According to the Multiverse 2025 skills intelligence report, we estimate employees could boost their productivity by as much as 38% by fully leveraging AI skills and tech in their roles. Nine in 10 employees further report wanting to upskill their AI abilities. Despite this, there's a disconnect — only 6% of surveyed employees were actively looking at ways to improve processes in their current roles with AI.
It's clear that fully adopting and utilising AI workflows can help professionals of all stripes gain an edge in their careers. Those already boasting AI expertise pursue careers in a broad range of sectors. For example, the marketing sector uses generative AI to create personalised content and automate tasks. This versatile technology also has numerous applications in e-commerce, finance, manufacturing, and other industries.
You can help fill this growing demand for AI-related roles by developing essential skills. Below, we’ll explore the top AI career paths, must-have skills, and strategies to build on your AI skillset.
Why AI Skills are in high demand
The demand for AI has exploded in the last decade, and this trend shows no signs of slowing down. Bloomberg Intelligence predicts that the generative AI market will grow from $40 billion in 2022 to $1.3 trillion in 2032. This rapid expansion will create new job opportunities and transform industries worldwide.
Several factors have contributed to the high demand for AI careers. Many businesses use AI to drive innovation and increase productivity. For example, this technology allows organisations to hyper-personalise customer experiences and develop new products. Businesses can also use AI to automate repetitive tasks like data entry and credit scoring. Organisations need skilled AI professionals to leverage these capabilities and create innovative solutions.
The exponential growth of big data has also fueled the need for AI skills. Between 2020 and 2025, the amount of data generated and consumed globally is expected to triple from 64 zettabytes to 180 zettabytes. Businesses can use AI algorithms to process, analyse, and gain insights from this big data.
Top AI jobs for 2025
Spend a few minutes browsing job boards, and you’ll find many artificial intelligence careers. However, some positions have more lucrative salaries and better growth prospects than others. Here are the top AI jobs for 2025.
Machine Learning Engineer
A Machine Learning (ML) Engineer creates and implements self-learning AI models and systems. They design algorithms–or sets of instructions–that allow machines to interpret and learn from data in a human-like manner.
ML Engineers often work in healthcare, finance, tech, and other industries that depend on data to make decisions.
Salary data
- Low range - £42K
- Average base salary - £57K
- High range - £76K
Source: Glassdoor
Data Scientist
A Data Scientist collects, analyses, and visualises raw data to gain novel insights and inform decision-making. They also use ML algorithms and statistical models to classify data, uncover hidden trends, and predict future outcomes.
The US Bureau of Labor Statistics (BLS) predicts that the demand for Data Scientists will grow by 35% between 2022 and 2032—and growth is also expected to be high for these professionals in the UK. Data Scientists often work in e-commerce, healthcare, insurance, and telecommunications, among other industries.
Salary data
- Low range - £39K
- Average base salary - £49K
- High range - £63K
Source: Glassdoor
Robotics Engineer
A Robotics Engineer designs, codes, builds, and maintains robotic systems. They develop algorithms that allow robots to perform complex tasks autonomously or semi-autonomously. For example, Robotics Engineers program robots to interact with humans and navigate the ocean floor.
Robotics Engineers play vital roles in the agriculture, automotive, healthcare, and manufacturing sectors.
Salary data
- Low range - £32K
- Average base salary - £39K
- High range - £49K
Source: Glassdoor
Software Engineer
A Software Engineer develops, tests, and updates software applications. They can use AI to automate repetitive tasks, write code, and troubleshoot bugs.
According to the BLS, the demand for software development will increase by 26% from 2022 to 2032 in the US. Across the pond, there are ample reasons to believe the UK will continue to be a top destination for Software Engineers in Europe. Many industries hire Software Engineers, including business, finance, healthcare, retail, and tech.
Salary data
- Low range - £38K
- Average base salary - £50K
- High range - £65K
Source: Glassdoor
Business Intelligence Developer
A Business Intelligence Developer uses data analytics and software to collect, interpret, and visualise business data. AI-powered software can help them analyse data and design business interfaces more efficiently.
Many Business Intelligence Developers work for consulting firms, government agencies, financial institutions, and large corporations.
Salary data
- Low range - £30K
- Average base salary - £37K
- High range - £45K
Source: Glassdoor
Essential skills for AI jobs
Employers expect candidates to have a broad range of technical and soft skills for AI jobs. Here are the essential abilities you’ll need to succeed in these roles.
Machine learning
AI professionals use data and algorithms to develop and train ML models that learn and improve without human input. ML requires a strong understanding of probability and statistics. You’ll use these mathematical concepts to analyse data, design predictive models, and assess their performance. You can also use ML libraries like PyTorch and TensorFlow to create and deploy models.
Natural language processing
Natural language processing (NLP) is a subfield of AI that uses ML algorithms to understand and respond to complex human language. AI professionals use many techniques to develop NLP models like ChatGPT. For example, sentiment analysis involves assessing text or speech for emotional tone. Topic modelling is another method used to identify themes in data.
