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Season 2 Episode 1: The Next Wave - Bill McDermott, Chairman and CEO, ServiceNow, and Ravi Kumar, CEO of Cognizant
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In this Season 2 premiere episode, host Phil Fersht sits down with two industry titans—Bill McDermott, Chairman and CEO, ServiceNow, and Ravi Kumar, CEO of Cognizant—to explore the evolving landscape of enterprise technology. They discuss how “digital fluidity” and transforming work from rigid tasks into dynamic workflows enabled by AI-driven agents can reshape entire organizations. They also dive into how AI can turn operational data into strategic assets, the importance of trust and ethics, and why leadership and cultural shifts are key to navigating the next technological renaissance.
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Transcript
Introduction to 'From the Horse's Mouth'
00:00:12
Speaker
You're listening to From the Horse's Mouth, intrepid conversations with Phil First, 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.
Future of Workflows and AI Integration
00:00:37
Speaker
All right, well, there's I'm really pleased that we could have you both lend a little bit of your time for um something much more fun, which is having a conversation about um you know the future of workflows, digital fluidity, and how do we get beyond a lot of the hype that we've experienced.
00:00:59
Speaker
over the last last um year or so. So ah maybe we'll start with you, Bill, and you know let's talk about ServiceNow's workflow data fabric. I mean, you're trying to bring AI into enterprise decisions. um But what does this really mean for the future of work?
00:01:19
Speaker
The future work has really evolved from generative AI, which was making tasks done on a platform like ServiceNow's easier, simpler, faster, to agentic AI, where you're really capitalizing on gen AI, but you're also putting these agents to work. I call this the digital workforce. They work 24 by 7, 365 days a year, and you don't even need need to give them a healthcare plan.
Agentic AI and Workflow Data Fabric
00:01:47
Speaker
And the vision is to have every employee and every company having agents work for them. And I believe the claim to fame at ServiceNow is that not only do we act as the orchestration layer or 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 and I do want to give a shout out to Cognizant and Ravi in particular because the workflow data fabric Ravi and Cognizant were the first movers.
00:02:32
Speaker
in adopting this in the marketplace because he saw how workflow would tie to data. And with the fastest database wrapped to 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.
00:03:02
Speaker
And 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 and together that makes a very valuable combination to drive productivity, efficiency, and growth in companies today.
Digital Fluidity and Cultural Shifts
00:03:24
Speaker
right So Ravi, you know you you you're partnered with Service Mail ah to promise digital fluidity, seamless connection across systems and teams. But how can organization really achieve this? you know What cultural shifts are required? How can leaders break down resistance to drive these AI-driven transformations?
00:03:46
Speaker
You know, what 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 there is a need of a technology which will allow you to do that.
00:04:18
Speaker
What does that do? What does digital fluidity do? If you're able to move work seamlessly across ah across an enterprise, you you can make that enterprise ah real-time sentient because you can do decision support in ah in ah 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,
00:04:45
Speaker
and it is moving along with work and you are able to do intelligent decisions as as the flow happens.
ServiceNow as a Platform of Platforms
00:04:54
Speaker
Imagine if there are AI algorithms underneath it which are making the data generative in nature and um going back to what Bin said, if you want to take the output from it and actually actionize it with agents which are digital nature rich well in alongside human humans. You're going to really find enterprises to be in ah in a in a state where they can take decisions real-time. They can actually predict what is coming, leave alone being an intelligent workflow.
00:05:33
Speaker
Now, ServiceNow, if you look at the stature of ServiceNow in an enterprise landscape, it's probably the only unique software product available, which actually orchestrates across an enterprise. And it is a platform of platforms which sits on top of existing systems. So not only as it does it have agents on on its own, it can actually integrate with agents of other systems which are available. So ServiceNow Stature, to be that system of experience and system of engagement, allows it to take that position of being that orchestration layer.
00:06:15
Speaker
So I'm very, very excited about the fact that not only are you able to agentify the output coming out of Genitive AI, you're embedding that into workflows and you are able to do day-to-day enterprise real-time decision making.
