New Grads are 1.5x More Likely to Use AI Daily. Here’s Why That Matters for Your Hiring Strategy.

You’re investing in AI tools. Who on your team actually knows how to use them? The answer might be the people you’ve stopped hiring.

At Big Tech and startups, the share of hires with one year or less experience is down 50% from pre-pandemic levels. The logic may seem sound: AI automates the routine work that junior roles used to handle, so why keep hiring for them?

Here’s the problem with that perspective: many of the companies pulling back on new-grad hiring are also struggling to get AI adoption past the pilot stage. New research from Atlassian’s Teamwork Lab suggests those two things may be connected.

New grads don’t just use AI. They use it differently.

Most organizations are still trying to get their teams to use AI consistently. Our research finds that those newest to the workforce are already there, and they’re using AI more effectively.

Atlassian’s Teamwork Lab analyzed AI usage data among engineering new hires at Atlassian alongside external survey data from the AI Collaboration Index covering over 560 tech workers across the broader industry. The findings were consistent across both datasets:

Across the tech industry (ages 21–24 vs. 25+):

• 1.5x more likely to be daily AI users
• 1.7x more likely to treat AI as a creative partner or expert advisor
• 2.1x more likely to use AI to enhance decision making

Inside Atlassian (engineering new grads vs. other new engineering hires):

• 19% more likely to be AI superusers
• 15% more AI tools used weekly, supplementing standard Atlassian tools with AI platforms like LLM Playground and RovoLab
• 1.8x as likely to spend an hour or more per day experimenting with AI

New grads enter the workforce versed in this technology. In our research, we found that means they’re more likely to iterate and experiment across tools. And when AI gives an unhelpful response, new grads are markedly less likely to give up. That persistence, treating AI as a collaborator rather than a vending machine, is what separates teams that get real value from AI from those that don’t.

The entry-level job market is cyclical. The AI skills gap isn’t.

It’s worth separating two trends that are often conflated; the decline in entry-level tech roles and the rise of AI.

The entry-level hiring decline began in early 2022, driven by interest rate hikes and tightening budgets — months before ChatGPT launched. While many think that AI accelerated the shift, it wasn’t the root cause. And the same forecasts that track the decline point to a rebound: the U.S. Bureau of Labor Statistics projects software and data roles growing 8–18% over the next decade, well above the 4% average across all occupations.

Meanwhile, AI talent demand is already outstripping supply. AI-related software job postings grew 31.7% annually from 2015 to 2022, while related bachelor’s degrees grew just 8.2%. AI hiring surged 17–33% year-over-year across the U.S., India, and Australia in 2024 alone.

Today’s hiring freeze will end, and the AI skills shortage will become more pronounced. Without considering new grads now, you’ll be behind on both headcount and skills when the market improves.

There’s a catch — and it’s a management problem, not a talent problem

The research surfaced one finding that deserves extra attention. Outside Atlassian, younger tech workers are 38% more likely to conceal their AI use from managers and teammates (40% vs. 29%).

They’re not hiding it because they don’t know what they’re doing. They’re hiding it because they’ve learned (from academic integrity debates, from workplace culture, and from unclear policies) that using AI can be perceived as cutting corners.

“This is a missed opportunity,” says Sami Nesnidol, a Teamwork Lab researcher. “When AI experimentation stays hidden, teams can’t learn, improve, or govern it. The most valuable thing about new grads’ AI fluency isn’t just what they produce individually, it’s the workflows and tool discoveries they can share across a team.”

The bottom line: Now is the time to “buy the dip” in new grad talent

Universities are catching up fast. The number of U.S. institutions offering AI bachelor’s programs more than doubled in 2025, with similar expansion in Canada, India, and Australia. And 92% of undergrads now report using AI in some form, up from 66% a year ago.

The next wave of grads will arrive with structured AI experience, and the best among them will already be tied to the companies that invested early.

“The question isn’t whether to invest in new-grad hiring,” says Teamwork Lab researcher Erica Messner. “It’s whether you’ll do it now, while the market is soft and the talent is accessible, or later, when it’s expensive and everyone else is scrambling.”

The data is clear: new grads are your most willing, most persistent, and most experimental AI users. They don’t need to be convinced to adopt AI, but they do need the support to use it well. That’s a solvable problem if you get ahead of the game today.

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Methodology: To investigate AI habits in the tech industry, the Teamwork Lab used external survey data from Atlassian’s AI Collaboration Index. We compared the self-reported AI sentiment and use of young tech workers (ages 21-24) to that of other Tech ICs (ages 25+) across the broader Dev/IT industry. Key measures included frequency and depth of AI use, most common use cases, persistence in using AI after unhelpful responses, concealment of AI use, and perceived impact of AI and effort required.

Within Atlassian, we analyzed AI usage data among engineering new grads compared with other engineering ICs. Atlassian employee survey responses were used to supplement findings. Key measures included observed AI use, including weekly AI usage, AI superuser status, and variety of AI tools used, alongside self-reported AI sentiment and use.

We then conducted 40-minute semi-structured interviews with 10 Atlassian new grads to investigate how AI is affecting early career experiences, goals and perspectives. Participants were primarily software engineers (8) with 2 non-engineers, from North America (5), Australia (3) and India (2). All graduated college between late 2024 and mid-2025. Most (8) interned with Atlassian prior to hire.