Hello and welcome to Eye on AI. In this edition… a call to action on AI’s catastrophic risks from Anthropic CEO Dario Amodei… more AI insights from the World Economic Forum in Davos… another investment in CoreWeave… Anthropic mapping the source of an AI model’s helpful personality.
Hello, I’ve just returned from covering the World Economic Forum in Davos, Switzerland. Last week, I shared a few on – the – ground insights from Davos. I’ll try to share more thoughts from my conversations below.
But first, the hot topic in the AI world over the past day has been the 20,000 – word essay that Anthropic CEO Dario Amodei released on Monday. Titled The Adolescence of Technology and published on Amodei’s personal [platform], the piece contained several warnings that Amodei had issued before. However, in the essay, Amodei used slightly more severe language and mentioned shorter timeframes for some of AI’s potential risks than he had in the past. What’s truly notable and new about Amodei’s essay are some of the solutions he proposes to these risks. I’ll attempt to break down these points [later].
One thing Amodei said in his essay is that 50% of entry – level white – collar jobs will be eliminated within one to five years because of AI. He said the same thing at Davos last week. But when talking to C – suite leaders there, I got the impression that few of them agree with Amodei’s prediction.
Amodei has been inaccurate about the rate at which technology spreads to non – AI companies before. Last year, he predicted that up to 90% of code would be written by AI by the end of 2025. It seems that this was actually true for Anthropic itself, but not for most companies. Even at other software companies, the proportion of AI – written code has been between 25% and 40%. So Amodei may have a distorted view of how quickly non – tech companies can actually adopt technology.
AI may create more jobs than it destroys
Moreover, Amodei may be wrong about AI’s impact on jobs for several reasons. Scott Galloway, a marketing professor, business influencer, and tech investor, who spoke at [company]’s Global Leadership Dinner in Davos, said that every previous technological innovation had always created more jobs than it destroyed, and he saw no reason to think AI would be different. However, he did admit that there might be some short – term displacement of existing workers.
And so far, that appears to be the case. I also had an interesting conversation with several senior [company] executives. Srinivas Tallapragada, the company’s chief engineering and customer success officer, told me that while AI did lead to role changes at the company, Salesforce was also investing heavily to reskill people for roles, many of which involve 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 transfer some customer support agents, who used to work in traditional contact centers, to become “forward deployed engineers” under Tallapragada’s organization, where they work on – site with Salesforce customers to help deploy AI agents.
Meanwhile, Ravi Kumar, the CEO of Cognizant, told me that unlike many businesses that have reduced their hiring of junior employees, Cognizant is hiring more entry – level graduates than ever. Why? Because they are generally faster and more adaptable learners who either already have AI skills or can 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 [field 1], [field 2], and finance—seem to suggest that it’s often the most experienced professionals who benefit the most from AI tools because they have the judgment to more quickly assess the strengths or weaknesses of an AI model’s or agent’s work. They’re also better at writing highly specific prompts to guide a model to a better output.
Kumar was intrigued by this. He said that organizations also need experienced employees because they are excellent at “problem finding,” which he says is the most important role for humans in organizations as AI starts to take on more “problem – solving” roles. “You get the opportunity to do problem finding because you know how to solve problems right now,” he said about experienced employees.
Opening up whole new markets
Raj Sharma, EY’s global managing partner for growth and innovation, told me that AI is enabling his firm to target entirely new market segments. For example, in the past, [company] couldn’t economically pursue a lot of tax work for mid – market companies. These are businesses that are complex enough to still require expertise, but they can’t pay the prices that larger enterprises, with even more complex tax situations, can. So the profit margins weren’t good enough for EY to take on those projects. But now, thanks to AI, EY has developed AI agents that can assist a smaller team of human tax experts to effectively serve these customers with profit margins that are viable for the firm. “People thought, it’s tax, it’s the same market, if you switch to AI, people will lose their jobs,” Sharma said. “But no, now there’s a new $6 billion market that we can target 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 achieving significant ROI from AI. First, companies need to completely reinvent their workflows, not just try to automate a few parts of the existing ones. Second, they need to understand context engineering—how to provide AI agents with the data, information, and tools to successfully complete tasks. Third, they have to create organizational structures designed to integrate and manage both AI agents and humans. And finally, companies need a skills development infrastructure—a process to ensure that their employees know how to use AI effectively, as well as 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.
The key point here is that none of these steps is easy to achieve. All require significant investment, time, and most importantly, human creativity to get right. But Kumar believes that if companies get this right, there are $4.5 trillion worth of productivity gains waiting to be realized in the U.S. alone. He said these gains could be achieved even if AI models never become more capable than they are today.
One more thing: My colleague Allie Garfinkle, who writes the Term Sheet newsletter, has an excellent profile in the latest issue of [magazine] about [company] AI boss Demis Hassabis’ side project of running Isomorphic Labs. The mission is nothing less than using AI to “solve” all diseases.
Ok, with that, here’s more AI news.
Jeremy Kahn
@jeremyakahn
[Company]’s Beatrice Nolan wrote the news and research sections of this newsletter below. Jeremy wrote the Brain Food item.