Like many enterprises, ServiceNow has been incorporating synthetic intelligence (AI) into its inside programs and customer-facing merchandise for years. But when Open AI’s ChatGPT emerged a yr in the past, every thing modified — quick. Suddenly, what had been machine studying — or “analytical AI” that might produce suggestions based mostly on monetary, gross sales, and advertising knowledge — grew to become natural-language processing. A model new worker might suddently ask the company generative AI (genAI) software for a solution to an in-depth shopper query. Seasoned staff might ask the platform for details about firm advantages or learn how to get a brand new laptop computer.Chris Bedi joined ServiceNow in September 2015 and serves as the corporate’s chief digital info officer. Prior to becoming a member of ServiceNow, he spent virtually 4 years as CIO of JDS Uniphase Corp. (JDSU), the place he was answerable for IT, amenities, and oblique procurement. Before that, Bedi held varied positions at VeriSign between 2002 and 2011, together with CIO, vice chairman of company growth, and vice chairman of human useful resource operations.When he joined ServiceNow, the corporate was incomes about $800 million a yr in income. Today, its income tops $8 billion, and it employs about 22,000 staff. Bedi has additionally gone all-in on AI.ServiceNow is now implementing genAI via an inside pilot program. Leveraging its personal platform and third-party LLMs, the corporate has gone dwell with 15 genAI pilots throughout a number of departments, together with customer support, IT, HR, and gross sales.Those trials are centered on driving higher buyer and worker experiences with greater self service, agent productiveness, automated advertising lead administration, and text-to-code software program growth. ServiceNow
ServiceNow’s CIO Chris Bedi
Bedi just lately spoke with Computerworld and defined why he sees the introduction of ChatGPT and genAI as a watershed second for enterprises, and why he worries much less about what might go mistaken and extra about whether or not he is creating an surroundings the place the know-how can advance as quick as its capabilities allow it. The following are excerpts from that interview. When did your organization start utilizing AI on any stage? “I joined September 2015, and I remember meeting with our machine learning team as part of my onboarding. So, we’ve been doing machine-learning applications as early as 2015. As you can imagine in 2015, a lot of this was a bit more pilot, science projects.”Over the years, we’ve scaled it tremendously. The trade hasn’t actually settled on a time period. What will we name the AI that existed earlier than genAI? I simply name it analytical AI. If you consider it, it’s infusing machine studying into all of our vital rating, score, or advice [engines] on the place income goes to finish up, the likelihood {that a} gross sales deal goes to shut, the chance that we might have a buyer doing this. We’ve been doing this for a very long time.”And, we’ve been building a lot of AI into the ServiceNow platform, as well — whether it’s MLU, NLP, machine-learning-based calculation mechanisms, risk ratings, routing of customer cases, etc. Even before GenAI, we were using ML to automatically assess processes to find bottlenecks and inefficiencies. Once ChatGPT came out, we very quickly started moving to experiments, and now experiments are in production.”Most main CIOs did one thing related. If I name it analytical AI, they’ve been at it for some time. What genAI and ChatGPT has finished is it has type of woken up the remainder of the C-suite to this complete AI factor that almost all main CIOs have been on for some time.” Can you give me a definition for analytical AI? “I struggle with it, too. We were doing AI before ChatGPT came along, but we were calling it supervised machine learning, unsupervised machine learning, natural language understanding, natural language query, natural language processing. All those names were under the category of AI. Now we have genAI, so do we call it traditional AI? Do we call it analytical AI because most of it has to do with numbers. So, when I say analytical AI, it’s a placeholder term for all the AI that came before ChatGPT came along. So, again NLU, NLP, NLQ, virtual agents, process mining, RTA…, a basket of stuff.”What modified in November 2022 when ChatGPT was launched? “I think what changed in November, and I ask myself this, is this a metaverse moment where we’re all enamored with the tech? Or is this blockchain where we’re all searching for use cases? Or is this more of an ‘iPhone moment,’ which is really going to change almost everything we know.“I feel like this is more like the iPhone moment. What genAI allowed us to do — with large language models the underpinning of AI — what defines a language, I think that’s where it’s up to us to reimagine. Coding we’ve defined as a language now. Obviously, there’s text-based, whether it’s resumes or summaries of security incidents, all of that is a language. We’ve been doing things on the NLP [natural language processing] side with products for a few years.”So, we’ve been partnering with Hugging Face and StarCoder in developing large language models on the product side of the house. And, obviously I serve as customer zero for all of our products, which is why we’ve been able to release products so quickly. I think we were one of the first to offer real working [AI-infused] products to the marketplace.” Can you offer up some of the top use cases for genAI at ServiceNow — both internally and externally? “Right now, we have 15 use cases that are live and using genAI. I’d simplify those into four general use cases. One is around customer/employee experience. The industry has been after case deflection, employee self-service for a while now. That’s not a new concept. I think what genAI did is it gives that function a step up in terms of effectiveness.”If you think about searching for an answer on any customer support site, including our own now, you’ll now get a genAI response. That’s the equivalent of a search engine response where you’re getting a bunch of links and then a genAI search response where you’re getting the information you’re actually looking for.”Even in 10 weeks, we’ve seen a 3% to 4% jump in case deflection rates on our customer support site. We’re seeing very similar results on employee self-service. As employees need to know, ‘Who’s my benefit provider? How do I get a new laptop? How do I get a new travel card? Is this thing worthy of a press release?'”All those answers that are buried in…corporate policies and documents — genAI makes them instantly accessible. So, customer and employee service is number one.”The second use case is…agent productivity. An