\n<\/p>\n
If data is truly the fuel for generative AI, and one of the keys to a successful implementation is access to data meaningful to running the business, it would seem that certain SaaS vendors have a built-in advantage where the data is concerned. Executing is another matter, but if the data is there, the models at least have something more meaningful to work with.<\/p>\n
One of the earlier SaaS adherents to generative AI has been ServiceNow, which has been able to take advantage of the data in its own platform to help build more business-centric models.<\/p>\n
For CIO Chris Bedi, it\u2019s all about building a practical experience that helps people get work done more efficiently. \u201cI\u2019m a firm believer that a model is only as good as the platform. If it\u2019s part of a great model, but it\u2019s not attached to an experience, not attached to a workflow, what\u2019s the point?\u201d Bedi told TechCrunch.<\/p>\n
Brent Leary, founder and principal analyst at CRM Essentials, says ServiceNow is making a deliberate effort to focus its AI on practical matters. \u201cI think ServiceNow\u2019s focus on building their own full-stack generative AI platform gives them the ability to aim their efforts on workflow creation, optimization and integration. This has the opportunity to impact processes that cross into multiple departments\/areas and platforms,\u201d Leary said.<\/p>\n
To achieve that, the company is building AI into all its workflows. Bedi divides ServiceNow\u2019s generative AI capabilities into three broad areas.<\/p>\n
The first is dealing more systematically with requests. \u201cWhen someone is asking for something, we call that a requester. That could be a customer, it could be a supplier, it could be an employee. How do you help them get an answer faster?\u201d<\/p>\n
The second piece involves helping agents do their job better, regardless of their focus. \u201cYou can be an HR agent, an IT agent, a customer service agent \u2014 somebody\u2019s doing something \u2014 helping them do the repetitive type tasks faster, or completely moving it to the machine, and we\u2019re seeing productivity gains there as well,\u201d he said.<\/p>\n
The last piece is finding ways to speed up innovation. Bedi thinks that this could bring a whole new level of automation like text to code, text to automated workflow or even working multimodally to allow users to do things like taking a picture of a diagram or whiteboard brainstorming session, and turning that picture into a workflow.<\/p>\n
\u201cServiceNow is implementing a unique AI strategy that is a mix of building, buying and partnering,\u201d said Holger Mueller, an analyst at Constellation Research. He says the company needs such a diverse strategy for a few reasons.<\/p>\n
\u201cFirst of all, ServiceNow customers have a wide range of AI partnerships, and they want ServiceNow to leverage and cohabitate with them,\u201d he said. Those partnerships include the likes of Nvidia and Microsoft, among others. \u201cThen it needs to build its own AI automation as customers also expect out-of-the-box AI experiences,\u201d he said. Finally, it combines in-house development with acquisition to build out the platform.<\/p>\n
At the same time, the company has customers with varying degrees of AI readiness, and it needs to provide a range of solutions that cross those capabilities, says Jeremy Barnes, VP of AI product at ServiceNow, who came to the company via the acquisition of his previous company, Element AI<\/a>. \u201cI\u2019d say the biggest and fastest growing companies have, for the most part, nailed the organizational changes needed to implement digital transformation,\u201d he said.<\/p>\n But for those who aren\u2019t as far along, they try to combine their own solutions with help from ISVs and MSPs to get them up to speed to take advantage of AI.<\/p>\n Financial analyst Arjun Bhatia from William Blair sees the new AI capabilities as something customers are willing to pay for. \u201cWhile it is still early, ServiceNow highlighted strong demand trends for its new Pro-Plus SKUs as enterprises look for ways to invest in gen AI,\u201d he wrote in a report<\/a> published in May. What\u2019s more, the company has seen relatively little pushback on the pricing, which could indicate that they see value.<\/p>\n IDC analyst Stephen Elliot says that the company has been investing in AI, generative AI and related talent for more than five years, and customers are seeing results from that effort.<\/p>\nMoving at the speed of customers<\/h2>\n