Balaji Thadagam of Kandavel & Cox Automotive: How We Leveraged AI To Take Our Company To The Next Level
An Interview With Chad Silverstein
AI advancements have become very important for any business, and in our case, I do not see people getting replaced. Certainly, there are things that we find dull and time consuming, so AI helps us consolidate those tasks and empowers our team. Transformations are usually quite overwhelming; however, we use AI to help navigate that with more clarity.
In the ever-evolving and never-ending landscape of business, staying ahead of the curve is a prerequisite for success. Artificial Intelligence (AI) has gone from being a futuristic concept to a daily business tool that executives can’t ignore. In this interview series, we would like to talk with business leaders who’ve successfully integrated A.I. into their operations, transforming their companies in the process. I had the pleasure of interviewing Balaji Thadagam Kandavel.
Balaji Thadagam Kandavel is a Senior Software Engineer, having accrued more than 16 years of experience in various areas such as AI, Machine Learning, AWS, Java, Typescript, Python, SQL, Sagemaker and Kafka Streams. This extensive background has enabled Balaji to acquire a profound knowledge of Software Engineering, Cloud Computing and Machine Learning. In his tenure, Balaji has directed the development and implementation of key technical and Architectural programs for companies’ success. This makes him an accomplished professional in the field of Machine Learning Solutions and Distributed Systems Architecture.
Thank you so much for doing this with us! To set the stage, tell us briefly about your childhood and background.
I grew up in India, where I developed an early fascination for assembling and repairing computers. This passion became a small hustle with my friends that funded my pocket money. My father, a cashier at the State Bank of India, would often recount the tedious task of manually counting currency notes. Inspired by his challenges, I built a small, battery-powered counting machine to assist him. Though that did not work as expected, these formative experiences nurtured my love for building and problem-solving. This pushed me toward studying computer science in school and later pursuing a degree in Computer Science and Engineering.
Throughout my career, I’ve remained drawn to the development and engineering spaces, where the actual building and innovation occur. Today, that curiosity drives my work in designing AI solutions and using right technologies to solve complex problems.
What were the early challenges you faced in your career, and how did they shape your approach to leadership?
In the early stages of my professional career as an engineer, I functioned in an environment where deadlines were highly pressurizing and nearly impossible to meet. As a newcomer to the field, the pressure was exciting, however, when I was promoted to Engineering Lead, the responsibilities were too severe. I found myself becoming a constant worrier and this did not help in contributing and assisting my team in any way.
This has been a learning curve for me. I have understood the difference between solving problems and worrying over them. Worrying and stress do not do anything, but planning and giving it a thought does. It is from this moment that I started practicing a leadership style where I aimed to lead with composure. I focused on ensuring that actionable steps were taken, shifting the attention to actionable perspective. Today, I aspire to be a leader who helps the team to think differently by fostering a problem-solving environment. That, I believe, massively redefined my leadership approach.
We often learn the most from our mistakes. Can you share one mistake that turned out to be one of the most valuable lessons you’ve learned?
Early in my career, I took on too many tasks simultaneously, thinking I could handle everything without help. As a result, I became overwhelmed, and the quality of my work suffered a lot. This experience taught me the importance of prioritization and delegation. Now, I better understand my team and stick to strategies such as setting realistic timelines and clear communication, which helps me estimate the workflow state. To bring these strategies to life, I always encourage the team to have clear team agreements that outline roles, responsibilities, and expectations. This has helped in defining right goals and individual responsibility without many assumptions on the task ownership.
A.I. is a big leap for many businesses. When and what first sparked your interest in incorporating it into your operations?
As I have worked in retail-based businesses my entire career, the main issue that often arises in online stores is getting people to make purchases. Long ago, we had the same online store website for everyone. When Amazon introduced personalized shopping experiences and Netflix implemented personalized movie suggestions, it triggered a revolution of machine learning algorithms for demand forecasting, dynamic pricing, and inventory management. This was the moment that inspired me to dive into learning machine learning and data science.
AI can be a game-changer for individuals and their responsibilities. Can you share how you personally use AI and what are your go-to resources or tools?
