You're listening to From the Horse's Mouth, Intrepid Conversations with Phil Fersht. Ready to meet the disruptors who are guiding us to the new great Utopia by reshaping our world and pushing past corporate spin for honest conversations about the future impact of current and emerging technologies. Tune in.
Now all right, well, I'm really pleased that we could have you both lend a little bit of your time for something much more fun, which is having a conversation about the future of workflows, digital fluidity, and how do we get beyond a lot of the hype that we've experienced over the last year or so. So maybe we'll start with you, Bill, and let's talk about ServiceNow's workflow data fabric and you're trying to bring AI into enterprise decisions. But what is this really meaning for the future?
The future work has really evolved from generative AI, which was making tasks done on a platform like ServiceNow easier, simpler, faster, to agentic AI where you're really capitalizing on gen AI but also putting these agents to work. I call this the digital workforce. They work 24/7, 365 days a year, and you don't even need to give them the health care plan. The vision is to have every employee in every company have agents work for them. I believe the claim to fame at ServiceNow is that not only do we act as the orchestration layer, the control tower for agentic AI in an enterprise because we have our own agents that go end to end across an entire company, but our control tower actually works with the other agents and all people in an enterprise that work in teams to get stuff done. So that's really a competitive advantage. I do want to give a shout out to Cognizant and Ravi in particular because the workflow data fabric and Cognizant were the first movers in adopting this in the marketplace because he saw how workflow would tie to data and with the fastest database, Raptor DB, and the ability to ingest as much data as an enterprise has, or leave the data structured and unstructured wherever it is in an enterprise, we could access it, make a zero copy of it, and accomplish a workflow or a process. This is really what is enabling companies to run much faster and much better with agentic AI. They're fast, and with workflow data fabric they can be fast with any data source in a company. Together that makes a very valuable combination to drive productivity, efficiency, and growth in companies today.
Right, right. So Ravi, you partnered with ServiceNow to promise digital fluidity, seamless connection across systems and teams. But how can organizations really achieve this? What cultural shifts are required? How can leaders break down resistance to drive these AI-driven transformations? What do you think needs to shift here?
Sure, Phil. So let me first define what digital fluidity is: the ability to move work across systems, across functions in an enterprise seamlessly without any constraints and barriers. I mean, you need a cultural shift inside the company which is more human-centric for you to get it, but there is a need of a technology which will allow you to do that. What does digital fluidity do? If you're able to move work seamlessly across an enterprise, you can make that enterprise real-time sentient, because you can do decision support in a real-time manner. Now imagine if there is data moving in the same flow and data is integrated from systems across the enterprise and it is moving along with work, and you're able to do intelligent decisions as the flow happens. Imagine if there are AI algorithms underneath it which are making the data generative in nature. Going back to what Bill said, if you want to take the output from it and actually actionize it with agents which are digital in nature, which work alongside humans, you're going to really find enterprises to be in a state where they can take decisions real time, they can predict what is coming, leave alone being an intelligent workflow. Now, ServiceNow, if you look at the stature of ServiceNow in an enterprise landscape, is probably the only unique software product available which actually orchestrates across an enterprise. It is a platform of platforms which sits on top of existing systems. So not only does it have agents on its own, it can actually integrate with agents of other systems which are available. So ServiceNow, being that system of experience and system of engagement, allows it to take that position of being that orchestration layer. So I'm very excited about the fact that not only are you able to agentize the output coming out of generative AI, you're embedding that into workflows and you are able to do day-to-day enterprise real-time decision making with the power of gen AI, with the power of identification, and with the power of in-memory data which is actually sitting in those workflows. It was almost a slam dunk opportunity for me to partner with ServiceNow and to bring the power of digital fluidity to enterprises. I mean, early on in my two years, I think this was one of the first strategic investments I made. Thereafter, we invested a billion dollars into ServiceNow infrastructure of Cognizant. Then we actually bought a company called Third Era, and now this is the next big thing we did: to bring the power of workflow, the power of agentic workflows, real-time data embedded into it for enterprises to be that sentient, real-time enterprise.
