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The Linux Foundation’s 2024 State of Tech Talent Report found that employers were leaning heavily on training existing staff while still seeking people with cloud, DevOps, cybersecurity, and AI/ML skills. Its findings also show that organizations expected generative AI to affect technical headcount in different ways—not only through cuts, but also through planned hiring increases and new use cases.
What the survey says about tech talent strategy
In the report, cross-skilling and upskilling were leading responses to technical talent needs. Cross-skilling means preparing employees to work in a different or broader skill area; upskilling means building further capability in their current area.
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| Finding | Reported result | How to read it |
|---|---|---|
| Cross-skilling as a key talent strategy | 47% of surveyed organizations | Respondents could identify strategies they were using; this is not a measure of training completion. |
| Upskilling as a key talent strategy | 43% of surveyed organizations | A separate strategy selection in the survey. |
| Upskilling considered important | 98% of surveyed organizations; 36% rated it extremely important | These responses measure the perceived importance of upskilling, not its measured effect on business performance. |
| Preference for developing existing staff | 48% average across technology domains | On average across domains, this share prioritized upskilling or cross-skilling existing staff over hiring or using consultants. It is not the percentage of organizations that never hire. |
The figures point to a blended approach rather than a simple choice between training and recruitment. Internal development can help organizations redeploy employees and support career progression or junior staff development; each of those benefits was cited by 40% of respondents. Training does not, by itself, establish that an organization can fill every specialized role internally, and the report does not provide a causal test showing that training reduces hiring needs.
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Respondents identified these domains as technical staffing priorities:
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| Technical domain | Organizations selecting it |
|---|---|
| Cloud | 55% |
| DevOps | 51% |
| Cybersecurity | 49% |
| AI/ML | 43% |
These are survey selections, not estimates of unfilled jobs or a ranking of skill shortages across the entire labor market. The report supports the conclusion that these areas were prominent staffing priorities among its respondents; it does not establish the size of a skills gap in each domain.
What employers expected from generative AI
GenAI plans did not point in one direction. In the survey, 27% of organizations said they planned to reduce technical headcount because of GenAI, while 23% planned to increase it. These are reported intentions, not evidence that the planned changes later occurred or that GenAI caused a particular employment outcome.
Respondents also reported planned GenAI use in several technical and analytical activities:
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problems| Planned use case | Organizations selecting it |
|---|---|
| Data analysis and reporting | 45% |
| IT infrastructure monitoring | 42% |
| Software development | 35% |
The combination of planned reductions and increases is consistent with organizations anticipating different workforce effects as they adopt GenAI. The survey describes plans and use cases; it does not quantify productivity gains, job losses already realized, or the net number of technical positions created or removed.
Why hiring and onboarding remain part of the picture
The report’s executive summary gives an average of 10.2 months for hiring plus onboarding. Its detailed figures separate that timeline into roughly 5.4 months to hire and 4.8 months to onboard. The same executive summary reports turnover among 38% of new hires. These are figures reported by the survey, not universal timelines for every employer, role, or region; the executive-summary turnover figure should not be read as a prediction for a specific company.
Internal development may help organizations build skills and redeploy people already on staff, while external hiring can still be necessary when a role requires expertise the organization does not have time or capacity to develop. The report does not provide comparable cost, productivity, or time-to-proficiency measurements for training, hiring, and consulting. A practical decision should therefore consider the role’s urgency and specialization alongside factors such as recruiting and onboarding time, the ability to move current employees into the work, and the risk of losing newly hired staff.
Training barriers and ways to make learning useful
The leading reported challenges were nurturing a culture of continuous learning and helping employees apply what they learn in practice. The detailed report figure puts application of knowledge in practice at 35%; the report announcement summary gives 36%, a one-point difference in how that finding is presented. Continuous learning was cited by 39% of respondents.
Those barriers matter because course access alone does not show that a team can perform the work. The report identifies online virtual courses, instructor-led training, employer-funded training and certifications, and performance-based training as relevant options. It does not establish that one format outperforms another. Organizations choosing among them can match delivery to the skill being developed: online courses can support flexible access, instructor-led sessions can provide structured teaching, employer funding can make training accessible to staff, and performance-based assessment can show whether learners can apply skills. Those are decision considerations, not comparative outcomes measured by this survey.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Do certifications matter more than degrees?
When asked about assessing technical skills, 23% of respondents selected certifications and 16% selected college or university degrees. In this survey question, certifications were selected more often. That result does not mean employers generally reject degrees, that every certification is valued equally, or that a credential proves a candidate can perform a particular job. It is a reported assessment preference among the survey’s respondents.
For employees and employers considering technical upskilling, the report provides context for looking at training and certification alongside demonstrated ability to apply skills. The survey itself does not rate particular credentials, courses, or providers.
Who took part, and what the findings can establish
The Linux Foundation’s 2024 State of Tech Talent Report, authored by Adrienn Lawson and Stephen Hendrick and dated April 2024, draws on a web survey of people responsible for hiring or training IT professionals. According to the report’s methodology summary, the survey ran from late December 2023 to early February 2024, contained 42 questions, began with 1,455 candidates, and retained 418 records after screening.
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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →The sample covered decision-makers across multiple industries, geographies, and organization sizes. It is not a census of technology workers or a representative count of every employer. The findings describe reported practices, assessments, and intentions—not a causal evaluation of training or a forecast of what happened after the survey.
As context, respondents reported that their organizations’ technical headcount in 2023 had decreased at 29% of organizations, remained unchanged at 34%, and increased at 37%. Those retrospective reports help frame the survey’s later staffing plans, but they do not establish that GenAI caused 2023 changes.
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