agent could be an IT agent, HR operations, customer support, or someone in finance. How do you help an agent be more productive by analyzing large sets of information quickly, summarizing it for the agent so they can get to the heart of the answer quickly?”On the flipside of that, as they’re managing their work and handing it off from one person to another or resolving it, you need to send a nice summary to the customer; genAI can write that summary for them. And we’ve actually seen with what we’ve deployed, 70% of agents are accepting those genAI summaries with minimal edits. We actually measure minimal.”We’ve seen an increase in cases solved for agents per week. We’ve seen shortened durations of the time it takes to resolve cases. So any way you slice it, the productivity boost is starting and we’re in the early innings. I know we’ll get better.”One other measure we’re looking at, which I think is really important, is the sentiment of the people using genAI. I’ll take my own shop that’s using AI for its IT agents, I think 56% have already said… this thing is a boost to their productivity. That sentiment is hard to get to because we’re so wedded to our current ways of working.”The third use case is accelerating digital transformation. So, text-to-code is real. Text to workflow is real. What we’ve seen is a 26% acceptance rate on our software developers accepting what genAI is providing them on a text-to-code standpoint. For people outside the industry, 26% may seem small, but as a practitioner, I’m really pleased with that number. If you pull on that thread, that’s 26% more lines of code that can be written without a human having to do it. Pull on the thread a little more and you’ve got a 26% productivity bump in an area that’s one of the scarcest talent areas regardless of the industry — software engineers. And it’s only going to get better.”I would say there’s work to do on sentiment and adoption. People have been working a certain way for decades. GenAI is very new and, like with anything new, it’s going to take some time for the adoption rate to climb up to the point where it’s like you or I listening to Spotify for music or something like that.”When genAI works, I think the adoption rate will be a bit slower than leaders like myself want. That’s the standard recipe of change management, and training and skillset development on all those things.”The fourth use case is around…how to help a human become an instant expert. If you think about us as a high-growth software company, we want to serve our customers in the best way. We have lots of innovation coming out of our platform every month; keeping up with that in the interest of serving our customers is pretty hard. I think about a new person joining ServiceNow. If you remember the movie “The Matrix” when he plugs that factor into the again of his head and he immediately learns learn how to fly a helicopter — that’s the imaginative and prescient I’ve.”So, we put all our product documentation, from high-level worth messaging to low-level product expectations — how do you configure this — and took each RFP response, each gross sales presentation and gross sales coaching, listed it in giant language fashions. So now, if somebody joins ServiceNow on a Monday, on Tuesday morning somebody from [our customer] FedEx asks how do your options assist out with operational know-how danger administration, that new worker can shortly go to a portal and kind within the query and can get a really clever response. Think about that context of ‘instant expert,’ it could apply to any persona. We simply occurred to use it to the one which serves the shopper first, however we’re going to roll that out throughout the group.”Explain what the time period ‘customer zero’ means when it comes to rolling out new know-how? Are you saying you roll it out for inside operations first? “Two issues: I’m speaking about deploying quite a lot of this for inside and customer-facing use instances, however as a software program supplier we’re providing quite a lot of genAI merchandise to {the marketplace}. When I say buyer zero, I imply we use all that very same know-how to energy our personal enterprise. We use it to scale ourselves, and…the productiveness good points we get from utilizing our personal platform are self evident. So, by buyer zero, I imply we use each considered one of our merchandise internally, show out the worth earlier than our buyer use them to verify we’re assured on the technical facet and the enterprise facet, change administration, and many others.”What feedback are you hearing from your peers and customers about the current landscape for IT decision makers when it comes to genAI? “Because ServiceNow serves about 90% of the Fortune 500, I’ve the privilege of speaking to plenty of Fortune 500 CIOs each week. I’d say there are three camps:
One camp is saying, ‘We must spend the subsequent three or 4 months determining governance, determining safety, determining all of the underpinnings in a super-solid structure, earlier than I begin doing pilots and placing stuff into manufacturing.’
A second camps is saying, ‘Yep, the tech works, however I have to see an actual ROI earlier than I make investments materials human capital or {dollars} into this.’
A 3rd camp believes that is inevitable. ‘We want to simply get on with it. We don’t measure the ROI [on an established technology like] e-mail, and genAI within the office will probably be as widespread as that. So, the sooner we get transferring, the higher.’
“Again, none of the viewpoints are wrong. Everybody is probably doing some of each, but the common underpinning is everyone is doing something around genAI. Most CIOs I’m talking to have been asked by their CEO or C-suit to have a genAI strategy for each department.”When it involves company insurance policies, requirements and oversight, what have you ever instituted to make sure the protected and moral use of genAI, particularly in mild of President Biden’s latest govt order? “With President Biden’s new rules, I think that’s a great step in the right direction. We have a commitment to the responsible and ethical use of AI models.”So, we’re supportive of the brand new govt order. But we even have an AI ethics and governance council…to guard our staff and prospects from bias, cybersecurity vulnerability, knowledge privateness dangers, and even the consumer expertise of transparency. If somebody is getting a genAI reply to their query, we wish them to know this was generated by a machine.”We are very focused on it. We have an AI governance and ethics committee, which is cross-functional in nature. It’s legal, it’s my organization, it’s our product organization, it’s cyber. We test all that out before releasing anything to the market or our own employees.”