During my younger freelancing days, I developed what is commonly referred to as a “growth mindset,” which means I am constantly seeking new skills to add to my repertoire. On the plus side, this voracious appetite for learning has helped me expand my expertise. On the minus side, this mindset is often accompanied by an unrelenting sense of insecurity.

It’s a hard way to exist if inner peace is what you seek, but this kind of adaptability may be the key to surviving the new entry-level job market for consulting and finance talent in the age of AI, according to Anne Chow. 

Plus, we see what happens when a social-media algorithm suppresses—rather than amplifies—the most-extreme online views. 

Surfing the entry-level job market … in the age of AI 

AI has upended the market for young consulting and finance talent. But Anne Chow, the former CEO of AT&T Business, sees ample opportunity for professionals willing to adapt their strategy. 

“What we’re actually witnessing is a compression of the traditional career timeline that, navigated intentionally, can accelerate professional growth in ways no previous generation has experienced,” says Chow, a senior fellow and adjunct professor at the Kellogg School. 

For one, employers are recognizing the dangers of choking off their talent pipelines completely, Chow observes, with companies like Reddit and IBM announcing plans to hire more entry-level positions. 

This makes sense. As generational age-out inches closer, Chow notes, companies will need early-career professionals with the neuroplasticity and openness to both grow with the business and serve as more agile catalysts for organizational change. 

People entering the workforce should seek out companies that recognize this need. 

Second, there is a great opportunity for applicants who can hone the skills that AI can’t easily replicate, like relationship building and exercising judgement when the data is ambiguous. “It’s about getting in the door and then, once you’re there, knowing that the first trimester of your career will not be consumed by the tactical as you’d always assumed it would. You must build the skills that create real leverage—storytelling, communication, intellectual and emotional agility, critical thinking, relationship building—from day one,” Chow says. 

Applicants who describe their strategy and objectives in these terms will have an edge over their competition, she says. 

Read more in Kellogg Insight. 

Taking the doom out of scrolling

On social media, it often feels like the loudest and angriest voices dominate the conversation, creating a virtual shouting match that drowns out more-thoughtful opinions.  

Scientists have speculated that these flames are fanned by the engagement-based algorithms social-media networks use to keep users on their platforms. These algorithms exploit a known bias: people tend to pay the most attention to information that is moral, emotional, and relevant to their social group, says Kellogg’s William Brady, an associate professor of management and organizations.  

“Algorithms learn that factor of our psychology, they amplify it, and then it leads to a situation in which our ecosystem is saturated with this information,” he says. 

Brady and a team of colleagues at Kellogg wondered if there was a better way to experience social media. So they built and then compared a new type of algorithm that reduces the influence of the loudest users with an engagement-based algorithm similar to the kind used on major social-media platforms. Then they studied how people responded to both feeds during one of the most fractious moments in recent history: the 2024 U.S. presidential election. 

As they expected, the researchers found that the typical engagement-based feed increased the visibility of the in-group, moral, and emotional content types, particularly after the election. Users on the engagement-based feeds also saw a significant increase in political posts.

By contrast, the researchers’ new algorithm decreased the amount of in-group, moral, and emotional content, as well as the number of toxic and political posts users saw, relative to engagement-based feeds, both before and after the election—even though the algorithm wasn’t specifically told to moderate the content. 

Read more in Kellogg Insight.