NTT Data sees GenAI as more than a solution to sell

NTT Data has invested US$3.5 billion annually in research and development into AI, particularly in GenAI, said its vice president of digital, Tal Nathan.

In April, the IT service provider entered a strategic collaboration agreement with OpenAI to drive innovation in GenAI. As part of this agreement, NTT Data will establish an OpenAI CoE (centre of excellence) to accelerate the development and deployment of new GenAI services powered by OpenAI APIs.

These services will be tailored to specific industries and business functions and will be introduced globally to deliver enhanced value to clients.

In an interview with ARN, Nathan said the provider has spent over two years and conducted 200 global proof-of-concepts across different industries and clients to demonstrate practical uses for GenAI.

Nathan said that operationalising AI is often the challenge, not the technology itself.

“We’re not a hammer looking for a nail, trying to figure out what problems to solve,” he said. “We’re in this unique position where we get to transform the capabilities of what the market requires today, leveraging these technologies.

With GenAI, NTT Data is in a “fortunate position” where product-market fit wasn’t something it was searching for, but rather “how to transform and accelerate what we’re doing with our clients today, and powering that with GenAI”.

Tal noted that clients were on a journey when it came to AI, with some “quite well progressed”, and already rolling out at-scale solutions for them.

“We began this journey almost two years ago,” he said. “We ran global proof-of-concepts to test the water around these capabilities with GenAI.

“Where we landed was really interesting. The challenge was [in] an organisation’s ability to operationalise and scale the technology or have the governance framework or the data quality to drive it.”

NTT Data came away with the understanding of “start small and build it up”. What that generally meant for the IT provider was to start the foundation with data quality and data governance to drive AI, explained Nathan.

“Once you have the foundations in place [with] the ability to accelerate and add additional use cases, it’s just an incremental effort thereafter,” he said.

Data and governance

For NTT Data, the underlying data infrastructure and governance to make it work was the real driver behind the success of GenAI adoption, Nathan noted.

This is where understanding customer needs and wants were important.

There are two types of customers, he continued. There’s one type that knows they need to do something with data and GenAI but just don’t know what.

“It’s really an industry-based, consultative approach, understanding what the use cases are they need to drive and accelerate,” he said. “We work backwards to understand the use case, then … the different data points and tools and processes that are required to do it.”

The other category of customer NTT Data works with is those that have data quality challenges and want the service provider to uplift its data platform to run use cases.

For example, a multinational beverage company wanted NTT Data to create a chatbot for all of their staff to be able to ask queries to the system around supply shipments, logistics and tracking.

“When we started engaging with that organisation, we probably spent 90 per cent of the effort not on the GenAI chatbot side of things, [but] on the data quality side,” he said.

“We realised they had data quality challenges [and] their ERP [enterprise resource planning] platforms weren’t communicating effectively with each other.

“We realised they didn’t have this golden record of a single view of customer [or] an order,” he said. “They also didn’t have that robust governance framework that allowed AI to operate on top of their system and make sure that data privacy and data security wasn’t impeded.

“What started as a GenAI use case turned into a data governance and data strategy.”

Nathan reiterated that implementing GenAI isn’t about the tool itself, but all the invisible infrastructure in the background

Complexity of cloud

Another key foundation to AI is the migration to cloud. However, there are organisations that are on the back foot with regards to adopting these technologies.

“From a cloud perspective it’s always a challenge and the anticipated budget of what it was thought to cost versus what it costs to run differs tremendously,” said Nathan.

He noted there were two lenses around financial operations (finOps). One of them is measuring and optimising utilisation effectively, “providing governance and checks and balances in place to make sure that you don’t run over unintentionally when you’re running workload”.

The other is cloud operations, which makes sure businesses are operating their cloud and leveraging automated capabilities to scale as required, explained Nathan.

NTT Data has also taken a holistic approach when it comes to cloud billing.

“We’ve also invested in enterprise architects and advisory consultants to operate and communicate at a business level,” Nathan said. “We can engage with the CFO and understand their needs and requirements.

“We also bring that back to the CIO, so that we’re connecting business and IT and making sure that we’ve got a unified strategy.”

According to Nathan, there have been cases where lines of business are leveraging software-as-a-service (SaaS) applications, often multiple versions of the same SaaS applications on different accounts.

“This leads to not getting the benefits of enterprise-wide licensing, as an example,” he said. “Or, they’re using capabilities that potentially impede security and don’t align with governance policies or data policies, which could have negative impacts.

“Unfortunately, business users aren’t as attuned as IT users with regards to security, governance and cost, so this is a major issue.”

At the same time, Nathan noted users feel like they’re being held back in terms of the pace of change that’s happening and they require that instant gratification.

“Bringing those two boards together and making sure that business and IT have a unified strategy from a business perspective, architecture perspective and cost perspective is critical,” he said. “GenAI can support that in terms of real-time monitoring of the environment, monitoring usage and understanding what the organisation is consuming.”

The next evolution

NTT Data is advancing in its AI technology services now that it has continually invested in R&D and use cases.

Recently, the IT service provider announced the launch of a comprehensive enterprise-grade Smart AI Agent Ecosystem with industry-specific solutions to help clients transform their business.

NTT Data also announced a patented plug-in solution that turns legacy bots into autonomous intelligent agents and an expanded key alliance network for providing best-fit solutions.

It has deployed smart AI agent instances in support of sophisticated processes and decision-making at clients. The company’s roadmap encompasses a continuous stream of agents to support more complex use cases from a range of industries as well as shared functions.

NTT Data CEO Abhijit explained that AI is causing a massive shift similar to the early days of the internet and reshaping work, problem solving and value creation.

According to Nathan, some organisations see AI as hype and continue with business as usual.

“That’s like saying in 1999, ‘We don’t need a website, we’re in the Yellow Pages’,” he said. “That’s not a sustainable strategy. Others believe they can do it all in-house but [GenAI] touches every facet of the business, from data governance and automation to integration and observability.

“It’s incredibly unlikely that one organisation has the full capability in-house to drive that transformation.”

The most successful companies are those who recognise the value of partnerships and proven governance frameworks.