00:06:31
Speaker
with the power of generative AI, with the power of identification, and with the with the power of in-memory data, which is actually sitting in those workflows. It was almost a slam-down opportunity for me to partner with ServiceNow and to bring the power of digital fluidity to enterprises. i mean you know, early on in my two years staying, this was one of the first strategic investments I made. And thereafter, we we invested a billion dollars into ServiceNow, into the ServiceNow infrastructure of Cognizant. Then we actually bought a company called Thadera. And now this is the next big thing we did, which is to bring the power of workflow to power of agentified workflows, real time data, you know, embedded into it.
00:07:20
Speaker
for enterprises to ah you know um be be that sentient real-time enterprises. and you know We talked a lot about service as software. and Is this really about converting services into autonomous software, Ravi?
00:07:38
Speaker
You know, ah the last wave of technology was software as a service. The next wave of technology, or rather the current wave of technology is, um you know, service as autonomous software or service as software, and it is real. You know, and I'll give you an example. Imagine if you are implementing, say,
00:08:08
Speaker
if you're implementing Salesforce software for any Salesforce software, sales and marketing software for an enterprise. this the 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.
00:08:33
Speaker
So if you assume the market of sales and marketing software, enterprise software is, say, $200 billion, dollars the underneath services was 2x, which is, you know, $400 billion. dollars I mean, the plumbing is in the cloud. Otherwise, it used to be one is to five as the ratio. Right now, it's one is to two. Now, in the world of identification,
00:08:57
Speaker
My total addressable spend is no longer the service underneath the software. It is actually all the labor pools attached to that particular function. And in this case, in my example, it's sales and marketing. So there are people punching in opportunities, there are people punching in forecasts, sales compensation, analytics. I can take all those labor pools and make it more productive using digital agents. So the total addressable spend is no longer that $400 billion of the $200 million of software.
Transforming Data into Strategic Assets
00:09:30
Speaker
It's actually $2 trillion, dollars which is actually spent around the software function, I mean, along this around the sales and marketing function. I can go after examples after examples if you take HR software. HR software is roughly the ballpark size of the businesses, maybe $100 to $200 billion. dollars
00:09:50
Speaker
The amount of money spent on you know all the human capital services attached to it is $2 trillion. dollars Now, with the power of you know platforms like ServiceNow, which really sit on top of all the enterprise software,
00:10:08
Speaker
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, unique opportunity to actually now translate operational spend into the addressable spend for companies like Cognizant and ServiceNow to come together. And that's why I ah think it is the next big wave, which is service as a software.
00:10:43
Speaker
Yeah. I mean, it's fascinating, isn't it? So getting back to the, I think the big theme of the partnership, Bill, you know, workflow data fabric, there's a lot of noise around transforming um 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 their business strategy?
00:11:10
Speaker
You have to take Ravi's remarks extremely inspirationally because this um AI market that we're participating in is a $20 trillion dollar market in terms of its impact um in the next five years.
00:11:29
Speaker
that's pretty incredible i've never participated in a market like it i've also never participated in a market where for every one dollar that's wisely invested you'll get a minimum of five dollars in return and 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.
00:12:10
Speaker
as Ravi beautifully said. I think now when we get into the workflow data fabric and the ri 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 is leaders have to have courage, but they also have to have speed because a decision delayed today is a loss tomorrow. And Ravi understands that as well as anyone I know.
00:12:40
Speaker
And so the way I look at the data fabric, you take these um 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.
00:13:09
Speaker
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.
Streamlining Workflows with Agentic AI
00:13:26
Speaker
And 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.
00:13:38
Speaker
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 org charts. And some of that data will be structured and some of that data will be unstructured. Some of that will be on someone's desk desktop. Some of that will be in a data vault. And some of that will be trapped in these archaic systems of record.
00:14:07
Speaker
Our job is to help the customer dig out of this mess with as simple as Ravi would say, um serve us software as a service.
00:14:19
Speaker
or 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 and 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 service now wrapped the DB, or you can choose to leave the data wherever it is and we make a zero copy.
00:14:52
Speaker
And the reason that that is so substantial is the speed at which you can execute the work itself and how it flows, especially with agentic AI, and the fact that it's lightning fast, it's totally secure, and it's 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.