I leverage AI in various ways for my day-to-day activities, especially for handling mundane, everyday tasks. Apart from regular LLMs, I use tools like Cursor and Replit for rapid software development and deployment. With these tools, tasks that previously took me two weeks to prototype, design, and develop now take less than two days. If you know what you need, you can bring a project to life in a day. AI also helps me identify research topics or subjects to focus on, and I use LLMs to engage in deep, thoughtful discussions. You can have extended conversations — lasting an hour or more — on a topic with these LLMs and truly enrich your knowledge.
On the flip side, what challenges or setbacks have you encountered while implementing A.I. into your company?
There are two key challenges, that I have faced when implementing AI.
The first challenge is ensuring the accuracy and predictability of results at the team level. While this remains a hurdle, it is likely a temporary setback as models continue to improve in their reasoning capabilities over time.
The second challenge involves handling critical company data, which cannot be shared with public LLMs due to confidentiality concerns. These models could inadvertently expose sensitive information, such as proprietary code that is the company’s intellectual property. To address this, we have developed internal LLMs, ensuring that all data stays securely within the organization and is not exposed to external systems.
Let’s dig into this further. Can you share the top 5 A.I. tools or different ways you’re integrating AI into your business? What specific functions do they serve and what kind of result have you seen so far? If you can, please share a story or example for each.
1 . Personalization is an important part of retail operations. At Manheim, part of Cox Automotive, we have made it to use machine learning for personalization. M LOGIC™ leverages advanced algorithms to match Manheim inventory with the right buyers, enabling dealers to discover and purchase the right vehicles faster than ever.
2 . Another example of AI application, beyond personalization, is with Cox CRM VinSolutions, where we offer Predictive Insights enriched by Generative AI (GenAI). This capability empowers Cox-owned marketplaces like Autotrader, Kelley Blue Book, and Dealer.com to identify buyers who are up to 8 times more likely to make a purchase, driving significant value for our clients.
3 . Retail360 delivers omnichannel car-buying and ownership experience. By automating many processes that dealers previously had to handle manually, Retail360 has transformed the car-buying and selling journey, enhancing efficiency and improving the overall dealer experience.
4 . Manheim also provides the Manheim Market Report (MMR), the gold standard in wholesale vehicle valuations. Using AI, MMR delivers precise, real-time valuations by considering factors such as mileage, condition, color, and location, ensuring accuracy and confidence in every transaction.
5 . Large Language Models (LLMs) have revolutionized software development within Cox Automotive. Developers now spend less time on repetitive tasks and more time innovating, allowing for the delivery of high-quality software.
There’s concern about A.I. taking over jobs. How do you balance A.I. tools with your human workforce and have you already replaced any positions using technology?
AI advancements have become very important for any business, and in our case, I do not see people getting replaced. Certainly, there are things that we find dull and time consuming, so AI helps us consolidate those tasks and empowers our team. Transformations are usually quite overwhelming; however, we use AI to help navigate that with more clarity.
Looking ahead, what’s on the horizon in the world of AI that people should know about? What do you see happening in the next 3–5 years? I would love to hear your best prediction.
I believe the future will see the rise of more specialized and personalized chat agents, each tailored for specific tasks and capable of handling them with remarkable efficiency. AI will revolutionize content creation, with movies and other media being entirely produced by generative AI tools, pushing the boundaries of creativity and innovation. While the definition of AGI may remain debatable, advancements in AI’s adaptability and reasoning will bring us significantly closer to realizing AGI in the coming years.
If you had to pick just one AI tool that you feel is essential, one that you haven’t mentioned yet, which would it be and why?
Google AI Studio and hugging face could be used to create a fascinating feature that enables text-to-3D model creation. It’s incredible to think that with LLMs, you can go beyond software development and venture into creating tangible hardware as well.
For the uninitiated, what advice would you give someone looking to integrate AI into their business and doesn’t know where to start?
You don’t need to dive into right away. Start small with a pilot project in a controlled area. Explain to the team that, It can handle repetitive tasks, freeing them up for more creative things. You will learn how to get exactly what you need from an AI tool when you communicate clearly and concisely. Identify a few tools that you think might work for your team and play with it. That will be good start.
Where can our readers follow you to learn more about leveraging A.I. in the business world?
You can follow me on my personal LinkedIn.
This was great. Thanks for taking time for us to learn more about you and your business. We wish you continued success!
About the Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead, advises Authority Magazine’s Thought Leader Incubator.
Balaji Thadagam of Kandavel & Cox Automotive: How We Leveraged AI To Take Our Company To The Next… was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.