‘The combination of all this coming together—the in-memory database with real-time data sitting with AI agents which are actually embedded into the workflow—will make this one of the most fascinating opportunities in enterprises,’ Cognizant CEO Ravi Kumar S tells CRN.

Global IT services provider Cognizant Wednesday became the first strategic partner of ServiceNow to bring that vendor’s new Workflow Data Fabric technology to customers.

ServiceNow Tuesday introduced Workflow Data Fabric, which works with an enterprise’s structured, unstructured, semi-structured and streaming data, both within and outside the business, to scale and provide efficiency and power workflows and AI agents with real-time, secure access to data.

The move by Cognizant, ranked No. 8 on the CRN 2024 Solution Provider 500, to quickly adopt ServiceNow’s Workflow Data Fabric technology is the latest expansion of the long-term relationship between the two companies, said Cognizant CEO Ravi Kumar S.

[Related: ServiceNow CEO McDermott: ‘Taking On The World’s Biggest Challenges’ With AI, New Nvidia Pact, More]

Cognizant has had a deep relationship with ServiceNow starting with Cognizant’s 2021 acquisition of Linium, a major ServiceNow channel partner, Kumar told CRN. That relationship expanded significantly with Cognizant’s late 2023 move to acquire Thirdera, which at the time was ServiceNow’s largest global pure-play channel partner.

“We put all of that together, and we have now become one of the leading partners for ServiceNow over the years,” he said.

In the world of AI, ServiceNow plays a very important role, Kumar said.

“ServiceNow is a ‘platform of platforms,’ as I call it,” he said. “It creates digital workflows and digital feedback loops on enterprise landscapes. It creates ‘digital fluidity,’ as I call it, and digital feedback loops. Now, what’s happening in the world of AI with these workflows, digital feedback loops, and digital fluidity, is AI agents are sitting on that workflow, on that engine, and are making those workflows intelligent. They’re making those workflows generative in nature.”

One of the biggest use cases for AI is task automation and task productivity, which is the starting point before enterprises can change their processes and operating models, Kumar said. These intelligent AI agents are making these workflows very intelligent, he said.

“Workflow Data Fabric draws data from different sources at the workflow level,” he said. “It’s an in-memory database and makes the data more meaningful, more insightful, more usable for decision support. A combination of the core ServiceNow engine, the AI agents and the Workflow Data Fabric will make the agents real-time agents, and the orchestration layer will bring data from different sources, whether internal or external. And it will actually orchestrate it to the agents, which then makes those workflows AI-native.”

That is a glimpse of the future of AI, Kumar said.

“The combination of all this coming together—the in-memory database with real-time data sitting with AI agents which are actually embedded into the workflow—will make this one of the most fascinating opportunities in enterprises,” he said. “Therefore, we jumped into it and became the first partner to not only take Workflow Data Fabric to our clients but implement it internally.”

For Cognizant, AI in general has become a strategic focus, particularly after Kumar left rival Infosys to become Cognizant’s CEO in early 2023. The company later that year unveiled a plan to invest $1 billion in GenAI capabilities over three years.

“We believe ServiceNow is one of the most strategic software platforms on the planet,” he said. “And then when I came on board in January of 2023, I had the same philosophy. I worked with ServiceNow before. So I made a plan to step up the game. Very early on in my first few months, I met up with Bill [McDermott, ServiceNow CEO] and his leadership team and we did a joint press conference of putting up a billion-dollar plan. And now we’re taking another leap by becoming the first partner in the ground-breaking new Workflow Data Fabric.”

Cognizant’s Billion-Dollar AI plan

That billion-dollar AI plan is wide ranging, focused in large part on developing what Kumar called the “last-mile infrastructure” of AI.

“To take the raw power of the foundation models and make them enterprise-grade, you need last-mile infrastructure to make the output very reliable and very trustworthy, to make sure the performance of the systems is very efficient, and make it possible to govern it, manage the flow of AI programs, and make them responsible. And because the AI output comes from neurologic processes, you need the output to be reliable and less hallucinating. So we have built the last-mile infrastructure to take the power of generative AI to enterprise grade. Consumer-grade AI is much quicker, much faster. Enterprise grade AI is much harder.”

That investment includes such technologies as the Cognizant Neuro AI platform, aimed at helping businesses improve decision-making as a way to increase company performance and find new revenue opportunities, the January launch of its Bluebolt GenAI-powered virtual assistant, the February launch of Cognizant Flowsource to help engineering teams increase the speed and transparency of delivering high-quality code, and the March launch of Cognizant’s new Advanced AI Lab in San Francisco.

Cognizant’s AI investment broadly targets three areas, Kumar said. The first is the last-mile AI infrastructure.

The second is in productivity studies, Kumar said.

“We take the operations jobs of every enterprise and look at what it takes to make them productive using AI,” he said. “And we went bottom-up to do that exercise so that the impact can actually be measured and felt and that you can amplify the potential of employees with this technology.”

The third area is investment in AI training and capability building.