Speaker Interview with Ankit Mangal, Director, Global Supplier Tech at Wayfair

We were privileged to interview Ankit Mangal about his career journey, experience, and profound involvement in technology, particularly AI.

In his current role as the Director of Global Supplier Tech at Wayfair, Ankit Mangal brings a rich blend of expertise and insights to the convergence of technology and business. Throughout this interview, Ankit delves into his professional trajectory, underscoring his pivotal roles in data science and analytics across diverse industries. Moreover, he accentuates the monumental impact of AI in reshaping the future landscape.

Please elaborate on your background and relationship with tech, and how your journey lead you to your current role?

I lead the data science and analytics teams at Wayfair with teams located globally across US, Canada, Germany and India. We are a global tech company that helps customers shop for their homes online. In the past, I have led Machine Learning and Data Science teams in Financial Services (HSBC, Discover) and Healthcare industries, and used data to personalize marketing strategies, improve customer experience, mitigate risk, prevent fraud etc. So for the past decade plus, I have been focused on driving business value and tech innovation at scale using data, statistics, machine learning and now AI which is where my background helps me do my job at Wayfair.

Why do you believe generative AI and LLMs are crucial for enterprises in the realm of data-driven decision-making? Provide a concise explanation.

Gen AI and LLMs have really turbocharged a few fields already with the Human + AI augmentation model, and have the potential to fundamentally change how enterprises operate and innovate. GenAI offers the human-like ability to process data in the form of text, images, videos and tons of it in real time, which has made it crucial for enterprises who are looking to make data driven decisions. 

With more and more data collected (text, images, videos) to make decisions, generating intelligence on the go is a NEED to stay ahead of the competition and LLMs are fulfilling those with improved pre-trained models and hardware capabilities. A relevant example here is of customer service, many companies including Wayfair are augmenting sales and service agents with intelligence powered by Gen AI already leading to faster and better resolutions. When the agent is on the call with a customer, AI is summarizing key insights about the customer’s past interactions in the form of prior orders, calls, images of damaged products delivered, where they dropped off from the site etc. to quickly address the pain points with context and offer appropriate resolution. This is data driven decision making at every agent and customer interaction level, having a direct impact on customer satisfaction and company’s bottom line. 

What excites you about The AI Summit Singapore, and what can the audience expect from your session?

There are a lot of exciting sessions and panels at The AISummit covering many industries. I see a great balance of topics around business applications, ethics as we are innovating using AI and scaling AI solutions which are all important as we look for tangible sustainable AI solutions. We are going beyond the hype here! 

I am hosting a session on “E-commerce with AI: Revolutionising e-commerce through advanced digital analytics” which will cover different business problems at Wayfair that we solved using AI applications and the future outlook of AI in digital shopping. I am also part of a couple of panels around the Ethics and Safety aspects of implementing AI. We will discuss the importance of and ways to procure ethical solutions, staying compliant with data regulations and assessing societal impacts of AGI. In the past, we have gotten a lot of engagement on those topics in the US and UK, I look forward to the discussions in Singapore.

What recent breakthrough in the application of AI, either within your organization or in the broader AI landscape, excites you the most?

Image generation in real time has been exciting especially in the home category. Decorify is one example where Wayfair is leveraging GenAI to empower customers to reimagine their space in a different style, be it bohemian, mid-century modern, industrial, or more. Customers can then browse their favorite products right there and make confident purchase decisions. 

What are the biggest mistakes business leaders make about AI?

That's a great question, I am seeing a few common mistakes across the board. Firstly, I see many business leaders get excited about using AI solutions and ask their teams to pursue them without clear understanding of the problem they are trying to solve or how they will measure success of the initiative. Secondly, the underlying costs of implementation are often overlooked by leaders. In the MVP phase, its low and ROI makes sense but the cost curve is often not linear. Thirdly, the quality of data needed to make intelligent decisions, even by AI, is extremely critical and many times I see business leaders trying to avoid investment in basics and jump to a magic solution.

If you're interested in joining Ankit's session on "E-commerce with AI: Revolutionizing e-commerce through advanced digital analytics," secure your ticket now!