Leading AI Transformation: Stories from the field

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AI Transformation today is not just a buzzword. It is a tried and tested process that continues to evolve every day and has brought success in different areas and scales to enterprises worldwide, and enterprises today are listening. With investments in AI Transformation increasing daily, the demand for people and teams that can lead and execute a successful AI transformation strategy is at an all-time high. But what does it mean to lead an AI Transformation team? The answer to that begins with understanding what AI Transformation is – and what it isn’t.

What is AI Transformation? AI Transformation is the process of driving digital transformation through Artificial Intelligence. With AI Transformation, businesses can make processes more efficient, drive growth and deliver value to their customers. AI Transformation enables companies to scale AI across the business and achieve meaningful value from investments – an organization-wide change that integrates AI seamlessly into every part of the business and not just focuses on aspects of the business that need improvement.  

With AI Transformation gaining traction, how are leaders approaching it? How are they navigating through the obstacles? What is the present state of the market like, and where are we headed?

We host AI Transformation leaders at the biggest AI Transformation event, REBUILD, held across the globe. REBUILD is an experiential event that brings changemakers together, and we have gathered insights about leadership and AI Transformation from industry leaders across domains.

Here are the key takeaways from them on successfully leading an AI Transformation project.

In sync!

Syncing Brands

In the first edition of REBUILD, we heard the story of India’s first super app, Tata Neu, from Pratik Pal, CEO of Tata Digital, who took us through the entire journey from the inception of the idea to how the app was built. The 150-year-old conglomerate is one of the biggest brands in India across domains and is now gaining a stronger foothold in the digital world.

“At Tata, we have 150 million consumers across all consumer brands and 4800 touchpoints. We decided it was time to harness the power of it,” he said. “Tata Neu is an ecosystem first, super app second.”

One key quality observed in every AI transformation leader is the ability to look at the big picture. AI Transformation is a journey, not a task, and leaders always look to extract the best value they possibly can from the journey.

“All the brands form the ecosystem. We want to be able to deliver an omnichannel experience because no one does online-offline better in India,” Pratik continued, “wherever you shop, whatever you do, at any touchpoint, you can reap rewards.” The reward points on Tata Neu are brand agnostic – you could use the points you received while purchasing groceries to purchase your airline ticket within the app, or at their line of clothing stores.

“With Tata Neu, our goal is to harmonize the data from all our offerings in one place,” said Pratik, talking about the ultimate goal for Tata Neu. “We want to be the destination for every Indian consumer.”

Syncing Teams

Enough has been said about AI transformation – there’s a ton of information available. But how does this translate into action? What are things an AI transformation leader should know?

We hosted Daniel Gandara, VP of IT Product Development at MercadoLibre. He manages a team of 12,000 engineers spread across Latin America, dealing with 100 Million consumers spread across 30 countries. With so many diverse teams and products, how do they ensure there are no hassles to digital transformation?

“The culture should be about sharing your culture. Keep the DNA of transforming and encouraging an entrepreneurial mindset even when you’re part of a big company,” Daniel said.

“We have teams that are responsible for four pieces of the product. We go ahead and build the product and adapt it to the different countries and markets that the companies operate in – based on the regulations and data points specific to the country,” Daniel added. Here are some principles they follow:

• Build, and then adapt: The team at MercadoLibre builds centralized features, and then adapts the feature for each market based on the data analytics specific to it.
• Complete ownership: Teams get complete ownership at every stage of the development process, from design to production to operation, and the production environments are accessible to all – thereby ensuring that any outcome is managed.
  

One of the significant goals an AI Transformation leader can achieve is creating a cross-functional, collaborative process – not just the tech teams that are responsible, it is everyone involved.

Takeaway 1:
Synchronicity within organizations handling large amounts of data is essential

Transformative Technology, Transforming People

Building great technology is not the most important factor in your AI Transformation journey. While great tech is important, it is largely about building culture. It is about bringing teams and processes together in alignment with an AI-driven future.

“I’d like to give 100 billion-dollar advice to all young CTOs – get great people. Without people, there is no business,” said Sauvik Bannerjee, former Founding CTO of Tata Digital, at REBUILD Chennai. 

“So much of digital transformation is about people transformation and process transformation,” said Ashwini Asokan, CEO, and Co-founder, of Mad Street Den.

