AI Research
First-of-its-kind Stanford study: AI is starting to have a ‘significant and disproportionate impact’
Stanford University has published a first-of-its-kind study on Tuesday that reveals “the AI revolution” is already beginning to have a “significant and disproportionate impact on entry-level workers in the U.S. labor market,” especially those ages 22 to 25 in highly AI-exposed professions like software engineering and customer service.
The research, led by Erik Brynjolfsson, a top economist and AI thought leader of sorts, analyzed high-frequency payroll records from millions of American workers, generated by ADP, the largest payroll software firm in the U.S. The analysis revealed a 13% relative decline in employment for early-career workers in the most AI-exposed jobs since the widespread adoption of generative-AI tools, “even after controlling for firm-level shocks.” In contrast, employment for older, more experienced workers in the same occupations has remained stable or grown.
The study highlighted six facts that Brynjolfsson’s team believe show early and large-scale evidence that fits the hypothesis of a labor-market earthquake headed for Gen Z.
1) Entry-level workers hit hardest
First, employment disruption is not happening evenly across the workforce. The largest declines are concentrated among young, entry-level workers—those whose skills are most easily replaced by AI systems automating routine, codified tasks. The report says experience and tacit knowledge are becoming crucial buffers against displacement as AI tools excel at replacing book learning over job-specific, hard-to-codify skills.
The report says it’s uncovered “substantial” declines in employment, especially for workers ages 22 to 25. This dovetails with mounting evidence from investment banks and surveys of layoff announcements, as Goldman Sachs has calculated a shrinking premium from a college degree, implying that entry-level workers are struggling to differentiate themselves in this hiring climate. Bank of America Global Research, meanwhile, has noted that since 2022, the unemployment rate for recent graduates has started to exceed the overall unemployment rate for the first time in recent memory.
2) A fading pattern since 2022
Second, the study finds fewer young people are being hired into AI-exposed occupations, with employment growth for young workers stagnant since late 2022—consistent with BofA’s analysis of census data.
In jobs less exposed to AI, the study says, young workers have experienced comparable employment growth to older workers. In contrast, entry-level workers in the occupations most exposed to AI have experienced a 6% decline in employment from late 2022 to July 2025, while older workers have seen 6% to 9% growth. The results suggest that the AI revolution is driving “tepid” overall employment growth for workers ages 22 to 25, the study adds.
3) Automation vs. augmentation
An important distinction is that not every use case for AI is leading to a decline in employment, the data suggests. The negative impacts are concentrated in fields where AI is more likely to automate tasks rather than augment work, and occupations with mainly augmentative AI applications have not seen similar declines in entry-level hires.
The team says it distinguished between automation and augmentation “empirically,” using estimates of the extent to which observed queries either substitute or complement for tasks in a given occupation. “These findings are consistent with automative uses of AI substituting for labor while augmentative uses do not,” the authors write.
This is similar to a line adopted by Joshua Wöhle, CEO of Mindstone, a firm that provides AI upskilling services to workforces. “We’re near the point where [AI is] more intelligent than most people doing knowledge work. But that’s precisely why augmentation beats automation,” Wöhle wrote on LinkedIn about his experiences with AI retraining. And Eric Vaughan, CEO of IgniteTech, took the drastic step of laying off nearly 80% of his company in 2023, telling Fortune that he didn’t do so because he wanted fewer workers, but because his team was not augmenting their work with AI tools fast enough.
4) Sturdiness
Stanford’s analysis rules out several other explanations, such as COVID-era disruptions or interest rate shocks. The effects only emerged after late 2022, coinciding with rapid generative-AI adoption, and are not limited to computer-related jobs, the authors write, stating the robustness of these findings as significant.
For workers ages 22 to 25, researchers say they found a decline in relative employment for the most AI-exposed quintiles compared to the least exposed quintile, a “large and statistically significant effect.” Other age groups had much smaller and statistically insignificant estimates, on the other hand.
