovations are deeply integrated into business operations rather than remaining superficial additions. Consequently, investing in employee education and adaptation must go hand-in-hand with technological deployment.

Agarwal’s career path, which began at the Samsung Research Institute and led him to Amazon and DoorDash, has consistently involved integrating groundbreaking solutions into business workflows. He views every task, regardless of its scale, as an opportunity to master new technologies and acquire knowledge applicable to future projects. His early international exposure at Samsung, for example, taught him to thrive in cross-functional environments while adhering to industry standards—skills that proved invaluable at Amazon and DoorDash, where he tackled large-scale, high-impact initiatives. A recurring theme throughout his career has been the ability to identify critical pain points and then efficiently apply novel technologies to resolve them.

His work at DoorDash, a leading US food delivery company, exemplifies this problem-solving approach. There, he spearheaded the development of voice automation systems and ordering platforms, now utilized by several global brands. These innovations underscore AI’s profound impact on customer experience and operational efficiency. AI-based solutions, Agarwal notes, are uniquely positioned to address contemporary challenges faced by restaurants and food delivery services, such as labor shortages and increasing workloads. The AI-powered voice system, by automating voice orders and customer service, has significantly reduced staff workload and expedited service. Initially implemented for phone orders in 2023 and later expanded to drive-throughs in 2025, this pioneering solution was subsequently adopted by major food chains including Donatos and Chicken Express. This case study powerfully demonstrates that well-executed AI solutions create a win-win scenario, benefiting customers, businesses, and employees alike through reduced burdens and enhanced service quality.

Agarwal’s tenure at Amazon, the global retail behemoth processing millions of orders daily, further illustrates that automation extends far beyond order processing, integrating into diverse aspects of business operations from warehouse management to fraud detection. Unlike his customer-facing projects at DoorDash, his work for Amazon primarily focused on internal processes. These automation efforts involved both the installation of new hardware and sensors—such as cameras and scales for tracking—and the development of sophisticated software to process the newly acquired data. This information was then utilized for real-time warehouse management, predictive analytics, and optimizing logistics. The result was an immediate reduction in labor costs and minimized errors, providing essential resources that supported the massive e-commerce growth that followed in 2022 and beyond.

As a staff software engineer at DoorDash, Agarwal was instrumental in shaping efficient teams of dozens of engineers dedicated to creating innovative solutions. He advises aspiring tech leaders to prioritize collaboration, emphasizing that it is crucial for both innovation and achieving technical excellence. Regardless of team size, establishing an environment where individuals from diverse backgrounds feel comfortable voicing perspectives and sharing ideas is paramount. Furthermore, leaders should maintain connections across their organization, beyond immediate teams, to understand the potential impact of innovations on other workflows and proactively address any arising challenges. He cautions against “innovation for innovation’s sake,” urging leaders to instead research user pain points and focus intently on resolving them. For instance, understanding the specific challenges faced by small restaurants directly informed the creation of a platform that these businesses actively use today.

Looking ahead, Agarwal believes that as AI technology advances, it will become increasingly accessible for smaller businesses, particularly through cloud-based and low-code solutions. His work at DoorDash demonstrated how AI-driven tools like voice automation can empower smaller restaurants to effectively compete in a digital-first economy. His personal ambition is to further advance AI-driven restaurant automation, combining it with logistics and autonomous delivery innovations. His vision is to scale these platforms worldwide, making services more accessible for underserved communities and thereby driving both economic and social equity.