What Skills will People Need to Thrive in an AI-Era?
The workplace is evolving at an unprecedented pace due to technological shifts. 66% of employees say they have experienced more change at work in the last year than in the 12 months prior.
This change is having a profound effect on skills. While some jobs may vanish due to automation, others will evolve and entirely new roles will emerge. The World Economic Forum predicts that 6 in 10 workers will require training before 2027.
There is a huge opportunity cost if workers are not upskilled adequately. Research from Korn Ferry estimates that by 2030 skill gaps are expected to cost global businesses $8.5 trillion dollars in unrealized revenue.
But as workers face growing pressure to reskill, how can they decide which skills they should invest in?
There is shared uncertainty from employers, workers, education providers about the best path forward and many organizations are already behind the curve. The Skills England Report (2024) demonstrated that employer investment in training in the UK has actually been in steady decline over the past decade.
Here at Quench, we are dedicated to shaping a future where everyone can succeed alongside AI. By identifying the skills that will matter most in the workplace, we want to ensure all workers can thrive in their careers.
The High Demand for AI Talent
Generative AI has been heralded as a breakthrough technology and is set to redefine the nature of work. Bloomberg Intelligence predicts that the generative AI market will grow from $40 billion in 2022 to $1.3 trillion by 2032.
This exponential growth has fueled the need for skilled talent to take full advantage of AI’s capabilities. Drawing a parallel to the Industrial Revolution, Fabian Stephany, Assistant Professor in AI & Work at the Oxford Internet Institute, noted that even the most powerful technologies can fail to drive impact without the right human skills to maintain and integrate them.
There has been increased demand for roles such as Machine Learning Engineers and Software Engineers with the US Bureau of Labor Statistics predicting that the demand for Data Scientists will grow by 36% in the US between 2023 and 2033. Industry demand also appears to outpace labour supply. Notably, over 60% of businesses surveyed by McKinsey in 2023 had difficulty hiring Machine Learning Engineers, AI Data Scientists, Data Architects, and other AI professionals.
The Value of Complementarity
To determine which skills workers should invest in to secure their future in the workplace, Fabian Stephany, Assistant Professor at the Oxford Internet Institute and Ole Teutloff, PhD Fellow in Social Data Science at the University of Edinburgh, analysed a decade’s worth of skill profiles of around 25,000 knowledge workers from one of the world’s largest online freelancing platforms. They came to the conclusion that complementarity is essential for determining the value of a skill, in other words, how well a skill complements and enhances other skills.
There are three reasons why complementarity matters:
- Skills come in sets: A skill is rarely applied in isolation. Most jobs require a combination of skills. For data scientists, for instance, combining technical expertise with social skills like communication, teamwork, and leadership is highly valuable.
- Reskilling efficiency: We rarely build our skill set from scratch but incrementally add new skills to existing capacities. In this process economic efficiency is relevant because we want to make use of as many complementarities between old and new skills as possible.
- A skill’s complementarity reflects its strategic value: The more versatile a skill’s applications across different domains, the more opportunities workers have to reskill, strengthening their adaptability to unexpected technological advancements.
AI skills are highly valuable because they complement other skills, making them adaptable across diverse fields, including graphic design, translation, and software development.
As industries embrace AI, the demand for AI skills has increased leading to higher wages. In fact, research shows that AI skills, such as programming languages and data analytics increase worker wages by 21% on average. AI skills are not just relevant to machine learning engineers and data scientists; workers in marketing and sales can earn 20% more compared to people in the same role who do not have AI skills.
This surge in demand means that being proficient in AI can be as valuable as holding a university degree, with some job sectors valuing AI expertise even more than traditional academic credentials as this study of one million job offers from the UK indicates.
Top 10 Skills on the Rise
Workers might be inclined to believe that technical skills associated with lucrative careers in programming and data analytics will be the only useful skills in an AI-powered economy. However, according to the World Economic Forum’s Future of Jobs Report 2023, cognitive and self-efficacy skills make up 4 out of the 5 top skills on the rise. As emerging technologies such as generative AI reshape workforce demands, employers are replacing greater emphasis on cognitive skills like creative thinking.
Cognitive Skills
Cognitive skills are reported to be growing in importance most quickly with analytical thinking expected to grow in importance by 72% over the next 5 years. Analytical thinking is crucial to assessing data outputs, making informed decisions and driving strategic initiatives. In fact, according to the World Economic Forum, analytical thinking is the highest priority for skills training from 2023-2027.
