AI Natives Are Now Entering the Workforce

Summary

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WSJ Tech News Briefing

Episode: AI Natives Are Now Entering the Workforce

Date: May 29, 2026
Host: Isabel Busquette
Guests: Lisa Ward (WSJ Contributor), Allison Poli (WSJ Reporter), Imani Moise (WSJ Reporter)

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Episode Overview

This episode explores two major themes: the surprising effectiveness of AI in debunking internet conspiracy theories, and the unique position of the "AI native" graduating class of 2026 as they enter a transformed job market. The host, Isabel Busquette, interviews reporter Lisa Ward about new research on "debunk bots," then turns to a discussion with Allison Poli and Imani Moise about how recent graduates—steeped in AI throughout their college years—are navigating both opportunity and uncertainty in a labor market fundamentally reshaped by artificial intelligence.

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1. AI and the Fight Against Misinformation

Guest: Lisa Ward, WSJ Contributor
Timestamps: 01:36 – 04:19

Key Discussion Points

• AI Debunk Bots & Conspiracy Theories:

  • New research demonstrates that large language model-powered "debunk bots" are surprisingly successful at persuading people to abandon conspiracy theories.
    • "Most participants not only changed their minds immediately after the conversation with the AI, but also continued to hold those new views for about two months afterwards." — Lisa Ward [01:51]

• Range of Theories Addressed:

  • Bots tackled a wide spectrum of beliefs, from 9/11 and JFK assassination conspiracies to deeply rooted antisemitic tropes.
    • "They tried all different ones... and they focused on antisemitism because they thought it was, you know, a deeply held belief and they were curious if you could challenge those facts, would it make a difference? And they were surprised it did." — Lisa Ward [02:19]

• Why Is AI Effective?

  • AI models excel by quickly providing an abundance of clear, relevant facts and explaining them in an understandable manner.
    • "These models are great conversationalists and teachers... When you can sometimes just bring an actual fact into it, it's easy to challenge that." — Lisa Ward [02:39]

• The Importance of Tone:

  • Effectiveness drops only when the AI is condescending; neutral or affirming tones work equally well.
    • "It only matters if the AI is condescending. You know, people really didn't like that." — Lisa Ward [03:08]

• Cautions & Limitation:

  • Commercial models differ from research setups; not all are programmed to fact-check, so misinformation risks remain.
    • "With commercial large language models, they're not always given those specific instructions... So it's important to be cognizant of that possibility." — Lisa Ward [03:25]

• Human Takeaways:

  • Effective debunking in human conversation requires marshaling facts and maintaining respect, without condescension or hostility.
    • "If you're going to get a person to engage, you shouldn't insult them, communicate that they're an idiot, or start yelling. It just shuts the conversation down." — Lisa Ward [04:11]

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2. The Class of 2026: Entering an AI-Shaped Workforce

Guests: Allison Poli (WSJ Reporter), Imani Moise (WSJ Reporter)
Timestamps: 06:07 – 10:54

Key Discussion Points

• What Makes the Class of 2026 Unique?

  • Their college journey coincided with the public release and societal normalization of generative AI, leading to mixed messaging: from "this is plagiarism" to "this will land you a job—or take it away."
    • "They kind of in some ways came of age with AI and have developed along with it... Now they're entering the job market at a time when it's all anybody is talking about." — Allison Poli [06:25]

• How Do Graduates Feel About AI?

  • There's pervasive ambivalence: acceptance of AI’s inevitability but also concern over dependence and its effects on critical thinking and future careers.
    • "They recognize there's this inevitability... At the same time, there is this resistance to it where people are concerned about relying on it too much." — Allison Poli [06:58]

• The Employer Perspective:

  • Many employers expect "AI-native" proficiency, making AI use a performance measure in workplaces; companies in tech, finance, HR, and beyond are specifically seeking graduates fluent in AI tools.
    • "Employers are expecting that these students will come in knowing how to use the technology, that they'll be AI native, so to speak." — Allison Poli [07:26]
    • "IBM, MetLife, Salesforce have all said we're really eager to hire people who are AI fluent." — Allison Poli [08:19]

• Reshaping Workplace Hierarchy?

  • While new graduates may have stronger technical fluency, traditional decision-making structures remain intact. Younger employees may guide managers on tools but won’t replace them in leadership quickly.

