A report on the 2025 State of Tech Talent was recently published by Linux Foundation Research. “Our results reveal significant shifts in the technical workforce, particularly driven by AI adoption and a shortage of skilled professionals,” wrote authors Adrienn Lawson and Marco Aurelio Gerosa in the report’s Executive Summary. “Contrary to widespread concerns about AI-driven job displacement, our research reveals a positive trajectory in workforce growth due to AI in the IT sector. The projected net hiring effect remains positive through 2026, expanding from 18% in 2024 to 23% in 2026, with remarkable consistency across regions.”
The report explores how organizations have been navigating AI’s impact on workforce dynamics, focusing particularly on the intersection of talent management and technological innovation. In March of 2025 LF Research conducted an online survey consisting of 42 questions to understand the effects of AI disruption on the workforce as well as trends in technical hiring. Data quality was addressed through extensive prescreening to ensure that respondents had sufficient professional experience to answer questions on behalf of their organizations. The final survey sample comprised 556 responses from participants responsible for hiring, training, and managing technical talent.
The report is structured around three main themes: the transformation caused by AI, the shortage of skilled IT professionals, and the role of upskilling to fill technological needs. “Our analysis shows how the talent shortage constrains technological innovation and explores successful talent management strategies, highlighting the potential of skill development programs, including upskilling (deepening existing capabilities) and cross-skilling (expanding expertise across domains). For consistency, we use the term ‘upskilling’ throughout this report to reference both of these complementary training approaches.”
Let me summarize the report’s key findings.
The transformation caused by AI
AI creates more jobs than it eliminates. “Despite widespread assumptions that AI’s automation capabilities are reducing workforce demand and mitigating the IT talent shortage, our research reveals the opposite. Our survey data shows that AI adoption is contributing more to workforce growth than reduction.”
The projected net hiring as a result of AI was 18% in 2024, and is expected to be 21% in 2025, and 23% in 2026, indicating a competitive job market for AI talent. The positive net hiring is consistent across regions, industries, and organization sizes.
How has AI impacted your technical workforce in 2024?
- AI specific roles: 57% increased, 3% decreased, 59% no impact.
- Software development: 32% increased, 8% decreased, 40% no impact.
- Technical management: 28% increased, 9% decreased, 64% no impact..
- IT operations: 25% increased, 12% decreased, 63% no impact.
- Q/A testing: 24% increased, 12% decreased, 60% no impact’
- Technical entry-level positions: 24% increased, 18%, decreased, 63% no impact.
Note that in all six areas, the percentage that responded that jobs increased is larger than those that responded that jobs decreased, ranging from +54% for AI specific roles to +6% for technical entry-level positions. In all cases, “no impact” was by far the largest response, not surprising given that we’re still in the relatively early stages of the AI age.
AI does not replace workers, but it reshapes their roles. As has been the case with other disruptive technologies, AI is mostly reshaping occupations rather than eliminating them. The path forward lies in embracing human-AI augmentation. “While AI may not replace professionals, those who are not able to operate in AI-enabled environments will certainly be replaced by those who do.”
94% of organizations expect AI to deliver significant value across their core operations. AI is expected to deliver the most value in software development (54%), followed by data analysis (52%), IT infrastructure optimization (45%), customer services support (40%), quality assurance (33%), network management (26%), project management (26%), and sales and marketing (26%).
67% of organizations report significant changes to their technical work due to AI. New AI-based technical positions include reviewing/validating AI-generated code (33%), effectively supervising/prompting AI tools (28%), automating traditional entry-level tasks (24%), and automating IT operations with AI (22%).
AI is also creating demand for new enterprise-wide functions including AI operations engineer (64%), AI product manager (36%), AI quality assurance engineer (33%), AI governance specialist (29%), prompt engineer (26%), AI safety engineer (20%), and AI ethics officer (16%).
The shortage of skilled IT professionals
The talent crisis poses a barrier to innovation. “IT modernization challenges for organizations are often centered more on human capital development than on the technological complexity, cultural transformation, or legal barriers. Therefore, for technology adoption to succeed, investment in human capital must parallel, or even precede, investment in the technology itself.”
What are your organization’s primary challenges in adopting new technologies? Budget constraints (52%), security and privacy concerns (45%), lack of a skilled workforce (44%), complexity of legacy system integration (39%), difficulty of adopting new technologies (39%), organizational culture (30%), government regulations (19%). Note that 44% of respondents said that the shortage of skilled workers remains a major barrier to technology adoption.
Strategic domains are understaffed in most organizations. Not surprisingly, the talent shortage is particularly acute in AI engineering and operations (68%), followed by cybersecurity and compliance (65%), FinOps and cost optimization (61%), cloud computing (59%), and platform engineering (56%).
“Without addressing these fundamental workforce challenges, organizations may struggle to fully capitalize on these transformative technologies and realize their strategic digital ambitions.”
Upskilling as the key strategy to develop the workforce
Organizations prefer to upskill existing talent. The survey asked: “How does your organization ensure that its technical staff have the necessary skills to fulfill the technological needs of the organization? 72% said that upskilling or cross-skilling existing staff was their top strategy; 56% preferred hiring new IT professionals; and 22% preferred hiring consultants. Only 3% of respondents said that upskilling was not important, while 70% said that it was extremely or very important.
Upskilling was also the top preference for developing talents across all major technical domains.
- AI, Data & analytics: upskilling 57%, hire new technical staff 27%, hire consultants 17%;
- Cybersecurity: upskilling 61%, new technical staff 21%, consultants 17%
- Cloud & virtualization: upskilling 70%, new technical staff 16%, consultants 14%;
- Privacy & security: upskilling 65%, new technical staff 17%, consultants 18%;
- Systems engineering: upskilling 70%, hire new technical staff 18%, hire consultants 13%.
“This strategic focus on internal talent development may prove to be one of the most significant organizational adaptations to the digital age, fundamentally altering how companies build and maintain their technical capabilities. As technology continues to evolve, the ability to rapidly upskill existing talent becomes the primary differentiator between organizations that thrive and those that stagnate in an increasingly complex technical scenario.”
One of the main reasons why upskilling existing employees is generally preferred over hiring external talent is the time advantage. On average, it takes 8.4 months months to hire and onboard new employees, whereas it takes 5.2 months to upskill existing employees. The difference is wider for more senior positions. The average hiring and onboarding time for executive positions is almost one year (11.7 months); for director (11.5 months); manager (10.1 months); and senior technical roles (10.0 months).
Upskilling is effective for retaining talent. On average, 19.2% of newly onboarded technical staff exit the organization — through resignation or termination — within their first six months, thus creating a costly cycle of recruitment, training, and replacement, further emphasizing why investing in existing employee development offers a more stable and efficient talent strategy.
The survey showed that technical training (91%) and career growth (91%) are almost as effective as compensation (92%) for retaining top technical talent. The survey also revealed the effectiveness (84%) of open source culture initiatives in retaining technical tangent, “recognizing that modern technical talent seeks more than just competitive salaries — they desire participation in broader technical communities and knowledge sharing.”
How does your organization plan to address its AI core activities. Upskill the existing workforce was the top choice of 49% of respondents, followed by leverage open source models and tools (40%), use AI-as-a-service platforms (36%), partner with AI vendors, startups and academia (29%), and staff up and build in-house (28%).
The LF Research report concluded by summarizing the survey’s five key findings:
- Prioritize internal talent development.
- Foster a continuous learning environment.
- Emphasize practical experience and certification.
- Leverage open source culture.
- Prepare for AI integration.
