As industries across the board continue to invest heavily in artificial intelligence (AI) and machine learning (ML) technologies, the demand for skilled specialists in the UK has more than tripled. This demand has created a lucrative opportunity for tech workers to capitalise on their expertise by transitioning into AI or ML roles.

But just how much more can the average tech worker expect to earn by making this shift? The experts at AIPRM analysed average entry level salaries, comparing them to higher skilled roles across a range of jobs within the tech sector to find out.

Comparing Salaries Across Technology Job Skills

Job Skill Comparison Mean Salary (£ Per Annum)Increase (£)Increase (%)
Non-AI Skills VSAI Skills57,263+20,51835.8%
Machine Learning VSDeep Learning68,039+16,02423.6%
Structured Query Language (SQL) VSPython57,104+10,736 18.8%
Excel VSStructured Query Language (SQL)52,851+4,2538.1%
  1. From non-AI Skills to AI Skills – Increase of £20,518

Tech workers with a non-AI based skillset can expect to earn around £57,263 per annum on average. This is already 48.3% higher than the UK average salary of £34,963, however making the switch to an AI-based role could see salaries skyrocket even higher, earning you £77,781 per annum – a considerable increase of 35.8%.

As organisations recognise the transformative potential of AI, they are willing to invest heavily in acquiring the right talent, leading to much higher compensation packages for AI professionals across the board.

  1. Machine Learning vs Deep Learning – Increase of £16,024

Those skilled in machine learning can expect to earn a comfortable salary of around £68,039 on average. In comparison, making the transition to a deep learning-based role could see tech workers earning around £84,063 – an increase of £16,024, or 23.6%.

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While both fields fall under the broader umbrella of AI, deep learning is more complex and specialised than traditional machine learning methods and has paved the way for groundbreaking advancements in various sectors, including healthcare, finance, and self-automated vehicles.

  1. Structured Query Language (SQL) vs Python – Increase of £10,736 

SQL (Structured Query Language) is one of the most widely used database languages and plays a crucial role in data management and analysis across various industries. Tech workers versed in this skillset can expect to earn £57,104 per annum on average. 

Making the switch to Python, however, could see workers earning around £67,840 per annum, an increase of  £10,736 or 18.8%. 

Python holds a distinct edge over SQL due to its versatility and broad scope of applications and with a limited pool of experienced Python developers and data scientists available in the UK job market, employers are willing to offer competitive compensation packages to attract top talent. 

  1. Excel vs Structured Query Language (SQL) – Increase of £4,253

Tech workers with Excel skills can earn a salary of £52,851 per annum on average but those who supplement their learning with SQL skills can expect a sizable salary boost, earning around £57,104 per annum, an increase of 8.1%.

Although SQL and Excel are both widely used tools for data management and analysis, SQL excels (no pun intended) in handling large datasets and complex relational databases, making it a preferred choice for organisations dealing with substantial volumes of data. 

Commenting on this, AIPRM spokesperson, Christoph Cemper, said: “AI and ML are not just buzzwords anymore; they’re driving real-world innovation and reshaping industries. The UK demand for skilled AI and ML professionals has shot through the roof in recent years, creating a supply-demand gap that’s tilting the scales in favour of those with the right skills. 

“Companies are scrambling to find talent that can help them unlock the full potential of these technologies, and they’re willing to pay a premium to get the best people on board. So, if you’re looking to take your career to the next level and boost your earning potential, diving into AI or ML could be a smart move that pays off big time.”