How is AI reshaping hiring priorities in tech?In the fast-moving world of technology, experience used to be the gold standard. Job titles, years in post, and familiarity with established systems once served as reliable markers of a candidate’s value. But in 2025, that’s changing. The rise of artificial intelligence (particularly GenAI) is transforming the skills landscape so rapidly that many of the old hiring playbooks are no longer fully fit for purpose. New findings from the 2025 Nash Squared/Harvey Nash Digital Leadership Report highlight just how much priorities are shifting. According to our research, 65% of digital leaders indicate they would now prioritise hiring a developer with strong GenAI skills and just three years of experience over someone with five years of experience but no AI fluency. While this doesn’t capture the full complexity of hiring decisions, it signals that AI skills are becoming a defining factor in today’s hiring decisions, particularly when it comes to technology recruitment. AI skills are now business-critical…and scarce This shift isn’t happening in a vacuum. AI has rapidly moved to the centre of how organisations operate, from code generation and data analysis to recruitment, customer service, and internal operations. The demand for AI talent has surged, with demand outstripping supply. Our report shows that AI is now the number one skills shortage in tech. Demand for AI talent has jumped from 28% in 2023 to 51% in 2025, an 82% increase, the steepest rise recorded since we began tracking skills scarcity. Yet despite this, over half of organisations are not currently upskilling their staff in AI. The gap between AI’s growing importance and the internal capability to support it is widening, and this has implications not only for hiring but also for retention, productivity, and long-term business performance. How AI is changing hiring processes The shift towards AI skills is not just about what’s being hired for, but how organisations are hiring. We’re seeing a fundamental rethink of recruitment processes: Job descriptions: Companies are rewriting job specs to specify proficiency in AI tools and platforms - such as Python, TensorFlow, and GenAI frameworks, rather than relying on generic “AI skills” as a buzzword. Assessment methods: There’s a growing use of AI-driven assessments and real-world coding challenges to test candidates’ ability to apply AI in practical contexts Skills over tenure: Where once tenure and job titles carried the most weight, today’s tech hiring is increasingly centred on proven skills, adaptability, and the ability to work alongside intelligent systems. However, many organisations are still catching up. Job specifications often reference “AI skills” without defining what this means in practice, and interviews may still lean too heavily on past roles or academic credentials. At the same time, candidates need to adjust, clearly showcasing where they’ve applied AI tools in real contexts, whether that’s automating analysis, streamlining development, or enhancing digital products. Practical steps for organisations To address the growing need for AI talent, organisations should: Develop a clear AI strategy: Ensure a defined roadmap is in place, or being worked on, to demonstrate commitment to AI adoption. Top AI talent is attracted to organisations with a vision for growth, where they know their skills will contribute to a structured and evolving AI environment. Define AI skills clearly: Avoid vague requirements. Specify the tools, platforms, and types of AI experience needed for each role. Update assessment methods: Use practical tasks, case studies, and AI-driven assessments to evaluate candidates’ real-world AI capabilities. Upskill internally: Invest in learning and development to build AI literacy across the workforce, not just in specialist roles. Foster a culture of continuous learning: Encourage ongoing development and provide access to AI training resources for all employees. Beyond recruitment: building a future-ready workforce Shifting hiring practices is only part of the answer. For AI adoption to deliver real value, businesses also need to think beyond recruitment and invest in developing the skills of their existing tech workforce. Yet with more than half of organisations not currently providing AI training, a significant opportunity to build capability internally is being missed. Collaboration between HR, L&D, and technology leaders is crucial. The organisations most likely to succeed will be those that not only rethink job specs and validate AI capability during hiring but also provide continuous learning opportunities to help their teams adapt. A collaborative approach, where recruitment and development reinforce one another, will be key to building resilient, future-ready tech functions. Shaping tomorrow’s workforce today For organisations undergoing digital transformation, this is a moment to reset. The ability to identify and hire people with the right AI and data skills could increasingly determine how quickly and effectively businesses adapt. At Harvey Nash, we’re helping our clients respond to this shift. As experts in tech and AI recruitment, including AI and data roles, we work with forward-thinking businesses to reshape their hiring strategies, assess practical capability, and build teams ready for the future of work. To explore more insights into how AI is shaping the tech workforce, download the 2025 Nash Squared / Harvey Nash Digital Leadership Report.