    • "There's still going to be managers who you have to report to." — Allison Poli [08:56]

  • Need for Closer Oversight:

    • "We can't just say, oh, go out and use these AI tools and come up with something and leave them alone... because they can get so far down a rabbit hole." — Allison Poli, referencing SharkNinja CEO [09:34]

• Looking Ahead—Disrupted or Advantaged?

  • Today's grads face a tougher market but still better than peak-recession classes; entry-level roles are sure to continue evolving, leaving the class of 2026 likely both uniquely advantaged and disrupted.
    • "This will be a class that was advantaged in that they had a decently good market, even though it was still challenging. But things are going to continue to be disrupted in ways that I don't even think are fully realized yet and we can't predict. So maybe both." — Allison Poli [10:44]

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3. Notable Quotes

• On AI as Conversationalist:

  • "These models are great conversationalists and teachers..." — Lisa Ward [02:39]

• On AI's Effect on Workplace Roles:

  • "A lot of employers are all in on AI and people's performance is now graded on how much they use AI at work." — Allison Poli [07:26]

• On Entry-Level Oversight Needs:

  • "We need to check in with these entry level hires more frequently because... they can get so far down a rabbit hole and be going in the wrong direction." — CEO of SharkNinja, as paraphrased by Allison Poli [09:32]

• On Duality of Opportunity and Disruption:

  • "This will be a class that was advantaged... But things are going to continue to be disrupted in ways that I don't even think are fully realized yet and we can't predict. So maybe both." — Allison Poli [10:44]

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4. Key Timestamps for Important Segments

• 01:36 – Research on AI debunking conspiracy theories (Lisa Ward)
• 02:39 – What makes AI effective at persuasion
• 03:08 – Importance of tone in AI conversations
• 04:11 – Human lessons from AI debunking
• 06:07 – What makes the class of 2026 an "AI native" cohort
• 07:26 – Employer expectations of AI fluency
• 08:19 – Expansion of AI fluency requirements beyond tech
• 09:32 – Entry-level autonomy and managerial oversight
• 10:44 – Predictions for the class of 2026: disrupted or advantaged?

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5. Summary Insights

• AI tools, when carefully programmed, can effectively challenge and reduce belief in conspiracy theories by communicating respectfully and offering robust, easily explained facts.
• The graduating class of 2026 is the first truly "AI native" generation, blending both anxiety and adaptability as AI transforms job expectations.
• Employers are increasingly demanding AI skills—but while these grads may outpace their managers in technical proficiency, traditional hierarchies aren’t vanishing overnight.
• The entry-level landscape is rapidly evolving, promising both unique opportunity and unpredictably ongoing disruption for young workers ahead.

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Transcript

[Caroline Roach]

Many companies are struggling to scale their AI deployments or even move them past the pilot stage. Often the problem isn't technology, but organizational misalignment around goals, processes and incentives. At the break, join Caroline Roach, Senior Partner, IBM Consulting, to learn why.

[Isabel Busquette]

Welcome to Tech News briefing. It's Friday, May 29th. I'm Isabel Busquette for the Wall Street Journal. AI is often criticized for spreading misinformation, but it turns out large language models are surprisingly good at talking people out of conspiracy theories. We're diving into why and what we can learn from them. Then here comes the class of AI. This year's college graduates are so called AI natives and they're now set to enter the workforce. We're breaking down how the job market is treating them and whether they're uniquely disrupted or advantaged. But first, new research has found that in some corners of the Internet, AI is helping combat misinformation. So called debunk bots or chatbots designed to fact check conspiracy theories are successfully changing people's minds by generating facts and evidence quickly and presenting it in a clear, understandable way. WSJ contributor Lisa Ward joins us for more on how they do it and what we as humans can learn from them. What does the research show about AI's ability to talk people out of conspiracy theories?

[Lisa Ward]

They're actually pretty good at changing people's minds. In one of the studies, participants discussed conspiracy theories they believed and the researchers asked AI to persuade participants that those theories weren't true. Most participants not only changed their minds immediately after the conversation with the AI, but also continued to hold those new views for about two months afterwards.

[Isabel Busquette]

What types of conspiracy theories did it talk people out of in that study?

