Switch on to AI and power up your career in 2025
Written by Dan Parry • 15 January, 2025
Future Skills Article
As we roll into a new year, AI skills are likely to play a leading role in many professional development plans.Whether you’re on your way to becoming the next Steve Jobs or you’re simply feeling bewildered by the whole AI shebang, here are the six leading skills and trends in AI.
According to PwC (August 2024), 73% of US companies use or plan to use AI. Meanwhile, a survey from Access Partnership and Amazon Web Services (AWS) found that 85% of UK employers expect to use AI-related tools by 2028.
Organisations who have signed up to AI are, on average, using it mostly in marketing and sales, and in product and service development – according to a global study by McKinsey (2024). Take-up rates of generative AI, in particular, are soaring. So-called ‘gen AI’ – giving content on demand including text, music, video or images – features prominently in our list of essential emerging trends:
Financial and other professional services lead the way among industries making an early commitment to AI, as shown in three studies from 2024. US careers website dice.com found that the biggest commitments to AI are in financial services, legal services, healthcare, manufacturing (robotics), and real estate. For Global recruiter Hays, the top five professions incorporating AI are marketing, technology, education, accountancy and finance, and engineering. Meanwhile, Canadian automation company Vention found that business and legal, consumer goods/retail, financial services, healthcare, and tech/telecom are prominent AI adopters.
The McKinsey study noted above suggested that AI is adopted in three ways: takers use off-the-shelf solutions; shapers customize those tools with proprietary data and systems; and makers develop their own models from scratch.
Although organisations are wising up to AI, particularly in professional services, its impact hasn’t reached a tipping point yet. AI is prevalent but not a primary force of change, similar to the early days of the internet. This is partly because, though investment is under way, resources remain limited. According to an IBM survey of 400 leaders across 17 industries and six geographies (October and November 2024), “77% of executives say they need to adopt gen AI quickly to keep up with competitors – but only 25% strongly agree that their organisation’s IT infrastructure can support scaling AI across the enterprise.”
Which skills does AI particularly support? A Forbes survey (2023) found that the top five uses of AI are:
No surprise then that the most popular AI tools are those that meet these needs. This list (from US software company Zapier) of leading contenders was released in October 2024:
According to a PwC report on jobs, the demand for AI-related skills is 3.5 times higher than ‘average’ job skills. Using AI to generate emails, research reports, provide meeting notes, or create content requires core skills such as:
Prompt engineering: Guiding a chatbot such as ChatGPT towards your goal requires a creative approach that doesn’t come easily to everyone. In some industries, people will need to break free from a compliance mindset if they are to creatively get the most from a chatbot.
Cybersecurity: As it rapidly expands, the digital landscape is becoming more vulnerable. In 2025, global cybercrime costs are projected to reach a staggering $12 trillion, according to a report by research agency Forrester. A shortage of qualified professionals in the field means that skills in preventing cybercrime are especially valued.
Data analysis: The ability to transform unstructured data into actionable insights can build productivity and drive growth. Analysts are skilled in protecting data integrity, ensuring that results are securely sourced, relevant, and reliable.
Digital marketing: With billions of social media users worldwide, messaging travels further and faster through digital marketing strategies. These can be targeted to ensure maximum reach, which is why marketing features in the lists of industries with an early interest in AI.
Leadership: Leaders must be prepared to think big. Early adopters are focusing on reimagining entire workflows using gen AI and analytical AI rather than simply seeking to embed these tools into their current ways of working.
AI mindset: An attitude of continuous learning will help to treat AI skills as an ongoing journey rather than a destination. For example, the rise of gen AI will require further skills in integrated platforms as organisations continue to migrate their workloads to the cloud.
AI skills are not restricted to simply knowing your chatbot from your co-pilot, they’re about knowing your own role and understanding how to support it by using tech. AI is only a means to an end, not an end in itself.
Human intelligence, unlike its artificial competitor, contains a basket of unrivalled skills. AI can help you spell things like listening, humility, curiosity, nuanced analysis, empathy, mentorship, emotional intelligence, and creative solutions based on practical experience – but it can’t do much to replicate them.
To make the most of AI, people need human skills, particularly in analysis and critical thinking. Skills in analysis help you penetrate a dataset and find relevant conclusions. Abilities in critical thinking can then transform your conclusions into meaningful actions – such as writing a presentation that translates complexity into an explanation for everyone in the room.
In the Access Partnership/AWS survey mentioned above, 53% of employers ranked critical thinking as one of the top three most important skills required to use AI tools in 2028, compared with only 42% for technical skills like coding.
AI brings advantages but challenges too and users need to be aware of both. For example, gen AI users may feel like they’re getting something new but in truth they’re getting a rehashed version of existing content.
McKinsey’s 2024 global study looks at some of the risks presented by gen AI – among them, inaccuracy. Other noted stumbling blocks include bias, intellectual property infringement, and breaches of data privacy. Similarly, gen AI results can lack ‘explainability’ – particularly if they were acquired by someone who simply wants to shovel content into a presentation without much personal investment or understanding.
Focus is important too when managing ‘AI hallucinations’. In response to a prompt, gen AI can hallucinate false information – perhaps by relying on the text of a resume and combining it with a job description to write a cover letter that includes experiences which didn’t occur.
While organisations are rushing to invest in AI, many are less energetic about training their people.
In the Access Partnership/AWS survey of 500 organisations, employers reported that the top barriers to providing AI skills training include not knowing which AI skills are required by employees (74%) and uncertainty about how to implement an AI training programme (71%).
Robust training programmes can help prepare people for change so that organisations get the most from their expensive AI investments. Training can also help employees understand the difference between an organisation’s proprietary tools and publicly accessible models so that code or proprietary data are not inadvertently shared with the world at large.
For most people, who are not in AI development or tech support, AI skills are about teamwork and communication. At Working Voices, our Team Engagement courses focus on the human skills that support the use of AI. In particular, we recognise that adopting AI is about changing mindsets as much as learning tools.
While for most organisations, the transition to AI is only just getting under way, trust in people will be key to a return on their investment. For individuals, AI will bring change which not everyone will be comfortable with. By building new skills into your professional development plan, however, change can be for the better, opening new ways to support traditional human strengths.
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