Experts in Technology Recruitment & Solutions

FutureScot’s recent article, AI, efficiency and the next wave of digital leadership in Scotland, explores how Scotland’s public sector is responding to the growing opportunities and challenges of digital transformation. Drawing on findings from the 2025 Nash Squared / Harvey Nash Digital Leadership Report, it highlights how technology leaders across Scotland are shifting their focus towards efficiency, resilience and measurable outcomes. The piece notes that operational efficiency has become a key boardroom priority, with organisations looking to deliver more impactful, outcome-driven technology investments. However, many leaders continue to face obstacles in the form of persistent skills shortages, particularly across areas such as AI, data, cybersecurity and DevOps. Cyber resilience remains another critical theme, as a significant number of organisations have experienced cyberattacks in the past year, underscoring the urgency of stronger security strategies. At the same time, the article points to the growing importance of collaboration and partnerships, with many Scottish digital leaders planning to increase their use of specialist partners and external expertise to scale transformation. Together, these developments suggest a more mature phase of digital leadership in Scotland, one focused on execution, capability and long-term impact. As proud sponsors of Digital Scotland 2025, Harvey Nash will be joining Scotland’s digital community to discuss exactly these themes, exploring how technology, talent and leadership can work together to deliver meaningful change across the public sector. Read the full article on FutureScot: AI, efficiency and the next wave of digital leadership in Scotland

Data roles are becoming increasingly critical as organisations look to harness AI effectively. The demand for professionals skilled in managing, structuring and interpreting data is rising, with experience in AI-specific roles particularly valued. In an article for Computing.com, Senior Recruitment Consultant at Harvey Nash, Daniel Neaves, explores how data-focused roles underpin the development and deployment of AI. He highlights the importance of building a career that demonstrates both technical expertise and practical experience, specialising in areas where AI and data intersect. Daniel also stresses the value of maintaining up-to-date profiles, targeting applications thoughtfully, and building strong relationships with recruiters and hiring teams. He underlines that while AI can support recruitment processes, personal effort, preparation, and persistence remain key to career success in this competitive market. Read the full article on Computing.com