Technological Literacy
Basic digital skills are increasingly important in the modern economy. According to Skills England’s 2024 report, basic digital skills are important to 92% of employers. Yet around 7.5 million working age adults do not have basic digital skills, and less than half (41%) of the UK workforce can do all 20 tasks deemed essential digital skills for work.
Socio-Emotional Attitudes
The socio-emotional attitudes which are expected to grow in importance most quickly are curiosity and lifelong learning. In a world of fast-changing skills, continuous growth is crucial. Focused learning is also key to keeping skills relevant and ready for emerging opportunities and obstacles.
AI and Big Data
AI and big data rank seventh for skills growing in importance today, with 60% growth in demand predicted by 2027. Yet, AI and big data is currently ranked third among company skills-training priorities from 2023-2027 and the number one priority for companies with more than 50,000 employees.
Embracing Gen AI at Work
There is a concern that an increasing number of jobs will be automated and performed by machines. However, keeping humans in the loop remains essential and evidence suggests leading companies are using AI to augment human capabilities, not replace them. This is, in part, because AI tends to excel in some areas but fall short in others. A BCG study coined the term “jagged technological frontier” and highlighted how AI’s helpfulness really depends on the task at hand with AI less likely to be proficient at more varied and complex job tasks
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Given that humans and machines are more likely to develop a symbiotic relationship, H. James Wilson, Global Managing Director of Technology Research and Thought Leadership at Accenture and Paul R. Daugherty, Accenture’s Chief Technology and Innovation Officer, have highlighted three “fusion skills” that people will need to excel in this new era of AI-human collaboration.
Intelligent Interrogation
Intelligent interrogation involves prompting Large Language Models (LLMs) in ways that will produce measurably better outcomes. Studies have shown when gen AI tools are instructed to break down a task into its constituent parts, their performance dramatically improves. In fact, simply adding the phrase “Let’s think step by step” to an LLM’s instructions can increase the accuracy of its output by more than threefold across a range of tasks from math to strategic reasoning.
It is also important to harness LLMs for innovative thinking. Many workflows, such as strategic planning and product design are iterative processes. To get the best results from AI you can steer it to generate multiple solution pathways that go beyond simple, binary choices.
Judgment Integration
Judgment integration in using generative AI at work involves recognising when and how to intervene effectively, ensuring outputs are reliable, accurate, and explainable. For instance, you should be mindful of biases in your prompts as these can affect results.
You should also stay on high alert for errors or “hallucinations.” Automated AI systems can be perceived as infallible but humans need to be clear of their limitations so they do not fall foul of two notable errors: errors of commission, where one follows an incorrect suggestion from an automated system, and errors of omission, where one fails to take action because the automated system did not suggest it.
Reciprocal Apprenticing
Help AI work smarter for your business by embedding rich data and insights into the prompts you provide, thereby training it to be your cocreator. As you teach the AI, you’ll also learn to guide it through more advanced tasks. Once a specialized skill for data scientists, reciprocal learning with AI is now a vital skill for professionals across all fields.
Before assigning a problem to an LLM, you can guide its reasoning by teaching it the “least-to-most” approach. This method involved breaking a complex challenge into smaller, simpler steps, solving the easiest first, and building on each solution. Research from Google DeepMind has shown that the least-to-most approach improves the accuracy of AI’s output from 16% to 99%.
You can also train your LLMs to learn new processes by walking it through a set of examples within your prompts, also known as “in-context learning”. This approach allows you to tailor pretrained LLMs like GPT-4 or Claude to your specific needs without the potentially arduous process of adjusting their parameters. As you refine your instructions by adding context, adjusting language and testing responses, you can gradually master the AI’s capabilities while achieving more nuanced and accurate results.
Adaptability is the Key to Success
The future of work is not about being replaced by AI, it’s about thriving alongside it. Success in the AI-driven workplace will belong to those who can adapt quickly, embrace lifelong learning, and leverage AI as a tool to amplify human ingenuity.
To keep pace with these shifts, workers may need to go beyond conventional educational pathways and embrace innovative learning opportunities like apprenticeships, online courses, and hands-on training.
As Claire Davenport aptly put it in her TEDx Talk: "Job security in the future won’t look like job security in the past. In the future, job security will be knowing that you have the skills and the support network to change as the world changes.”
At Quench, we’re committed to helping individuals and organizations navigate this transformation. If you’re unsure about how to best navigate this AI-era, you can book a call with our team.
