Hello and welcome to Eye on AI. In this edition…Anthropic CEO Dario Amodei’s call to action on AI’s catastrophic risks…more AI insights from the World Economic Forum in Davos…Nvidia makes another investment in CoreWeave…Anthropic maps the source of AI model’s helpful personality.
Hello, I’m just back from covering the World Economic Forum in Davos, Switzerland. Last week, I shared a few insights from on the ground in Davos. I’m going to try to share some more thoughts from my conversations below.But, first, the talk of the AI world over the past day has been the 20,000-word essay that Anthropic CEO Dario Amodei dropped Monday. The piece, titled The Adolescence of Technology and published on Amodei’s personal blog, contained a number of warnings Amodei has issued before. But, in the essay, Amodei used slightly starker language and mentioned shorter timelines for some of AI’s potential risks than he has in the past. What’s actually notable and new about Amodei’s essay is some of the solutions he proposes to these risks. I try to unpack these points here.
One thing Amodei said in his essay is that 50% of entry level white collar jobs will be eliminated within one to five years due to AI. He said the same thing at Davos last week. But, talking to C-suite leaders there, I got the sense that few of them concur with Amodei’s prognostication.Amodei has been off about the rate at which technology diffuses into non-AI companies before. Last year, he projected that up to 90% of code would be AI-written by the end of 2025. It seems that this was, in fact, true for Anthropic itself. But it was not true for most companies. Even at other software companies, the amount of AI-written code has been between 25% and 40%. So Amodei may have a skewed sense for how quickly non-tech companies are actually able to adopt technology.
AI may create more jobs than it destroys
What’s more, Amodei may be off about AI’s impact on jobs for a number of reasons. Scott Galloway, the marketing professor, business influencer and tech investor, who spoke at Fortune’s Global Leadership Dinner in Davos said that every previous technological innovation had always created more jobs than it destroys and that he saw no reason to think AI would be any different. He did allow, though that there might some short-term displacement of existing workers.And so far, that seems to be the case. I also had an intriguing conversation with several senior Salesforce executives. Srinivas Tallapragada, the company’s chief engineering and customer success officer, told me that while AI did result in changing roles at the company, Salesforce was also investing heavily to reskill people for roles, many of them working alongside AI technology. In fact, 50% of the company’s hires last year were internal candidates, up from a historical average of 19%. The company has been able to shift some customer support agents, who used to work in traditional contact centers, to be “forward deployed engineers” under Tallapragada’s organization, where they work with Salesforce customers on-site to help deploy AI agents.Meanwhile, Ravi Kumar, the CEO of Cognizant, told me that contrary to many businesses that have cut back on hiring junior employees, Cognizant is hiring more entry-level graduates than ever. Why? Because they are generally faster, more adaptable learners who either come with AI skills or quickly learn them. And with the help of AI, they can be as productive as more experienced employees.
I pointed out to Kumar that a growing number of studies—in fields as diverse as software development, legal work, and finance—seem to suggest that it is often the most experienced professionals who get the most out of AI tools because they have the judgment to more quickly guauge the strengths or weaknesses of an AI model’s or agent’s work. They also can be better at writing highly-specific prompts to guide a model to a better output.Kumar was intrigued by this. He said organizations also needed experienced employees because they excelled at “problem finding,” which he says is the most important role for humans in organizations as AI begins to take on more “problem solving” roles. “You get the license to do problem finding because you know how to solve problems right now,” he said of experienced employees.
Opening up whole new markets
Raj Sharma, EY’s global managing partner for growth and innovation, told me that AI was enabling his firm to go after whole new market segments. For instance, in the past, EY could not economically pursue a lot of tax work for mid-market companies. These are businesses that are complex enough that they still require expertise, but they couldn’t pay the kinds of prices that bigger enterprises, with even more complex tax situations, could. So the margins weren’t good enough for EY to pursue those engagements. But now, thanks to AI, EY has built AI agents that can assist a smaller team of human tax experts to effectively serve these customers with profit margins that make sense for the firm. “People thought, it’s tax, it’s the same market, if you go to AI, people will lose their jobs,” Sharma said. “But no, now you have a new $6 billion market that we can go after without firing a single employee.”
What ROI from AI in existing business lines?
Kumar, the CEO of Cognizant, told me that he sees four keys to realizing significant ROI from AI. First, companies need to reinvent all of their workflows, not simply try to automate a few pieces of existing ones. Second, they need to understand context engineering—how to give AI agents the data, information, and tools to accomplish tasks successfully. Third, they have to create organizational structures designed to integrate and govern both AI agents and humans. And finally, companies need a skilling infrastructure—a process to make sure their employees know how to use AI effectively, but also a retraining and career development pipeline that teaches workers how to perform new tasks and functions as AI automates existing tasks and transforms existing workflows.What’s key here is that none of these steps is simple to accomplish. All take significant investment, time, and most importantly, human ingenuity to get right. But Kumar thinks that if companies get this right, there is $4.5 trillion worth of productivity gains waiting to be grabbed in the U.S. alone. He said these gains could be realized even if AI models never become any more capable than they are today.
One more thing: My colleague Allie Garfinkle, who writes the Term Sheet newsletter, has a great profile in the latest issue of Fortune magazine about Google AI boss Demis Hassabis’ side gig running Isomorphic Labs. The mission is nothing less than using AI to “solve” all disease. Read it here. Ok, with that, here’s more AI news.
Jeremy Kahnjeremy.kahn@fortune.com@jeremyakahn
Fortune’s Beatrice Nolan wrote the news and research sections of this newsletter below. Jeremy wrote the Brain Food item.
This story was originally featured on Fortune.com
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