Artificial Intelligence (AI) and machine learning (ML) have moved rapidly from experimental projects to mainstream business priorities in the UK. Organisations across every sector are exploring how automation, predictive models and generative AI can unlock efficiency, innovation and competitive edge. As adoption accelerates, demand for AI and ML professionals has risen sharply. What was once the domain of research labs and niche tech firms is now a boardroom conversation. Employers aren’t just looking for technical experts; they need individuals who can help shape strategy, manage risks, and embed AI capabilities responsibly across the organisation. 2025 feels like a pivotal year. The opportunities are vast, but the competition for talent is intensifying. The challenge for businesses is to secure the right people, with the right skills, to deliver on their AI ambitions. Why AI and Machine Learning talent are in high demand Across the UK, companies are seeking to integrate AI into their operations, often starting with chatbots, automation, or customer-facing applications, but increasingly moving towards deeper transformation projects. Three main drivers are shaping demand: Business adoption at scale – AI is no longer confined to pilot projects. Retailers are using it for customer personalisation, banks for fraud detection, and healthcare providers for diagnostics. Generative AI hype and reality – the explosion of generative AI tools has prompted many organisations to invest in in-house capability, either to build proprietary models or to adapt existing ones. Competition and retention – talent is scarce and mobile. Many employers are hiring defensively, seeking to retain people before competitors can lure them away. This combination is fuelling one of the most competitive hiring markets we’ve seen in years. Key AI and ML trends shaping the UK in 2025 To understand the AI and ML hiring landscape, it’s important to look at what’s driving the conversation today: Generative AI takes centre stageThe surge in generative AI adoption has created an increased demand for ML engineers, prompt engineers, and AI product specialists who can operationalise these technologies. Ethics and governanceAs AI is embedded in business processes, risks around bias, transparency and regulation are rising. Employers are beginning to seek specialists in AI governance and compliance to develop ethical frameworks, ensure accountability in AI decision-making, and align their AI strategies with evolving legal standards. Data foundations are criticalWithout high-quality, well-structured data, AI projects fail. Companies are therefore investing heavily in data engineering and analytics talent alongside AI hires. Integration into digital transformationAI is no longer a separate initiative; it’s becoming part of broader transformation strategies, impacting IT, operations, HR and customer experience. Professional development and evolving skillsContinuous learning and upskilling is essential for all employees, especially technologists and AI or machine learning experts who must evolve as fast as the technology does.  The most in-demand AI and ML roles for 2025 The hiring market is being shaped by organisations seeking resilience, innovation and agility. Some of the most in-demand roles include: Machine Learning Engineer – building, training and deploying ML models.Typical salary: £70,000 – £110,000* Data Scientist – analysing complex data sets to provide actionable insights.Typical salary: £60,000 – £100,000* MLOps Engineer – managing the deployment and lifecycle of AI models in production.Typical salary: £75,000 – £115,000* AI Product Manager – bridging the gap between business strategy and AI delivery.Typical salary: £65,000 – £105,000* Prompt Engineer / Generative AI Specialist – optimising large language models for business use cases.Typical salary: £55,000 – £90,000* AI Governance Specialist – ensuring ethical, transparent and compliant use of AI.Typical salary: £70,000 – £95,000* * Salary ranges are based on London market rates. We are also seeing hybrid roles emerge, for example, “AI Risk Manager” or “Applied AI Strategist”, reflecting the fact that AI is no longer just a technical discipline, but a strategic business capability. The skills employers are prioritising Employers are searching for candidates who bring both technical depth and the ability to shape strategy. Core technical skills include: Python, TensorFlow, PyTorch Natural Language Processing (NLP) Generative AI and LLM fine-tuning MLOps and cloud AI platforms (AWS, Azure, GCP) Data engineering and governance Certifications occasionally requested: Cloud AI certifications (AWS, Azure, GCP) AI/ML specialisations from leading universities Data science and advanced analytics credentials Soft skills are equally vital: Strategic thinking and business alignment Communication with non-technical stakeholders Problem-solving in fast-moving environments Collaboration across functions Challenges in hiring AI and ML talent As demand for AI and ML talent grows, organisations face several key challenges: Talent shortages – Our 2025 Nash Squared / Harvey Nash Digital Leadership Report found that AI has surged to become the most scarce technology skill in the UK. Competition – top candidates often receive multiple offers, driving up salaries and expectations. Slow processes – delays in the hiring process can mean losing talent to faster-moving competitors. Capability assessment – employers often struggle to test technical and applied skills effectively. Building the future with AI and ML talent AI and machine learning are no longer niche specialisms but central to business growth, innovation and competitiveness. For UK organisations, 2025 represents a critical moment to secure the talent that will define their future. The organisations that succeed will be those that: Invest early in the right people. Provide clear strategic direction. Offer development and retention opportunities. As Dan Neaves highlights, success in AI hiring starts with the right foundations: “Businesses need quality data, a clear AI strategy, and a future plan of what the capability looks like now, in three years, and in five years. Combined with a slick hiring process and professional development opportunities, that’s how you attract the best talent in AI.” How Harvey Nash supports AI and ML recruitment At Harvey Nash, we’ve spent more than three decades helping businesses navigate technology change. As AI and ML continue to evolve, we’re applying that experience to help organisations build the right teams for the future. This is a dynamic and fast-moving area of recruitment. Roles are constantly changing as new tools, frameworks and use cases emerge. That’s why we take a consultative approach, understanding each organisation’s goals, maturity and culture before connecting them with exceptional talent. Our consultants are deeply embedded in the UK technology community and speak to AI and ML professionals every day. We provide insight on salary benchmarks, in-demand skills and how to position roles to attract and retain the best people. If your organisation is expanding its AI capability in 2025, Harvey Nash can help you navigate the evolving market, connect with exceptional professionals, and build a team fit for the future. Get in touch with our team to start the conversation. Daniel Neaves – AI & Machine Learning Specialist

Mo Gaibee, Associate Consultant at Harvey Nash, was recently featured in a CSO Online article exploring how AI is reshaping entry-level cyber hiring and shifting the nature of the cybersecurity skills gap. In the piece, Mo highlights how hiring criteria are evolving; it’s no longer just about technical certifications. Organisations are increasingly valuing soft skills such as communication, collaboration, adaptability, and strategic thinking, as cybersecurity now touches many areas of a business, including legal, HR, and marketing. He also notes that while AI is automating more of the repetitive monitoring tasks, it hasn’t reduced the need for human talent, instead, it’s changing the profile of the skills that are most in demand. Read the full article on CSO Online.