[Lisa Ward]

All types of conspiracy theories from 911 to Kennedy's assassination to conspiracies based on anti Semitic tropes. In one study where the bunk bot talked people out of anti Semitic conspiracy theories, participants actually saw Jewish people more favorably afterwards. So it wasn't based on a specific conspiracy theory. They tried all different ones and I think they focused on antisemitism because they thought it was, you know, a deeply helpful belief and they were curious if you could challenge those facts, would it make a difference? And they were surprised it did.

[Isabel Busquette]

So what is it that makes the AI so good at this?

[Lisa Ward]

The primary reason the model is effective is its ability to come up with lots of relevant facts and evidence and then explain it in a clear, easily understandable way. These models are great conversationalists and teachers. When you go back to a lot of conspiracy theories, ultimately they often don't make sense. So when you can sometimes just bring an actual fact into it, it's easy to challenge that.

[Isabel Busquette]

Does the tone that the AI is talking to the person in matter at all here?

[Lisa Ward]

It only matters if the AI is condescending. You know, people really didn't like that. But there is no difference in effectiveness between a neutral or affirming debunk bot.

[Isabel Busquette]

You know, this is a great use case. But are there also concerns that AI could further perpetrate misinformation or conspiracy theories?

[Lisa Ward]

Yeah. So in these studies, the debunk bots were instructed to really challenge conspiracy theories, but with commercial large language models, they're not always given those specific instructions. So it's unclear to what extent these models are going to correct you. So it's important to be cognizant of that possibility.

[Isabel Busquette]

So what can we as humans learn from this? About the best way we could maybe talk each other out of conspiracy theories?

[Lisa Ward]

I mean, being able to marshal a lot of facts and evidence to refute conspiracy theories is really important. Of course, that can be difficult. Often conspiracy theorists will say, what about this piece of evidence or that piece of evidence? And you need to be able to have an answer for each of those things. And that can be difficult to do. Also, some pretty basic manners matter, too. If you're going to get a person to engage, you shouldn't insult them, communicate that they're an idiot, or start yelling. It just shuts the conversation down.

[Isabel Busquette]

That was WSJ contributor Lisa Ward. What are some other ways you've used large language models? If you're a listener on Spotify, leave us a comment with your answer. Coming up throughout their college careers, the class of 2026 has received a lot of mixed messaging about AI. How's it impacting them as they enter the workforce? That's after the break.

[Caroline Roach]

Delivering real business results with AI starts with organizational alignment, says Caroline Roach, senior partner, IBM Consulting.

You need to understand what problem you're solving, really commit yourself to it, and then be clear on how you're going to change the way you work to deliver those outcomes. With AI as a tool, but not the only tool.

If deployments aren't optimized to how work gets executed, ROI can suffer as programs stall and adoption lags.

Alignment is difficult to achieve because people are rushing to a solution without first defining the problem.

[Isabel Busquette]

It's graduation season, but the class of 2026 is entering one of the toughest job markets for young college graduates in years. Young adults are facing elevated unemployment rates as companies are increasingly using AI to handle the entry level tasks that once served as career launch pads. Still, more than any other age group, young, young graduates say they feel prepared to compete in an AI shaped job market. And many employers say this graduating class brings a unique set of skills that could actually give them an edge. WSJ reporter Allison Poli joined our colleague Imani Moise to talk about what this moment means for the future of work.

[Imani Moise]

You spoke to several graduating seniors for this story. What's unique about the class of 2026?

[Allison Poli]

So they were in their first semester of freshman year when ChatGPT was released to the public. And then as they progressed through college, AI went from being something that they were told don't use, it's cheating, it's plagiarism, to something they were encouraged to use. And then we're told this is either going to help you get a job or it's going to take away all the job opportunities that you thought you had. So what's interesting about the class of 2026 is they kind of in some ways came of age with AI and have developed along with it over the past few years. And now they're entering the job market at a time when it's all anybody is talking about.

[Imani Moise]

How would you sum up their feelings towards AI?

[Allison Poli]

There's an ambivalence, I think some of them recognize that there's this inevitability where the cat's out of the bag. It's going to be an expectation in the workplace. At the same time, there is this resistance to it where people are concerned about relying on it too much. They're worried about what it will do to their critical thinking and what it will even mean for their careers going forward.