00:15:19
Speaker
But best of all, with the help of Cognizant that we not only run ServiceNow domain-specific LLMs, which means on the ServiceNow platform, but we also warmly welcome LLMs from other providers, and they seamlessly integrate into the ServiceNow platform the way workflows 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. And so 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
00:16:07
Speaker
or the public sector, part of the enterprise, we're reinventing it.
AI's Impact on Jobs and Productivity
00:16:13
Speaker
Right. What about the human cost of AI, Bill? Because, um you know, our research shows nearly 50 percent of executives are just don't feel ready for the shift or are nervous about the shift, and I think 15 percent generally are there. um So how do we get past the technical and and actually fix the cultural problems that enterprises are facing?
00:16:36
Speaker
I think there's a few things going on here and allow me to unpack it um just a little bit, Phil. First of all, this has been going on way before the AI generation where technology was feared as a potential source of job loss. In fact, in 1966, Time magazine published a huge article essentially stating that the computer would likely displace 90% of the jobs. Only 10% of the jobs would be left and they would be senior executive jobs and the state and the federal governments would have so have to subsidize 90% of the people because it'd be no work.
00:17:22
Speaker
And i as you know, 100 plus million jobs later just in the United States alone, that theory was proving incorrect. Now, as it relates to generative AI, keep in mind there are literally millions of jobs in the global economy available today that go unfilled because we don't have the technical skills to fill them.
00:17:46
Speaker
Also, we have millions of jobs in the global economy today that are doing soul-crushing work that people don't even want to do in the first place. And in some job categories, you have 40% year-over-year turnover. Call center would be an example of such ah an area where there's this enormous turnover. And this turnover in every company, could you imagine if people came to work and they weren't swivel-sharing?
00:18:16
Speaker
between 17 different applications on average a day in the average enterprise, eating up a third of their productivity, and instead, AI was doing the soul-crushing, repetitive work that humans don't want to do, and now they don't have to do it.
00:18:36
Speaker
And you could enter one operating experience with ServiceNow, search for any information you want, and execute a workflow as part of a team doing all kinds of new and highly innovative things to bend the curve on revenue per employee where companies could actually grow again.
00:18:57
Speaker
and companies could take this efficiency and this productivity increase and start reimagining business models and start thinking about things that the world doesn't even yet know it needs. But once it has it, it won't know how it ever lived without it. And I think that's what Ravi and I are trying to bring to the world.
00:19:17
Speaker
a positive feeling that agentic AI, an automation platform like ServiceNow, the flow of work, the fabric of data, and the great skills of Cognizant can come together and fundamentally rethink business models and innovation and change entire industries in the global economy and do it right now.
00:19:41
Speaker
Yeah. i mean I mean, we are going through a profound shift and I think Bill, you've you've described it beautifully. Ravi, you're running a 400,000 person company. um but How do you deal with the ethics around this and the security and the intent of tensity intensity around accounting and accountability? yeah yeah so the so Fairly, Bill beautifully explained the the human capital aspect of this technology. I'm just going to add one or two things before I get to the ethical part. I mean the biggest challenge for enterprises across the world and for the manner of the societies we all live in is upward social mobility in jobs.
00:20:28
Speaker
ah Just in the United States, we have any point of time, eight to nine million open jobs, which is what Bill was alluding to. And there are no takers for it because you know the skills needed are digital skills. Equally, on the other side, we have 4 million people leaving jobs every month, every month, which is one third of the US s workforce turns around every year. And these are people who are in a swim lane, which don't have access to the other one, which has
00:21:00
Speaker
ah which needs digital skills. I think the power of AI technologies with natural language as an interface for its applicability is going to create and diffuse much faster than any other technology we've seen in the past. fast just because the interface is natural language and never before have you know humans and you know computers have tried to understand humans versus the other way around so I would actually believe it it kind of unlocks um it kind of unlocks barriers to get into specialized jobs
00:21:39
Speaker
It reduces the ah the ah the space within an occupation and between occupations. ah It ah kind of removes the entry barriers to high profiled, high paying jobs. And I would say this is going to be a tectonic shift in the way we would look at human capital and how we are you going to use technology to amplify human capital, the potential of human
Ethical Frameworks in AI Development
00:22:04
Speaker
capital. Imagine if you have higher wages and lower costs. It's going to be deflationary for a high growth economy. Higher wages for lower costs because you just are able to do both on that.