5) Employment, not wages
Fears of collapsing income related to AI may be overblown, the study says, finding that the adjustment in the labor market is happening largely through decreased employment rather than lower wages. Pay rates have not shifted dramatically, according to Stanford, with “little difference in annual salary trends by age or exposure quintile, suggesting possible wage stickiness.” If this is true, they write, AI may have larger effects on employment than on wages, at least to begin with.
6) Widespread consistency
Finally, the Stanford team argues these facts are largely consistent across various samples, with patterns in the data appearing “most acutely starting in late 2022, around the time of rapid proliferation of generative AI tools.”
The authors caution that while these findings are early, their large-scale, real-time dataset provides some of the first direct empirical evidence that AI is shifting job opportunities away from America’s entry-level workers. The study repeatedly stresses it is assessing the beginning of what it calls the “AI revolution,” but the much-publicized economic anxiety among Gen Z is beginning to show up in employment data confirming that yes, something is going on here.
The National Science Foundation plans to award up to $35 million to establish an operations center for its National AI Research Resource, signaling a step toward the pilot becoming a more permanent program.
Despite bipartisan support for the NAIRR, Congress has yet to authorize a full-scale version of the resource designed to democratize access to tools needed for AI research. The newly announced solicitation indicates the project is taking steps to scale the project absent additional support.
“The NAIRR Operating Center solicitation marks a key step in the transition from the NAIRR Pilot to building a sustainable and scalable NAIRR program,” Katie Antypas, who leads NSF’s Office of Advanced Cyberinfrastructure, said in a statement included in the announcement.
She added that NSF looks forward to collaborating with partners in the private sector and other agencies, “whose contributions have been critical in demonstrating the innovation and scientific impact that comes when critical AI resources are made accessible to research and education communities across the country.”
The NAIRR began as a pilot in January 2024 as a resource for researchers to access computational data, AI models, software, and other tools that are needed for AI research. Since then, the public-private partnership pilot has supported over 490 projects in 49 states and Washington, per its website, and is supported by contributions from 14 federal agencies and 28 private sector partners.
As the pilot has moved forward, lawmakers have attempted to advance bipartisan legislation that would codify the NAIRR, but those bills have not passed. Previous statements from science and tech officials during the Biden administration made the case that formalization would be important as establishing NAIRR fully was expected to take a significant amount of funding.
In response to a FedScoop question about funding for the center, an NSF spokesperson said it’s covered by the agency’s normal appropriations.
NAIRR has remained a priority even as the Trump administration has sought to make changes to NSF awards, canceling hundreds of grants that were related to things like diversity, equity and inclusion (DEI) and environmental justice. President Donald Trump’s AI Action Plan, for example, included a recommendation for the NAIRR to “build the foundations for a lean and sustainable NAIRR operations capability.”
According to the solicitation, NSF will make an award of a maximum of $35 million for a period of up to five years for the operations center project. That award will be made to a single organization. That awardee would ultimately be responsible for establishing a “community-based organization,” including tasks such as establishing the operation framework, working with stakeholders, and coordinating with the current pilot project functions.
The awardee would also be eligible to expand their responsibilities and duties at a later date, depending on factors such as NAIRR’s priorities, the awardee’s performance and funding.
AI Research
Top AI Code Generation Tools of 2025 Revealed in Info-Tech Research Group’s Emotional Footprint Report
The recently published 2025 AI Code Generation Emotional Footprint report from Info-Tech Research Group highlights the top AI code generation solutions that help organizations streamline development and support innovation. The report’s insights are based on feedback from users on the global IT research and advisory firm’s SoftwareReviews platform.
TORONTO, Sept. 3, 2025 /PRNewswire/ – Info-Tech Research Group has published its 2025 AI Code Generation Emotional Footprint report, identifying the top-performing solutions in the market. Based on data from SoftwareReviews, a division of the global IT research and advisory firm, the newly published report highlights the five champions in AI-powered code generation tools.
Info-Tech Research Group’s 2025 AI Code Generation Emotional Footprint report identifies leading solutions that enable organizations to accelerate development and drive innovation. (CNW Group/Info-Tech Research Group)
AI code generation tools make coding easier by taking care of repetitive tasks. Instead of starting from scratch, developers get ready-made snippets, smoother workflows, and support built right into their IDEs and version control systems. With machine learning and natural language processing behind them, these tools reduce mistakes, speed up projects, and give developers more room to focus on creative problem solving and innovation.