[Imani Moise]

And how does that compare with the way employers are thinking about AI right now?

[Allison Poli]

A lot of employers are all in on AI and people's performance is now graded on how much they use AI at work. various financial firms and other companies, the employers are expecting that these students will come in knowing how to use the technology, that they'll be AI native, so to speak. And so it's a skill that certain companies, like Salesforce for example, are looking for very specifically in the entry level hires that they're bringing on.

[Imani Moise]

What companies are most eager to hire these AI native grads? Is it mostly happening in tech or are you seeing it spread across more industries?

[Allison Poli]

It's definitely happening in tech, but I talked to some students who were applying for jobs in graphic design and in HR and they're job postings. It said familiarity with AI tools as one of the requirements. So it is across the board. But there are notable companies. IBM, MetLife, Salesforce have all said we're really eager to hire people who are AI fluent. Consulting firms like McKinsey say they're increasing hiring as well.

[Imani Moise]

It sounds like a lot of these grads might be more fluent in AI tools than their managers. Did you get the sense that this could reshape traditional workplace hierarchies?

[Allison Poli]

I think there will be a reshuffling of roles and what we traditionally think of as certain jobs. But I don't know about the hierarchy because at the end of the day, you still need somebody who's going to be making a decision and making that judgment call. And just because someone can use a tool or is more fluent in helping someone get familiar with the technology doesn't mean they're in a position where they can be making the final call on a client facing project or anything like that. There's still going to be managers who you have to report to.

[Imani Moise]

It kind of reminds me of being a teenager in the 2010s, and social media is becoming a phenomenon. And honestly, my parents didn't know what I was doing on the computer. I could have been doing anything.

[Allison Poli]

Yep.

[Imani Moise]

Are you expecting some of that to happen in the workplace as well?

[Allison Poli]

Yeah, and I think that was something that came up in one of the interviews we did with the CEO of SharkNinja where he was basically saying we need to check in with these entry level hires more frequently because we can't just say, oh, go out and use these AI tools and come up with something and leave them alone for one to two weeks because they can get so far down a rabbit hole and be going in the wrong direction that it's like, oh no, we just spent two weeks working on something that was totally irrelevant.

[Imani Moise]

Five or ten years from now, do you think we'll look back on the class of 2026 as uniquely disrupted or uniquely advantaged?

[Allison Poli]

You know, when I was looking at the recent graduate unemployment Data, compared to 2020 and 2008, it's not as high as those two time periods. Even though entry level grads are struggling to find jobs, a lot of employers are saying, we're not going to slow down on entry level hiring. We still need these graduates. But in five to 10 years, entry level hiring will look super different. I think this will be a class that was advantaged in that they had a decently good market, even though it was still challenging. But things are going to continue to be disrupted in ways that I don't even think are fully realized yet and we can't predict. So maybe both.

[Isabel Busquette]

That was WSJ reporter Allison Poley speaking with our colleague Imani Moise. And that's it for Tech News Briefing. If you're a listener on Spotify, be sure to leave us a comment. Today's show was produced by Julie Chang. I'm your host. Isabel Bousquet, Jessica Fenton and Michael Lavalle wrote our theme music. Our supervising producer is Katie Ferguson. Our development producer is Aisha Al Muslim, and Chris Dinsley is the deputy editor of audio for the Wall Street Journal. We'll be back later this morning with the TNB Tech Minute. Thanks for listening.

[Caroline Roach]

Scaling AI successfully requires more than the right technology Here again is Caroline Roach, Senior Partner, IBM Consulting.

The biggest thing that we were talking about a year ago is what model to use, and the biggest thing that I'm talking about with my clients now is how do I drive change within my organ companies?

Able to identify correct and then avoid misalignment will be best positioned to deliver meaningful business value from AI.

The organizations that are the most successful set very clear targets and have several priorities that are very clear across the enterprise. The technology is really good, but if you're not changing your organizational alignment, not incentivizing your people correctly, not looking at workflows, you're not going to see real value with it.

Visit IBM.com think leadership to learn how building organizational alignment can help deliver AI deployments that scale and drive growth.

[Isabel Busquette]

This content was created by custom content from WSJ, a unit of the Wall Street Journal Advertising department.