The top 5 AI skills in demand right now
AI skills are no longer just for tech specialists. These days, they’re becoming a normal requirement for jobs across a range of different industries. According to SEEK research, since 2024, mentions of AI in job ads have increased by more than 80% – and that number is likely to keep rising.
This trend spans a broad range of roles as well. For instance, AI terms now appear in 5% of Marketing & Communications ads. With demand for AI-related skills going up,what exactly are the AI skills that are helpful for you to learn?
To understand what skills are in demand, SEEK’s new AI Gauge lets you take a closer look at roles on the rise, in-demand AI skills, and industries adopting AI fastest. Here’s what the AI Gauge tool found are the top five AI skills in demand.
1. Skills in machine learning (ML)
ML refers to a branch of AI where computers learn from data and get better at tasks over time – like detecting fraud patterns in banking. It’s typically a skill needed in IT roles, like an engineer or data scientist, that need to set up and oversee ML systems.
2. Skills in Generative AI (Gen AI) and Large Language Models (LLMs)
These are AI systems trained on text to understand and generate human-like language or images for tasks, like Claude or ChatGPT. Demand for Gen AI and LLM skills exists both at an engineering level (like setting up organisation-wide systems) and as a lower-levelcapability for everyday use.
3. Skills in Agentic AI
These are AI systems that can plan, make decisions and take actions mostly on their own. AI agents act more like individual employees, rather than simple tools, for instance, fulfilling the role of an AI customer service agent. Employers are looking for candidates who can set up and manage AI agents, at organisational, department and team levels.
4. Skills in AI governance and ethics
This area involves the policies and principles that guide the responsible and ethical use of artificial intelligence. These skills are most in-demand in roles that are responsible for setting up AI systems and assessing their risks.
5. Machine Learning Operations (MLOps)
This is the practice of managing the end-to-end set-up and operations of machine learning models so they’re reliable and efficient. Another more technical AI skill, this also typically sits within the role requirements of AI-experts and engineers.
The Rise of AI Skills
Although these AI-related skills are most common in IT roles, there’s growth in the demand for AI abilities across a wider range of industries, says Blair Chapman, Chief Economist at SEEK. For example, Marketing & Communications, Creative, Advertising and Legal roles are increasingly asking for specific AI skills in job ads.
“The adoption of AI is spreading from technical specialists to a broader set of professionals who can apply AI to their day-to-day work,” he says. “We’re seeing growing demand in roles where AI can enhance analytical or creative work.”
At the same time, new roles are being created to help organisations responsibly and ethically use AI, like AI Analysts and AI Transformation Leads.
The growth rate of AI mentions in jobs ads is significant, says Chapman. “The rapid increase in ads referencing Generative AI, Agentic AI, and AI Governance reflects a shift in the labour market – businesses are actively seeking workers who can use AI responsibly and productively.”
However, mentions of AI skills are a small portion of the skills demanded in job ads, with human skills, such as communication, collaboration, leadership and problem solving still outweighing the demand for AI skills.
While AI skills are increasingly sought after, they are often tied to specific roles or industries. On the other hand, human skills, or transferable skills, are more broadly applicable across diverse roles. For example, no matter what industry you're in, good communication and problem-solving are key to working well with others and leading a team, whether you’re using AI tools or not.
Despite the rise of AI, “people skills” are in high demand across all industries and have been among the top skills listed in job ads over the past decade. What this means is that AI-specific skills are always needed in tandem with more human-based skills, rather than instead of them.
How to learn AI skills
The approach to growing your AI skills is no different from learning any other skill, says Leah Lambart, Career Coach and Founder of Relaunch Me. While the subject might feel unfamiliar, the approach to learning is the same: start small and get plenty of practice.
A good place to begin is with free online courses or tutorials, such as those offered through platforms like Coursera or YouTube. “If you need deeper knowledge, there are also paid courses, such as through General Assembly or universities,” she says.
Learn from those around you, too. “Speak to people in your business who are already using AI and get ideas about how they’ve introduced it in their daily work,” says Lambart. “Then, just start small, like by using AI to make your emails more professional.”
Even if your role doesn’t specifically require AI tools, there may be opportunities for you to introduce it to streamline your workflow. “Don’t be afraid of it. Test, experiment and see what works for you,” says Lambart.
The use of AI is growing across all industries, so it makes sense to add some AI skills to your toolkitCertain types of AI – like Generative AI – are already widely used outside of tech-based roles, so it’s worthwhile upskilling to stay ahead of the curve.