00:22:19
Speaker
So that's the world we are all going to live in. you know you see it's ah It's a world of abundance, and it will help us to unlock that digital divide, which we put which we probably, in ah in a you know and you know in in the last few decades, ended up doing ah because of the need of digital skills.
00:22:41
Speaker
ah Coming to ah ethical ah frameworks on AI development, i mean you have to balance innovation with ethics. The framework for any technology around ethics was about safety and equity because you know technology has data underneath it.
00:23:02
Speaker
I think this is uniquely a technology with transformer-led algorithms, internet-scaled data, and unbelievably high compute, which Bill was referring to. You are going to find trust as a very, very important constituent in the ethical framework of how you deliver its trust, equity, and safety.
00:23:26
Speaker
And if i if I have to put this in a framework, you know, Cognizant has a framework called FAST, which is fair and inclusive, accountable, safe, private, and secure, and ah transparent and explainable. I mean, you need it needs to be explainable because you're getting the output out of a black box.
00:23:49
Speaker
So the importance of ethics and responsible AI ah is an important cog in the wheel to support the process of scaling use cases and powering the use cases with more values so that they can actually be more mainstream.
00:24:09
Speaker
So, the power of actually you know taking this technology, the raw technology, and making it enterprise-grade is all about making it responsible enough.
Leadership and Technology for Societal Improvements
00:24:18
Speaker
And I think the the frameworks of ethics are going to be an integral part of this process. um You might have noticed this, Phil, and maybe Bill has seen the ah press release we did yesterday. We are the first company We are the first company, which actually got ISO certified on AI management yeahi management systems. And the power of doing that was related to making it responsible and ethical as we deliver these systems at scale. um And we created continual improvement process by using these standards, which are third-party standards.
00:24:58
Speaker
Yeah, say adopting a software mindset for services. It's incredible to see. Well, I'll finish up with a question for each of you. um It's been one hell of a 2024, right? So what's our one wish for our industry in 2025? Maybe Bill, you could lead off. One wish. Leadership.
00:25:22
Speaker
I think um you know we're in a world where ah leadership matters now more than ever. If you think about ah technology's place in the world, the only way to truly fundamentally improve business or society today is through the intelligent, secure, and ethical use of these technologies.
00:25:47
Speaker
And so it's going to take leadership in both the public and the private sector and full cooperation between the two to fundamentally change things and build a better society for everyone. I think leadership is really what it's all about.
00:26:03
Speaker
Thank you. Ravi, I wish. You know, um Phil, we're living in a phase of uncertainty and change. I mean, I hope the the promise of change outpaces the uncertainty around us.
00:26:23
Speaker
um And then the change is powered by the extraordinary transformative power of AI. And the uncertainty, of course, all of us know the geopolitical uncertainty around the world. So I'm very, very hopeful that the change is going to trigger and outpace the uncertainty. And therefore, we are all going to benefit out of this extraordinary transformative ah power of AI technologies. Wonderful. world
Conclusion and Future Outlook
00:26:53
Speaker
smarter leadership, stronger leadership, and much less uncertainty. Sound good like good ideas to me. And I really appreciate you both taking time at the end of a busy year to share some of your thoughts. So congratulations on your partnership. This is the year of, I think next year is going to be the year of services as software. And it's great to have a leader from each area share their thoughts and come together today. So thank you very much for your time and
00:27:21
Speaker
And a happy yeah holidays to you both. Thank you very much Phil. Thank you Ravi. Happy holidays. Thank you so much. Thanks for hosting us.
00:27:33
Speaker
Thanks for tuning in to From the Horse's Mouth. Intrepid conversations with Phil first. Remember to follow Phil on LinkedIn and subscribe and like on YouTube, Apple Podcasts, Spotify or your favourite platform for no-nonsense takes on the intricate dance between technology, business and ideological systems. Got something to add to the discussion? Let's have it. Drop us a line from the horse's mouth at.com or connect with Phil on LinkedIn.