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ARTICLE | May 14, 2024

5 macro lessons from Knowledge 2024 

Revolution was on the agenda at ServiceNow’s flagship conference

By Richard McGill Murphy, Workflow contributor

In early May, more than 20,000 technologists and business leaders gathered in Las Vegas for Knowledge 2024, ServiceNow’s annual user conference. Billed as the smartest Knowledge ever, this year’s conference focused on how organizations can put AI to work to solve challenges across every business function, from IT to HR, sales, customer service, finance and beyond. 

Knowledge 2024 featured hundreds of keynotes, panels, and learning sessions designed to help customers get the most out of ServiceNow’s AI platform for business transformation. Experts from many disciplines provided context for the tech conversations by sharing insights on culture, geopolitics, macroeconomics, and business strategy.   

On the macro front, here are five key takeaways from Knowledge 2024:

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New technology is expanding human intelligence in a time of war, economic shocks, populist rage, and cultural division. All in all, this might be the most revolutionary moment in human history, according to global affairs expert Fareed Zakaria, author of the new book Age of Revolutions and host of the weekly CNN show Fareed Zakaria GPS.

Speaking to a select audience of senior business leaders at Knowledge 2024’s Executive Circle, Zakaria argued that we’re living through simultaneous revolutions in globalization, technology, identity, and geopolitics. All four revolutions were shaped by past periods of economic and social disruption.


The Industrial Revolution turned peasants into workers and moved whole economies from agriculture to factory production. In the late 20th century, the fall of the Berlin Wall and the collapse of the Soviet Union marked a global shift from closed, authoritarian societies to a more open world where people, information, and capital moved freely across national borders.

Today we’re seeing a populist backlash against globalization, a resurgence of authoritarianism in many countries, the rise of identity politics, and a changing geopolitical landscape where the United States is no longer the sole superpower. Zakaria ended his talk on a guardedly optimistic note, arguing that the U.S. still has the power to revitalize the liberal international order. For that to happen, America will first need to fix its dysfunctional political culture. “If we thread that needle, we can have the next American century,” he concluded. “If we fail, it’s up for grabs.” 

This might be the most revolutionary moment in human history.
—Fareed Zakaria

The AI revolution is transforming the relationship between people and machines. At Knowledge 2024, experts from ServiceNow and Pearson presented new research that uses machine learning to predict how AI will change the mix of skills needed for organizations and individuals to succeed in the global economy.

Key findings from the ServiceNow/Pearson study: Despite rising automation, global demand for labor will exceed supply over the next five years. One million additional workers will be needed in the U.S. alone to support projected annual GDP growth of 2.1%. To stay relevant and employed, many workers will need to acquire new skills and even change industries. And as AI takes over more routine tasks, there will be rising demand for uniquely human skills such as critical thinking and creativity. 

Encouragingly, AI can also help people build those human skills, according to Jayney Howson, head of global learning and development at ServiceNow. “AI gives us the ability to upskill at scale,” Howson said during a Knowledge panel discussion on AI skilling. “For example, AI coaches could teach us how to have difficult conversations with our colleagues.” 

At the same time, leaders should not assume AI is a magic wand that can solve all business problems by itself. Instead, they need to do the hard work of deciphering how work gets done inside their organizations, said Gregg Aldana, ServiceNow’s global area vice president for creator workflows. “It starts with journey mapping and understanding work,” Aldana noted during an exclusive Knowledge presentation for senior leaders. “As the saying goes, a fool with a tool is still a fool.”

As AI takes over routine tasks, there will be rising demand for uniquely human skills such as critical thinking and creativity.

Since ChatGPT burst on the scene in late 2022, we’ve heard endless chatter about how generative AI (GenAI) will change everything for everyone, everywhere. At Knowledge 2024, the focus was on practical GenAI applications that provide valuable experiences for customers, employees, and customers to drive business transformation.

ServiceNow’s GenAI solutions focus on three main use cases: intent detection, content creation, and content summarization, said Jon Sigler, senior vice president for Now Platform. Intelligent chatbots, such as ServiceNow’s Now Assist, use intent detection to figure out what a customer or employee really wants even if their questions are vague or imprecise. 

On the content creation front, text-to-code and text-to-flow tools enable developers to boost their productivity using natural language prompts to write software. This vastly improves their productivity: Chief Digital Information Officer Chris Bedi told the Knowledge audience that our engineers have achieved a 48% code acceptance rate from using Now Assist to translate natural language instructions into code. 

Finally, content summarization helps customer and employee service reps by creating pithy, accurate summaries of complex case histories. ServiceNow’s IT service agents are able to close cases in half the time using GenAI-powered incident summarization. And our customer service agents have seen a 10% boost to the customer case deflection rate using GenAI, according to Bedi. A higher deflection rate means more customers get their problems solved immediately via self-service. Meanwhile, agents get more time to work on complex cases that require human judgment. 

Nothing kills a digital experience faster than forcing users to surf multiple applications to get information or perform a task. Yet in modern organizations, employees must “swivel chair” among an average of 13 separate applications to get their daily work done. That soaks up roughly a third of their productivity—one reason why call center turnover rates average 40% per year, according to ServiceNow Chairman and CEO Bill McDermott. “They hate their jobs,” McDermott told the Knowledge audience. 

The better path, McDermott said, is to build intelligence into a single platform, such as the ServiceNow platform, that employees and customers can use to find information and achieve transformative business outcomes. McDermott describes ServiceNow as a “platform of platforms” that connects all the disparate systems of record that modern companies use to run functions such as HR, IT, customer service, and finance.

ServiceNow is no exception, McDermott said. “We have a finance system, an HR system, a CRM system,” McDermott said. “But nobody in our company knows that. They only see ServiceNow.”

Data matters, but wise human decisions matter more. That was the key takeaway from a Knowledge conversation between Bloomberg journalist Emily Chang and author Michael Lewis, whose latest book, Going Infinite, is an unvarnished portrait of the disgraced crypto magnate Sam Bankman-Fried. 

Among other things, Bankman-Fried represents the Platonic ideal of a business leader whose poor judgment trumped his analytic brilliance and access to vast troves of useful data. The same goes for the credulous investors who bought Bankman-Fried’s rumpled savant schtick and funded his doomed cryptocurrency exchange without bothering to kick the tires on its deeply flawed governance model. “Sam’s oddness masked everything,” Lewis said.

We find a more positive example of human judgment in Billy Beane, the subject of Lewis’ 2003 bestseller Moneyball. That book tells the story of how Beane used data analytics to build the Oakland A’s into a baseball powerhouse that routinely beat clubs with far bigger payrolls. 

Especially at a tech industry conference, it’s tempting to attribute Beane’s success exclusively to his ingenious use of sabermetrics to predict which combination of players was most likely to win baseball games. For his part, Beane saw analytics as table stakes. Any general manager could extract insights from data, he told Lewis. In Beane’s opinion, however, few of his baseball peers had the toughness required to make unlikely or even obvious decisions that flew against conventional wisdom. That’s a lesson for leaders in every industry.

Data matters, but wise human decisions matter more.

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Author

Richard McGill Murphy is the editor in chief of Workflow. A journalist and social anthropologist by background, he runs a research and publishing program at ServiceNow that studies how emerging technologies are shaping the future of work.

Articles by Richard McGill Murphy