(US & Canada) VIDEO | AI Is Not a Single Capability — Franklin Templeton Head of AI and Digital Transformation

Deep Ratna Srivastav, SVP, Head of AI and Digital Transformation at Franklin Templeton, speaks about his role, AI as an enabler, and the impact and usage of AI to transform business.

Deep Ratna Srivastav, SVP, Head of AI and Digital Transformation at Franklin Templeton, speaks with Nazar Labunets, Product Marketing Manager at Ataccama, in a video interview about his role, AI as an enabler, and impact and usage of AI to transform business.

Franklin Templeton is a global leader in asset management with more than seven decades of experience.

As the Head of AI, Srivastav’s role operates in three key dimensions:

  1. Creating demand

  2. Delivering on the promise

  3. Driving the adoption

Regarding demand creation, Srivastav affirms working with business leaders and teams to create the vision of the potential of AI, for the long and short term. In addition, it is about understanding the wins and applying them.

Then, delivering on that promise requires internal and external collaboration with providers, tech companies, and SMEs, he adds. Further, driving the adoption includes bringing in capabilities and transforming the business operations.

Commenting further on creating demand, Srivastav states that it depends internally on leveraging various capabilities like AI and digital to create and scale. Serving clients effectively also creates demand, he adds.

Delving more on the client side, Srivastav shares how AI facilitates the creation of new products, new value propositions, and new market capabilities. On the other side, it also deals with clients and external partners.

The AI strategy, he says, involves transforming the enterprise and ecosystem and businesses need constant gains to invest more, says Srivastav. He stresses that AI is not a single capability but a lot of capabilities blended together.

Therefore, organizations must effectively try and create an intelligence that represents the organizational value proposition. That is where the systems need training to be able to comprehend what adds value, to create and sell better products.

When asked about AI opportunities for value creation, Srivastav shares about his organization. Being in the investment and wealth management space, the focus is to create investment products, take them to clients, and provide the right advice.

Every step of that requires data and making the right decisions based on structured data and years of intelligence, wisdom, and acquired knowledge in investing, says Srivastav. The AI opportunity lies in bringing all the data elements together and providing personalized support to meet the needs of clients and investors.

Moving forward, he asserts that people think of AI in terms of artificial general intelligence, which in reality is a distant dream. In reality, AI is great at narrow tasks, if it is trained on each decision, be it investment, providing advice, or running day-to-day operations.

Srivastav notes that it is a series of bots that work well individually, but the magic happens when they are connected. From a potential perspective, the AI shift is not marginal, rather it will bring a significant change in enterprise value propositions, he says.

Highlighting the organizational usage of AI, Srivastav mentions building a “goals optimization engine” that creates personalized financial advice for advisors based on client needs. While such products have been available in the market in the form of standard packaged products, AI allows customization.

AI enables understanding the client and ensures that the portfolio stays in lockstep with the changing client needs throughout the lifecycle, says Srivastav. He states that massive research had to be done in this space to be able to create that shift and that requires AI and digital as the constant source of interaction.

The other part involves supporting the clients in the right way by providing the right information. Further, Srivastav mentions developing models to identify capabilities and the kind of support a client expects.

In conclusion, he states that a lot remains to be done, especially with generative AI in the picture, as it enables connections across different data sets. Also, the organization continues to improve internal efficacy and scale of decision-making.

CDO Magazine appreciates Deep Ratna Srivastav for sharing his AI insights with our global community.

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