Venkat Raghavan, Associate Director & Global Head of Data at Tesco, spoke about how the 103-year-old global retailer uses an inside-out culture for digital and AI Transformation. ​​”At Tesco, our tagline is “Every little helps” – and that is our approach to digital transformation as well. Every little step towards better digital transformation and building it up over time gives us a competitive edge. It’s a culture of continuous improvement – both internally within the company and facing the customers,” he said.

The technology that is required to process and transform data is evolving every single day. But is just good technology enough? We spoke to Ahmad Musa, Head of Planning, Budgeting & MIS at Invest Bank P.S.C, who spoke about the early days of his journey and his own experience working with AI transformation.

“I learned the hard way on how to utilize data and technology. You could have state-of-the-art technology, deep pockets to spend, and the vision – even if you had clean & good data – but adaptation and change management was the issue. Not knowing what to do with the data is the problem.” Ahmad said, in conjecture with many others, about AI transformation being more than just a change in technology, but something that requires a change in mindset and process.

“For AI Transformation, It’s important that the culture and mindset is shifted towards data-driven organizations, because AI doesn’t function without data.” concurred Oan Ali, Chief Architect, Ahli United Bank.

This holds true across domains! Dr. Karthik Anantharaman concurred, saying, “Healthcare is now moving from B2B to Consumerism with a direct feedback loop, and that is receiving resistance. But we are pushing back and highlighting the importance of customer experience. Any service provider needs to make their consumer happy – it comes from people, process, and mindset change,” he said.

Takeaway 2:
Great data & technology is indeed great, but they could be rendered useless without the right mindset & processes. Fostering a data-driven culture is extremely important.

Decision making

Making the right decisions is a core tenet of building and running a successful business. With teams in sync and processes in place, how do leaders make the right decisions? What are the processes they undertake and the goals they set for themselves and their teams?

“The goal is not the technology – the goal is the business we’re trying to run,” said Daniel Gandara, on what drives his decision-making process. “Data is the starting point, but all the different dimensions above that matter,” he added. If your teams are in sync and they are aware of their goals, then it enables quicker decision-making with the required, appropriate direction. “We follow the 90-10 rule at Mercado Libre,” he said. What is the 90-10 rule?

The 90-10 rule: 90% of decisions taken by the managers are their own, without oversight. The remaining 10% is for decisions that aren’t easily reversible and are part of the bigger picture, enabling autonomy and quicker decision-making.

AI Transformation leaders create a bridge between AI Strategy and Business Strategy, tying them both together keeping all the factors involved in mind – ranging from reduction of cost to revenue growth to the organization’s AI Maturity. “Should we go from Data to Decision or from Decision to data? The latter works better – you work backward, and it gives you a clear picture of your goals and compares it with the data you have, therefore enabling you to fill in the gaps in data if any,” said Shailendra Singh, Chief Growth Officer at Fractal.ai. “It’s better to decide where you want to go first, and then look for the data you need for it. It makes the job a lot easier,” he added.

Takeaway 3:

• AI Transformation leaders need to have a birds-eye view of the business strategy to enable accurate and proper decision making
• Work backward – your goal determines your decisions

What is the future of AI Transformation?

With AI Transformation nearing the end of its nascent stage and heading towards widespread adoption, what do AI Transformation leaders think about where we’re headed and how companies can successfully implement an AI Transformation strategy?

“There will be a talent war in the next 5 years. There’s enough data & technology out there. You need people to ask for the right data. To find people to translate that into implementation & strategy and make sure it works is going to be hard.” said Timo Weis, on the nature of the job market and how it plays into the picture of digital transformation.

“I think there’s going to be a convergence – we have to get real. It doesn’t matter if you call yourself a data center or not – but can you work with the right tools, the right digital technology, and the right storytelling to make a real impact? That’s where I see the convergence happening.” said Venkat Raghavan.

Takeaway 4:
There is abundant data and technology, but that won’t cut it. You need the right combination of people, data, and technology to translate it into results and deliver impact. 

In Conclusion…

AI Transformation is a process that has technology at its core – but to execute a successful AI Transformation strategy, you need a combination of factors ranging from a transformation of culture and processes within your organization to the availability and transformation of data to derive results and a culmination of all these factors to successfully translate into a story that is woven together with the right technology, data, processes, and people.