Presented by ServiceNow
The demand for AI has reached a tipping point -- IDC estimates an $11 trillion USD impact from AI in the next three years and forecasts that businesses will spend more than $half-trillion USD on AI in 20271. And when EY (Ernst & Young) recently asked 1,200 CEOs around the world if they plan to invest in generative AI, 100% of them said yes2.
The immense appetite for gen AI is beyond hype -- it’s reflecting the huge opportunity for well-positioned companies and investors, says Paul Smith, chief commercial officer at ServiceNow, whose cloud-based Now Platform powers end-to-end digital transformation for 8,100+ global customers including ~85% of the Fortune 500. It’s changing the anatomy of work, massively accelerating productivity almost immediately -- from 14% on average to 34% for novice workers, a recent study found3 -- reducing call times for customer service agents and more. It has the potential to automate the work tasks that take up 60 to 70% of employee time.4 It’s a game changer like never before.
“There’s no doubt that generative AI is a once-in-a-lifetime opportunity for the enterprise,” Smith says. “The results are real, undeniable and hugely profound -- we see it in our own business, and across every industry. If your competitors are moving on this while you hesitate, then the gap between you and them will grow sharply, and it will be enormous.”
The “why” is clear, but CEOs are wrestling with the “what to do” and the “how to do it” pieces of the equation. Too often that results in dozens of gen AI pilots scattered across the enterprise -- as companies experimentally dip into the alphabet soup of LLMs across a variety of use cases. But, says Smith, it’s the organizations placing bigger, strategic bets and striking up partnerships with select AI providers that are going to be the winners here, highlighting the value of adopting a platform-centric approach.
“As an enterprise, as a senior executive, or a CEO or a board, it burns just as many calories to do a few small generative AI pilots as it does to make some very thoughtful, very significant platform bets that will have far-reaching impact across your entire enterprise,” he adds. “Same effort, but dramatically different results when you put a platform to work behind some very key use cases.”
Boosting case deflection and beating resolution times
ServiceNow is so bullish on the value of gen AI for its customers because the company is using the technology to run its own business and already seeing tangible benefits. Customer service augmentation, developer productivity and employee self-service are serving up some of the biggest results for the company.
“As we look at our road map, we have some very specific use cases to help give us the biggest and fastest return, saving tremendous, double-digit percentages of those teams’ time," said Smith.
ServiceNow’s gen AI experience, Now Assist, is embedded across the Now Platform -- including its Virtual Agent chatbot and search capabilities -- delivering more effective self-service solutions. For example, customers can pose questions to the chatbot in natural language, and it can return answers in simple, conversational language rather than a traditional link list. Call histories are put right into a call agent’s hands at the start of an interaction. At the end of a call, Now Assist can summarize the output and update the knowledge base automatically while the agent moves on to service the next customer.
“We’re seeing a significant reduction in notes resolution time,” Smith says. “After we rolled out our own Now Assist technology, agents are taking about half the time to generate resolution notes and seeing a 10% boost to customer case deflection rates. When you apply those productivity gains to more complex cases, you get some far-reaching results.” And if you’re running, say, a 28,000-person call center, the impact can be massive.
A smart knowledge base for employees
As employees use gen AI tools in their home lives, they’re increasingly expecting that kind of convenience in their work lives. Now Assist has replaced the limited virtual agents that used to facilitate employee knowledge retrieval with a conversational generative AI interface, which is driving a 14% boost to employee request deflection rates -- whether it be to review onboarding procedures, check a pay slip, book personal time off and much more.
At the same time, Smith is using Now Assist to empower his Global Field team. Sales Assist is helping accelerate time for the company’s sales team to get quotes and proposals out to customers. “Rather than having to go hunt and peck for the information that they want, a conversational interface can get them the information they need on pricing queries, on customer references, on use cases that they can share,” says Smith.
Coding gains for developers
Developers are also seeing significant results with gen AI in the mix. Using Now Assist, ServiceNow developers are currently posting a 48% code acceptance rate -- in other words, the gen AI-produced code is being taken unchanged almost half the time. Developers are notoriously (necessarily) exacting in their coding, so this is a huge gain, Smith says.
“The one thing that every company on the planet is short of right now is software developers,” he adds. “If your software developers are getting a 48% acceptance rate overall, making them tens of percent more productive in their job, then that is absolutely huge for the whole industry.”
Strategic investments in the right platform
Again, going all in on strategic platforms with gen AI built in is a far better bet, financially and results-wise, than experimenting with a variety of tools, Smith says.
“Most leaders that I speak to are firmly of the mindset that they need to invest in fewer, more significant platforms -- and fewer projects as a result, but more transformational ones,” he explains. He pointed to a major bank who shared with him that they’re investing in Microsoft for employee productivity; they’re investing in ServiceNow for customer service and HR; then creating some of their own domain-specific LLMs for very specific use cases in financial services.
“The days where CEOs were prepared to tolerate thousands of enterprise applications in their business, thousands or millions of different dim points of light, those days are gone,” he said.
The only risk is not moving fast enough, he adds.
“You have to move fast. You have to do it with governance. You have to do it with security. You have to do it with the right platform partner,” he says. “But once you’ve done that, the company going the fastest is going to win the most.”
Learn how companies around the world are putting AI to work with ServiceNow.
Footnotes 1. IDC: "From Breakthrough Innovation to Impact: Monetizing the AI Moment," April 3, 2024. 2. E&Y: The CEO Outlook Pulse – January 2024, https://www.ey.com/en_gl/ceo/ceo-outlook-global-report 3. Graduate School of Stanford Business Working Paper, Generative AI at Work, https://www.gsb.stanford.edu/faculty-research/working-papers/generative-ai-work 4. McKinsey: The economic potential of generative AI: The next productivity frontier, https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.