ServiceNow seeing “millions of dollars of savings” using its own AI products internally

(Image sourced via ServiceNow)

Cloud workflow vendor ServiceNow recently raised its guidance and said that 2024 will be the year that it hits $10 billion in annual revenue. What’s been clear from the leadership at the company is that central to its success is a one platform, one data model approach. In fact, when diginomica sat down with ServiceNow CEO Bill McDermott last year, this was the central focus of our conversation. However, what’s particularly interesting now is that this one platform, one data model approach might also prove useful as the company expands its Artificial Intelligence (AI) offering. 

It’s not hard to understand why. AI models need data to scale and become useful, which is made much harder if the data itself is siloed and not accessible in a ubiquitous way across an organization. ServiceNow has announced partnerships with the likes of OpenAI and NVIDIA to build out its AI capabilities, but its focus is primarily on building domain specific LLMs - AI models that are uniquely useful to individual companies, because of the data that they’re based on. 

To this end, since then, ServiceNow has launched a number of AI products, including Now Assist, as well as add-ons that allow for more complex AI computations - in the form of Pro Plus, Enterprise Plus and Creator Plus. Depending on how many ‘seats’ an organization buys for these add ons, depends how much they can use the ‘Pro’ - or more advanced - tooling. 

This context formed the basis of an appearance by ServiceNow CFO Gina Mastantuono at the Morgan Stanley Technology, Media and Telecom Conference, where she shared some guidance on how the AI tools are being used, how it might impact ServiceNow revenue in the coming months and years, as well as details on how the vendor is using the tooling internally. 

Firstly, Mastantuono was keen to highlight that whilst the Generative AI hype has been significant since the launch of OpenAI’s ChatGPT, ServiceNow has been investing in AI more broadly for many years. She said: 

We get the question about AI a lot and we've been building continuous innovation into that platform. And that is one platform, one data model, one architecture that holds all of the data that really allows us to have enormous quantities of information that really drives productivity efficiencies. 

And it's one of the reasons why I think we've been able to be first to market in our AI solutions, because we have been innovating and investing behind those areas for years and years. We had our first AI SKUs launched in 2018. So, this is an area that we've been fundamentally driving, and it's about innovation first, innovation first, innovation first.

Adoption and impact

Mastantuono said that AI is coming to the enterprise and it’s “coming fast”. However, she cautioned that the market needs to be realistic about its material impact on the top line, given that it’s still early days. Enterprises take things like change management and security very seriously, she added, and those aspects will take some time to figure out. However, Mastantuono added: 

We launched our first [Generative} AI SKUs on September 30th. And so, one quarter in, [it’s] the fastest growing of the new products. But it's still new and it's still small in a $10 billion base. 

When is it going to start to make a meaningful contribution? I know that's what everyone keeps asking. What I keep saying is we will keep you updated as to the progress we're seeing. 

Our customers are really leaning in. I think Gartner is talking about $3 trillion being spent on AI over the next three years. And so I absolutely think it's going to make a meaningful contribution over the next two to three years.

Mastantuono said that the adoption of ServiceNow’s Generative AI SKUs are mimicking the adoption curve that it saw with its initial AI SKUs, back in 2018. It’s not quite yet an “accelerated adoption curve” - but she expects this to gain traction over the year. Mastantuono added: 

But if you think about the excitement, the understanding of the productivity gains that Gen AI can drive in 2024 versus what we knew and understood, and what customers knew and understood back in 2018, there's an argument for sure that that adoption curve will be faster. 

Exactly how fast given…change management, implementation road maps…[who knows]. The great thing is that for people who are already on our Pro SKU, it's a pretty easy lift to upgrade to Pro Plus. We'll keep you updated as to progression. One quarter out, it's a bit too early to say, but I think the top line opportunity is clear.

Mastantuono gave some customer examples, however. She cited Siemens, which is using ServiceNow’s AI SKUs to automate the HR experience and drive productivity for HR agents when resolving issues with employees. Another large American fast food chain is planning on using AI to drive end-to-end employee engagement, she added. Whilst, another US industrial company is using it for low-code and no-code, to build text to code, in order to make developers more efficient. She added: 

It's really across the platform. We're using it internally across the board. We're actually using it not only in finance and in IT - IT obviously is a big area where we're using it - but also in our sales organization, with Sales Assist.

How do we make one place for our sales associates to go where everything about their customer is on their phone? Where they can understand when the last conversation was, what their pipeline is, what the next best activity is - really having an end-to-end solution for sales to help drive productivity. I love that because it's efficient. And by the way, if they're spending less time with admin, they're spending more time with customers.

Doing the math

Mastantuono said that ServiceNow is pricing the new AI SKUs based on how organizations are receiving productivity gains from the new AI tooling. She said: 

We looked at the productivity expectations, the efficiencies by task, and we looked at employee salaries. And what we do is we give 90% of that value to customers and we keep 10%. That value equation seems to work extremely well with the customers. And based on our initial kind of one quarter out, feels like we're in the right place.

However, she cautioned that the discussion on ‘AI coming for our jobs’ is too broad. Instead we should be thinking about certain tasks being automated away. Mastantuono added: 

Now ,I don't think that 30% of one person's job is going away immediately, right? It's specific tasks. So, how does that math work? How many of the tasks that they do are going to be automated? 

I think companies are going to really have to lean into reskilling some employees, because it does mean that they have more time. I don't think that full jobs go away, but how do we make them much more productive and really drive reskilling in areas where I think there's more value add.

In terms of future pricing, Mastantuono said that there’s a few different ways of thinking about charging ServiceNow customers for AI. For instance, ServiceNow could look at ‘speed to resolution’ as a metric. She said: 

Productivity is not just about time, it's about better resolution, it's about getting those IT issues solved faster, which means the employee who's either with the customer or building code and driving innovation can be more productive to drive better top line, better innovation across the board. 

However, as is wise, ServiceNow is developing its understanding of how organizations may benefit from new AI tools by deploying them internally. Mastantuono said that the vendor has focused on 15 to 20 use cases, which are live, and that it is already seeing “millions of dollars of savings” just in one year. She said: 

We drink our own champagne, as you say. We're seeing great efficiencies within our IT organization. I talked about Sales Assist, where we're really leaning into Gen AI for our sales teams. Another use case [is using] text to code in our developer community. 

Obviously, we are a very large R&D organization, so the more that we can use our own SKUs within our developer community, the more efficient we get and we'll see some productivity there as well.

My take

Some interesting insights here from ServiceNow. Whilst not completely black and white, Mastuonono’s comments give us some insights into where the market is seeing uptake and how the vendor might think about pricing in the future. These are some of the details that we need as the hype in the market begins to die down and buyers start to get real about their use of AI. Where benefits are most likely to be realized? What are the use cases? How are you measuring the gains vs the cost? And what are you doing about skills as employees are freed up and have more time?