Info-Tech’s Emotional Footprint measures high-level user sentiment. It aggregates emotional response ratings across 25 proactive questions, creating a powerful indicator of overall user feeling toward the vendor and product. The result is the Net Emotional Footprint, or NEF, a composite score that reflects the overall emotional tone of user feedback.
Data from 1,084 end-user reviews on Info-Tech’s SoftwareReviews platform was used to identify the top AI code generation tools for the 2025 Emotional Footprint report. The insights support organizations looking to streamline development, improve code quality, and scale their software delivery capabilities to drive innovation and business growth.
The 2025 AI Code Generation Tools – Champions are as follows:
- Visual Studio IntelliCode, +96 NEF, ranked high for delivering more than promised.
- ChatGPT 5, +94 NEF, ranked high for its effectiveness.
- GitHub Copilot, +94 NEF, ranked high for its transparency.
- Replit AI, +96 NEF, ranked high for its reliability.
- Amazon Q Developer, +94 NEF, ranked high for helping save time.
Analyst Insight:
“Organizations that adopt AI code generation tools gain a significant advantage in software delivery and innovation,” says Thomas Randall, a research director at Info-Tech Research Group. “These tools help developers focus on complex, high-value work, improve code quality, and reduce errors. Teams that delay adoption risk slower projects, lower-quality software, and missed opportunities to innovate and stay competitive.”
User assessments of software categories on SoftwareReviews provide an accurate and detailed view of the constantly changing market. Info-Tech’s reports are informed by the data from users and IT professionals who have intimate experience with the software throughout the procurement, implementation, and maintenance processes.
Read the full report: Best AI Code Generation Tools 2025
For more information about Info-Tech’s SoftwareReviews, the Data Quadrant, or the Emotional Footprint, or to access resources to support the software selection process, visit softwarereviews.com.
About Info-Tech Research Group
Info-Tech Research Group is one of the world’s leading research and advisory firms, proudly serving over 30,000 IT and HR professionals. The company produces unbiased, highly relevant research and provides advisory services to help leaders make strategic, timely, and well-informed decisions. For nearly 30 years, Info-Tech has partnered closely with teams to provide them with everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.
To learn more about Info-Tech’s divisions, visit McLean & Company for HR research and advisory services and SoftwareReviews for software buying insights.
Media professionals can register for unrestricted access to research across IT, HR, and software, and hundreds of industry analysts through the firm’s Media Insiders program. To gain access, contact [email protected].
For information about Info-Tech Research Group or to access the latest research, visit infotech.com and connect via LinkedIn and X.
About SoftwareReviews
SoftwareReviews is a division of Info-Tech Research Group, a world-class technology research and advisory firm. SoftwareReviews empowers organizations with the best data, insights, and advice to improve the software buying and selling experience.
For buyers, SoftwareReviews’ proven software selection methodologies, customer insights, and technology advisors help maximize success with technology decisions. For providers, the firm helps build more effective marketing, product, and sales processes with expert analysts, how-to research, customer-centric marketing content, and comprehensive analysis of the buyer landscape.
SOURCE Info-Tech Research Group
Vanderbilt University has established the Enterprise AI and Computing Innovation Studio, a groundbreaking collaboration between VUIT, the Amplify Generative AI Innovation Center and the Data Science Institute. This studio aims to prototype and pilot artificial intelligence–driven innovations that enhance how we learn, teach, work and connect.
Each of the partner areas has a strong record of addressing challenges and solving problems independently. By uniting this expertise, the studio can accelerate innovation and expand the capacity of the university to harness emerging technologies to support its mission.
Through the studio, students will have immersive experiences collaborating on AI-focused projects. Staff will deepen their skills through engagement with AI research. In addition, the studio underscores Vanderbilt’s position as a destination for global talent in artificial intelligence and related fields.
Members of the university community who have specific challenges or opportunities that AI may solve or address can submit a consultation request.
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