The professionals who understand artificial intelligence best should, in theory, feel secure about its rise. Their skills are in demand, and organisations are competing for talent who can turn AI ambitions into practical results.
Despite this, our latest research reveals a more complicated picture.
In our 2026 Tech Talent & Salary Report, 14% of AI and machine learning professionals said they felt their job was highly threatened by AI. That is twice the global average of 7% and the second-highest figure of any technology specialism, behind only quality assurance and testing at 15%. A further 36% of AI and machine learning professionals felt slightly under threat.
At the same time, AI is the area where employers face the greatest skills shortage. A third of respondents placed it at the top of the shortage list, ahead of software engineering and development at 24% and cybersecurity at 23%.
How can the professionals in greatest demand also be among those most concerned about their future?
Proximity brings a clearer view of what AI can do
For many people, AI is experienced mainly through gen-AI applications powered by large language models (LLMs), such as chatbots, coding assistants and summarisation tools. AI professionals see a much broader picture, spanning model development, data, automation and deployment. They understand how quickly these capabilities are advancing and how tasks that once required significant human input are becoming easier to automate.
That proximity may explain some of the concern. It is not necessarily a belief that AI will remove the need for AI professionals altogether. It may instead reflect a more informed view of how quickly their roles, tools and required skills could change.
Building, training and deploying AI is not immune to AI-enabled automation. In fact, some of AI’s clearest productivity gains are already being seen across coding, testing, data preparation, model development and monitoring, where tasks can be completed faster and with less manual input. Those closest to these capabilities are likely to recognise that valuable expertise will need to keep evolving.
Their concern, therefore, should not simply be dismissed as pessimism. It may be an early signal from the people with the clearest view of the technology’s direction.
Skills shortages do not mean roles will stand still
The apparent contradiction becomes easier to understand when we separate demand for skills from the shape of individual jobs.
Our Digital Leadership Report 2025 found that 51% of digital leaders were experiencing an AI skills shortage, up from 28% in the previous report. This 82% increase was the steepest rise in skills scarcity recorded during 16 years of tracking.
Organisations clearly need more AI capability. But that doesn’t mean every role will remain unchanged. As AI becomes embedded across business functions, employers need people who can apply it to real organisational challenges and achieve ROI, not simply understand the technology in isolation.
LinkedIn data in our Tech Talent & Salary Report identifies machine learning, data structures, pattern recognition, deep learning and large language models among the most sought-after capabilities. These technical skills must increasingly sit alongside data quality, governance, commercial understanding and awareness of the human consequences of automated decisions.
This is not a market in which expertise is becoming less important. It is one in which the definition of expertise is moving quickly.
AI is changing hiring, but it can also create growth
The same tension can be seen in employers’ hiring plans.
Digital leaders expect AI to reduce their future hiring needs for existing technology roles by around 18% over the next two years. Almost two-thirds would choose a software developer with excellent generative AI skills and three years’ experience over someone with five years’ experience but no generative AI capability.
However, organisations with large-scale AI implementations are 24% more likely than their peers to be increasing technology headcount, with much of that growth focused on AI and data. Those making the greatest progress are changing the capabilities they need and investing in people who can help them scale.
For employers, hiring talent and investing in AI are closely connected. Technology can automate tasks, but organisations still need specialists who can select the right use cases, challenge outputs, manage risk and connect technical capability to measurable business value.
Access to AI is not the same as preparation
Some of the anxiety may also come from the gap between the speed of adoption and the support available to employees.
Three-quarters of technologists in our latest report have access to AI tools and platforms, but only 37% say their organisation is actively investing in AI upskilling. Just 43% are given dedicated time to experiment and learn, while 20% are expected to develop their knowledge independently.
Providing access without the time, training or direction to use AI effectively places the burden of adaptation on the individual. Even highly skilled professionals can feel exposed when expectations change faster than career pathways and learning opportunities.
It’s clear that employers seeking scarce AI talent need to provide structured development, clarity about how roles are evolving and opportunities for specialists to broaden their experience across data, governance, deployment and business strategy.
Turning concern into capability
The expertise that makes AI professionals so valuable also gives them a clearer view of how the technology could reshape their own roles. Their concern does not contradict the demand for their skills, but it reflects a deeper understanding of both AI’s potential and its disruptive impact.
For AI and machine learning professionals, long-term career resilience will come from continuous learning and the ability to connect deep technical knowledge with judgement, communication and business impact.
For employers, the priority is to create an environment where that development can happen and where scarce specialists can see a future, not just an immediate project.
AI expertise remains one of the most valuable capabilities in the technology market. But demand alone isn’t removing uncertainty. The organisations that recognise this and invest in their people as deliberately as they invest in the technology will be best placed to secure the skills they need and turn AI implementation into lasting value.
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