生成式AI对人才、技术与人力资本的影响

TABLE OF CONTENTS INTRODUCTION: THE IMPACT OF GENERATIVE AI ONTALENT, TECHNOLOGY, AND HUMAN CAPITAL David Francis, VP, Research, Talent Tech Labs PEOPLELED AND TECHNOLOGYPOWERED:WALMART’S GENERATIVE AI JOURNEY Ben Peterson, Global Leader of People Product, WalmartMackenzi Crank, Group Director of People Strategy & Innovation, Walmart A CONVERSATION WITH JOHN DICKERSON John Dickerson, Co-Founder & Chief Scientist, Arthur.ai GENERATIVE AI IN HIRING: BUILD TRUSTBEFORE BUSINESS IMPACT Emre Kazim, Co-Founder & Co-CEO, Holistic AI COPILOTS IN ACTION PhenomEightfoldSense NAVIGATING A GEN AI FUTURE David Francis, VP, Research, Talent Tech Labs The Impact of Generative AI on Talent,Technology, and Human Capital By David Francis, VP, Research, Talent Tech Labs Nobel Prize winning economist Paul Krugman predicted in 1995 (infamous for being completely wrong) that “The growthof the Internet will slow drastically, as the flaw in ‘Metcalfe’s law’—which states that the number of potentialconnections in a network is proportional to the square of the number of participants—becomes apparent: most peoplehave nothing to say to each other! By 2005 or so, it will become clear that the Internet’s impact on the economy hasbeen no greater than the fax machine’s.” The internet went on to become largely responsible for transforming how welive, shop, interact and consume information, not to mention its role in disrupting entire industries and reshaping thebusiness climate. Krugman's sentiment, while funny in hindsight, shows how difficult it can be to see in advance thefull magnitude of technological shifts. Today we are in the first inning of another generation-defining breakthroughin technology that will similarly reshape business and society and have animpact as large (and likely as yet unpredicted) as the introduction of theinternet. That breakthrough is generative AI. It is the closest we’ve come to computers being able to “think,” “reason,” “create,”take instructions and “work” on a human level across any domain. But wait. We’ve had “artificial intelligence” for decades. Why is this particular flavor so much different? Artificial intelligence has been a field of research since the 1950s, and its history has been marked by periods ofsuccessive hopes and disappointments in the 1980s, 1990s, and the 2010s. Generative AI, which was pioneered by ateam of Google Researchers in 2017 and “productized” by OpenAI’s launch of ChatGPT (which became the fastestgrowing consumer product in human history), is unique in that it is a.) universally accessible by consumers anddevelopers, b.) really good at complex cognitive tasks across domains. The success of early generative AI applications has led to a flood of investment in companies and underlyinginfrastructure. Microsoft has poured more than $10 billion into Open AI. Google and Amazon have committed acombined $6 billion in Anthropic (while Google continues to develop its own models). Facebook is investing upwards of$10 billion building the world’s largest array of graphics processors in the world (the chips that power AI applications)while NVIDIA has ballooned to a $1.7 trillion dollar market cap designing and selling such chips to everyone. AI “wars”are being fought across multiple fronts: underlying large language models (which software and application developersrely on), open source versus proprietary, computing power and technical infrastructure (which are the “rails” on whichAI runs), and the business applications that use generative AI to drive results. McKinsey predicts that half of work will be automated by generative AI in the next three to four decades, whileGoldman Sachs estimates it will increase global GDP by $7 trillion. Open AI founder Sam Altman wrote an articleproposing Universal Basic Income and a land / equity tax to address the disruption he foresees in the job market as aresult of human-capable AI. CEOs, CTOs, and CIOs across the world are demanding their teams figure this out andbuild use cases. As a result, nearlyevery industry is wrestling with how to best leverage generative AI to drive results, and the talentindustry is no exception.In this issue of the Trends Report, we unpack the use of generative AI across HR and talentacquisition. It is a look at what is in the market or coming to market from those who are actually building it. We begin with a case study led by Ben Peterson, Head of People Product, and Mackenzi Crank, Global Strategy andInnovation Lead, from Walmart, the largest employer in the US (and one of the largest in the world), about how theWalmart team built and launched an HR co-pilot with generative AI in 60 days. Walmart is on a journey to reimagineassociate and candidate experiences, and employers large and small alike can learn from Walmart’s journey andmethodology for not just embracing innovation but executing on its vision and getting organizational alignment fromthe CHRO down. We then have a broad-ranging interview wit