And you know, we talked a lot about service as software. Is this really about converting services into autonomous software? The last wave of technology was software as a service. The next wave of technology, or rather the current wave of technology, is service as autonomous software, or service as software. It is real. I'll give you an example. Imagine if you are implementing Salesforce software for any sales and marketing software for an enterprise. The total addressable spend for services companies like ours was the downstream services revenues to implement and to generate the outcomes the software is intended to do. So if you assume the market of sales and marketing enterprise software is say $200 billion, the underneath services was 2x, which is $400 billion. I mean, the plumbing is in the cloud; otherwise it used to be a 1 to 5 ratio. Right now it's 1 to 2. Now in the world of identification, my total addressable spend is no longer the service underneath the software; it is actually all the labor pools attached to that particular function. In this case, in my example, it's sales and marketing. So there are people punching in opportunities, people punching in forecasts, sales compensation, analytics. I can take all those labor pools and make them more productive using digital agents. So the total addressable spend is no longer the $400 billion of the $200 million of software; it is actually $2 trillion which is actually spent around the software function. I mean, around the sales and marketing function, I can go after example after example. If you take HR software, the ballpark size of that business is maybe $100 to $200 billion. The amount of money spent on all the human capital services attached to it is $2 trillion. Now with the power of platforms like ServiceNow, which really sit on top of all the enterprise software, I could identify all these labor pools and create significant impact and significant productivity. Productivity has been flat for the last 20 years in spite of all this software, all the enterprise technology which is in there. We have this unique opportunity to actually now translate operational spend into the addressable spend for companies like Cognizant and ServiceNow to come together. That's why I think it is the next big wave, which is service as a software.
Yeah, I mean it's fascinating, isn't it? So getting back to the big theme of the partnership, Bill, you know, workflow data fabric. There's a lot of noise around transforming data from an operational asset into a strategic powerhouse. So how can C-suite leaders leverage this to unlock competitive advantage and really make this a real driver of business strategy?
You have to take Ravi's remarks extremely inspirationally. Because this AI market that we're participating in is a $20 trillion market in terms of its impact in the next five years. That's pretty incredible. I've never participated in a market like it. I've also never participated in a market where for every $1 that's wisely invested, you'll get a minimum of $5 return. So I think that this orchestration, or this platform of platforms concept at the workflow level, has now been anchored pretty well. Because if you think about ServiceNow's role, it's almost like the iPhone of the enterprise. You have a clean pane of glass with enormous compute power and complexity underneath it, but that's hidden from the user. The user has a great experience, as Ravi beautifully said. I think now when we get into the workflow data fabric, the reason that I really admired Ravi's decision making and his swiftness in making decisions, and I think that's one of the big things about the AI world we're in now: leaders have to have courage, but they also have to have speed. Because a decision delayed today is a loss tomorrow. Ravi understands that as well as anyone I know.
And so the way I look at the data fabric, you take these AI agents and you put them to work. But think about the reality of the 20th century architectures that we work around every day. Cognizant and ServiceNow, you literally have companies with software that has been lying around for the last half century plus. And what's wild about this environment is most of the software is from pretty well-known brands, but these well-known brands might have hundreds of separate instances within a single company. Those instances might be some in the cloud, some on premise, but in most cases they're not well integrated from one geography or one use case to another. So the flow of work is basically done in silos or departments, and that's essentially where the data is trapped as well. You'll have data that's locked into silos of 20th century architectures. Some of that data will be structured, some unstructured, some on someone's desktop, some in a data vault, some trapped in archaic systems of record. Our job is to help the customer dig out of this mess with a simple, as Ravi would say, service as software. Where we could take the workflow data fabric connected perfectly to the workflow and how it automates work between departments on one single pane of glass. Now we can access the unstructured and the structured data with one magnificent database that can ingest as much data as you want to put into it. That's the ServiceNow Raptor DB. Or you can choose to leave the data wherever it is and we make a zero copy. The reason that is so substantial is the speed at which you can execute the work itself and how it flows, especially with agentic AI. It's lightning fast, totally secure, and extremely inexpensive to run because we're not consuming huge GPU power to run on the workflow automation or the workflow data fabric of ServiceNow. But best of all, with the help of Cognizant, we not only run ServiceNow domain-specific LLMs on the ServiceNow platform, but we also warmly welcome LLMs from other providers, and they seamlessly integrate into the ServiceNow platform the way work flows and the way the data in that workflow comes together. So you get stuff done, and you get it done at a low cost, at a tremendous pace, and most importantly, it's super secure. I think all these forces coming together leads us to believe that we're generating a true renaissance in the enterprise today, whether that's in the commercial or the public sector. We're reinventing it.
Right, what about the cost of AI, Bill? Because our research shows nearly 50% of executives just don't feel ready for the shift, or are nervous about the shift. 15% generally are there. So how do we get past the technical and actually fix the cultural problems that enterprises are facing?