AI specialists can streamline the development of NLP models with spaCY, NLTK, TextBlob, and other libraries and frameworks.
Proficiency in programming languages
Every AI career path requires knowledge of programming languages. Python’s simple syntax and vast libraries make it the most popular choice for data analysis and ML. Other useful languages for AI professionals include:
- Java - to design complex algorithms
- JavaScript - to develop web-based ML applications
- R - for data processing and visualisation
You don’t need to master all these languages, especially for entry-level AI careers. Instead, you should research the requirements for careers you're interested in to determine which programming languages to learn.
Problem-solving
AI experts work with complex and cutting-edge technologies, so it’s normal to encounter obstacles during projects. For instance, your algorithm may make wildly inaccurate predictions, or you might struggle to find high-quality data. Strong problem-solving skills will help you troubleshoot issues and develop creative solutions.
Collaboration
AI professionals often work on complex projects that require expertise in multiple disciplines. For example, they may work with Data Scientists, Project Managers, and Product Developers. Strong collaboration skills will enable you to tackle these projects in cross-functional teams. Practice sharing your knowledge with people from different backgrounds and resolving conflicts.
Communication
AI and ML are complex topics that involve advanced technical concepts and specialised jargon. Strong communication skills will allow you to explain these ideas to stakeholders from various backgrounds. For instance, you may need to present your findings to non-technical clients and Project Managers. You can prepare for these situations by practising simplifying complex ideas and translating jargon into plain language.
AI ethics
Many challenging ethical dilemmas surround AI, leading to widespread concerns about this technology.
You can help assuage these fears by following ethical AI practices. Always obtain consent before using data, and practice transparency by documenting the methodologies and sources used.
How to acquire AI skills
Here are four possible avenues to develop the necessary skills for AI jobs.
University degrees
Some people obtain a degree in computer science, data science, mathematics, or statistics. This path allows you to gain relevant skills through a structured curriculum. But, you may not have the opportunity to develop AI-specific projects and experience. A university degree also requires a significant investment of money and time.
AI boot camps
A boot camp is an intensive program that focuses on work-ready skills. Participants also gain hands-on experience with AI projects. Some boot camps have low placement rates and high price tags, so research programs carefully before enrolling.
Self-study resources
Many websites offer free online classes, tutorials, and other resources. Aspiring AI professionals can use these materials to learn about data science, ML, programming languages, and other key concepts. Self-studying lets you learn at your own pace, but the lack of structured guidance can lead to knowledge gaps.
Apprenticeships
An apprenticeship allows you to acquire hands-on experience and follow a structured curriculum designed by AI experts. Apprentices also earn a competitive salary and build a professional network in their chosen industry.
Looking to get started or grow your skillset in AI? Explore programmes ranging from our AI and Machine Learning Fellowship to AI Strategy and Leadership with Multiverse.
Building a portfolio for AI jobs
You don’t need a university degree to pursue a career in AI, but you’ll need to show potential employers you have the right skills. Developing an online portfolio is the most effective way to showcase your abilities.
Start by developing hands-on projects that use a diverse array of AI skills. Here are a few project ideas:
- AI chatbot
- Image classification model
- Music generation model
- NLP-powered virtual assistant
- Predictive analytics model to forecast the weather or the outcome of sporting events
- Sentiment analysis tool to evaluate social media posts
These projects allow you to apply theoretical concepts to real-world scenarios. You can also gain practical experience by using real, free datasets to develop and train your AI models. Potential sources for datasets include Kaggle, GitHub, Data.gov, and the r/datasets subreddit.
As you create projects, assemble them into an online portfolio. Some tech professionals build a website from scratch to house their projects. You can also use a portfolio hosting website like Carrd, Notion, and Webflow.
Provide context with detailed descriptions, screenshots, and other supporting materials for each project. Link this portfolio in your application materials so potential employers can assess your skills.
The future of AI Jobs
AI is reshaping the future of work across industries. Microsoft released a report in 2025 showing high levels of AI applicability to roles associated with finding information, for example — implying large degrees of AI-related workforce reductions could arrive in the future.
This prediction may sound scary, but many companies won’t eliminate these jobs completely. Instead, AI will likely enhance existing roles and allow workers to focus on complex tasks that require human minds.
AI will also open new career opportunities for many employees. 36% of employers are already making a strong effort to reskill workers affected by generative AI. This percentage will likely grow as emerging technologies like multimodal AI and small language models create new roles.
Developing AI skills now can help you future-proof your career and gain a competitive advantage in this shifting landscape. As you gain experience, you may qualify for more advanced–and often more lucrative–roles in AI.
Level up your AI skills with Multiverse
There’s never been a better time to grow your career with artificial intelligence skills.
Prepare for opportunities in this rapidly growing field by developing or expanding AI skills. The top AI jobs in 2025 require excellent technical and interpersonal abilities. You’ll need a strong foundation in programming languages, machine learning, and natural language processing. Many careers also require soft skills like communication and collaboration.
Multiverse’s free apprenticeships will help you develop the necessary AI skills and gain hands-on experience.
Fill out our fast apprenticeship application to start your journey.
