Another day, another SaaS vendor competing to grab the attention of the enterprise with a range of new AI capabilities. This week, as part of its Now Platform Orlando release, ServiceNow introduced Now Intelligence - a new set of AI and analytics capabilities.
Ahead of the announcement we spoke with ServiceNow’s VP of Innovation, Chris Pope, who gave a rundown of how the vendor is utilising the best of AI platforms on offer from the likes of Microsoft, Google and IBM, whilst also differentiating where it feels it can compete (workflow/process).
However, Pope also warned that organisations that want to make the most of AI technologies often still haven’t woken up to the fact that they won’t fix what’s currently broken by throwing AI at it. In order to make the most of the ‘machines’, Pope argues that companies need to take a long hard look at what outcomes they’re trying to achieve and invest time in rethinking processes.
This is ultimately ServiceNow’s bread and butter - ‘making the world of work, work better for people’ - but it’s still interesting that the company is taking a process first approach to AI. It’s a more measured response than we see from some others that fall into the marketing hype and try to convince end users that AI tools are here to solve all their problems.
That being said, ServiceNow does have a challenge in refining its meaning in this space, given that it doesn’t position itself as the ‘system of record’ in the enterprise (where those vendors have very obvious use cases to sell). That being said, as the vendor ‘redefining workflows’, it makes sense to double down on process.
So what’s new? The Orlando release provides a number of updates under the Now Intelligence umbrella - including everything from surfacing context-aware recommendations to ‘always on’ virtual agents’. However, ServiceNow has broken it down into three categories:
Analytics solutions - this includes cloud insights to help IT teams optimise the cost of their cloud assets; advanced risk assessments to help frontline staff asses risks within their daily work; and software exposure assessments to help miniseries the potential impact of zero-day vulnerabilities.
Intelligence solutions - this includes agent affinity for work assignment, allowing customer service teams to assign work to the best agent using intelligent context; virtual agents with natural language processing; CI/CD tools.
Mobility Solutions - which provides mobile agent enhancements that deliver native mobile experiences so service desk agents can ‘resolve issues at any time’; providing employees with contextual and relevant information on their mobile devices, making employee communications more proactive.
Where can ServiceNow differentiate?
As noted above, we got the chance to speak to ServiceNow’s innovation chief Chris Pope about the announcement. He highlighted that ServiceNow is making use of partnerships it has forged with the likes of Microsoft, IBM and Google to take advantage of their AI platforms - such as natural language processing or image recognition, to integrate them directly into the workflow.
Pope said that ServiceNow shouldn’t be investing in AI where it can’t compete. He said:
[Microsoft, Google, IBM]...they’ve got armies of people to do this stuff. Google’s AI team is 7,500 people, we as a company are 10,000. It makes no sense for us to try and replicate or compete with what they’re doing.
However, he does think ServiceNow holds a niche in the market that the likes of Google can’t compete on, which is where it will double down on investment under the Now Intelligence umbrella. This largely focuses on process intelligence. He said:
I think the thing that we have that they don’t, is where the work occurs. So the processes.
We’ve built our own process mining capability that leverages machine learning and AI. And it starts to say: you are the service owner for a bunch of service desks, the process you model looks like this - from A to B to C - but actually the way people are using the system, the way that data is flowing, it’s not following your model.
You’ve got bottlenecks, you’ve got delays. So process mining gives us the ability to inspect and understand what’s going on in the process.”.
The next stage of that is using intelligence to say, here’s a better way that that process should be modelled based on actually how your teams are working together. They’re the things that the Microsofts and the Googles don’t have.
Pope elaborated by saying that ServiceNow wants to automate workflows, intelligently. It wants to allow customers to identify where the work should be going the first time, every time, and remove moments of friction throughout that process. This is very much in line with ServiceNow’s workflow platform more broadly, but it is looking to add moments of intelligence throughout those journeys.
How do we use the intelligence to say, we know where they are, we know they are in an advanced state of a challenge or an issue, let’s route that work to the right people first time. You get the support you need without the traditional frustration of getting bounced between departments or you go back in the queue, or the person you talk to can’t help you.
However, Pope advised that ServiceNow’s ambitions for AI are not to throw technology at every situation, claiming a recognition that despite what customers may be demanding, there are likely more fundamental problems that customers need to fix first.
He said that organisations have been focused on building and scaling massive data lakes and warehouses, integrating those, but often without a clear vision of the problem at hand.
ServiceNow aims to guide its customers towards AI solutions, with an outcomes focused lens, Pope said. However, that being said, ServiceNow will largely be relying on its partner ecosystem to advise on this change management agenda. Pope explained:
There’s a maturity problem. AI is here and now. It is available. The barrier to entry is very low. The technology is good enough. But many organisations just aren’t in a place where their processes work consistently. We don’t want to say, ‘Hey we’ve got machine learning, what do you want to do?’. Because you get into, ‘what can it do?’. And then it’s, ‘I don’t know, what do you want it to do?’. And it’s a never ending conversation.
We want to go to the customer and say, what does good look like? What is the outcome that you want? Too often it’s another technology project without a defined outcome. There’s a big organisational change element to this.
People that think you can throw a blob of unstructured data at a machine and it will magically tell you what the lottery numbers are, are wrong. There’s more structure to it that’s needed. The machine will tell you that the way you work and the way your process works are broken. You’ve got to go and fix those things, to start getting better results.
This isn’t necessarily a technology problem, but you’ve got to fully understand the guts of the problem first, the outcome you want, the processes, and then the technology can be applied.
I like that ServiceNow is focusing on outcomes and fixing the fundamentals in the enterprise, alongside it’s AI pitch. It’s more compelling than ‘AI will fix everything!’. That being said, I do think ServiceNow’s sell in this field is a bit tougher than some other system of record vendors that can talk to specific use cases in HR, accounts, CX and ERP. And that’s because ServiceNow is about workflow and touches everything. A big part of its story over the past 10 years has been about automation already. Refining the process fix pitch, and elevating that with AI, will be key.