Thanks to AI, work will look very different in the near future than it does today. According to the World Economic Forum, 85 million jobs will be impacted by AI by 2030, and millions of new jobs will be created that don’t yet exist.
In a world where the pace of change is accelerating dramatically, it will be our skills -rather than our education, work history or past achievements – that define our value.
In practical terms, employers will be less concerned about what we know or have achieved in the past and more interested in how we can apply knowledge and abilities to solving modern business challenges.
So, what will this mean in the age of AI? How do we prepare for a world where machines will carry out many of the tasks that humans have traditionally had a monopoly on? And what skills will we need to ensure we remain relevant and able to create value? Let’s take a look.
Two Core Skillsets For An AI Future
I believe the skills essential for staying relevant in the future can be divided into two groups. Broadly speaking, we can refer to these as AI skills and human soft skills.
Firstly, having AI skills doesn’t necessarily mean becoming an AI engineer or data scientist.
Instead, it involves the ability to use AI effectively, augmenting our own abilities and overseeing its output. This means becoming an effective AI collaborator, delegator, and supervisor.
As AI becomes increasingly omnipresent, the ability to identify and use the best tools will be crucial in virtually every profession.
Secondly, human soft skills represent abilities that AI either can’t do yet or can’t do as well as humans. These skills are rooted in the qualities that have made humans so successful as a species in evolutionary terms. They allow us to work together, solve complex problems using diverse data, navigate social situations, creatively solve problems, critically evaluate progress, and create emotional connections with others.
As machines become more capable, the value of these uniquely human abilities increases. These two skill subsets are complementary, and developing them in tandem is key to building future-proof skills.
Let’s explore each of these skill sets in more detail.
AI Skills
AI skills are a broad category encompassing everything that has to do with working with AI effectively.
Of course, it includes the technical data and computing skills needed to design, build and deploy AI systems. But not everyone will need to do that.
It also covers general AI literacy, which means understanding what AI can do and how to apply AI tools to achieving specific goals.
This involves understanding the AI landscape in terms of the available tools and applications, and their capabilities and limitations, as well as proficiency in using and operating these tools.
It covers skills such as prompt engineering, which involves being able to frame human and business problems in a way that AI can address.
A central concept is “augmented working” – a term that’s frequently used to describe the ability to use AI to automate routine tasks, allowing a human professional to work more efficiently.
Understanding how to use AI to aid and boost creativity is a valuable skill, too. This could involve using it to generate ideas or create multiple iterations of our own ideas to suit different audiences.
People with skills needed to supervise AI workforces and act as the critical “human-in-the-loop” required to ensure accuracy, safety and fairness will be highly valued in workforces of the future.
Crucially, so will those with an understanding of the ethical and legal implications, such as an ability to recognize when there is a danger of bias or breach of privacy or when an organization’s use of AI might be overstepping the boundaries set out by regulation and legislation.
Soft Skills
With AI taking care of much of the technical work, human soft skills – things that machines can’t yet do – will become exponentially more valuable.
Among the most important will be the ability to strategize at a high level.
For example, ask an AI delivery optimization algorithm to plot the most efficient route for a van driver to drop off parcels, and it will do it more effectively than a human.
What it probably won’t do is suggest exploring drone delivery. Or reducing the weight of packaging to make deliveries more fuel-efficient. This is because most AI applications are highly specialized and don’t have the “general” intelligence capabilities of humans.
Creative problem-solving is another vital soft skill. Humans excel at lateral thinking, connecting disparate ideas, and imagining novel solutions to complex problems. Our ability to envision and articulate a better future – whether in technology, society, or the environment – is uniquely human. This imaginative capacity, combined with the power to inspire others towards these visions, will remain crucial in an AI-driven world, allowing us to conceptualize and pursue innovations that AI alone cannot conceive.
Developing plans that encompass long-term goals and take into account a multitude of factors that aren’t necessarily going to be in the training data will be out of reach of AI for a long time.
Then there’s critical thinking, which involves objectively analyzing and evaluating every aspect of a problem, situation or opportunity in order to make a judgment. While AI can critically assess a plan of action or an idea, once again, it’s limited by its training data, which may or may not contain the specific insights required.
Teamwork, leadership and mentorship all require explicitly human skills, too, including a high level of emotional intelligence. This is our ability to recognize and respond appropriately to our fellow humans on an emotional level and is essential to collaboration and relationship-building.
Partnership building, for example, is critical in modern business. An AI’s lack of emotional intelligence means it will always be at a disadvantage when it comes to the subtleties of negotiating, building rapport, and establishing the alignment of mission and values, which are critical to effective partnering.
And human soft skills are still important for project management, where there’s a need to balance resources, budgets, time constraints and any number of unexpected factors that could emerge.
Once again, we can see that computer intelligence is still too specialized to deal with many potential scenarios that can throw a spanner in the works of even the most carefully laid plans.
Adaptability and Life-Long Learning
One skill, perhaps more than any other, that will determine whether we remain relevant in the AI era will be our ability to adapt to change and continuously learn and improve.
Technology is constantly evolving, and the AI available in ten years’ time will most likely be far beyond anything we can imagine now. No matter how carefully we prepare for it now, it will take us by surprise. So, the ability to adapt and keep our knowledge and skills up-to-date is crucial.
This isn’t just about keeping pace with technology; it’s about developing a change-oriented mindset that will allow us to continue to perform as the world becomes more complex and uncertain.
The tradition of front-loading ourselves with education in our formative years is increasingly outdated. Seeking out roles where we will continuously learn, as well as pursuing opportunities for self-directed learning, can all help us to develop this mindset.
Likewise, the human skills we’ve discussed – communication, creativity, emotional intelligence – are not innate traits that some are born with and some aren’t. They can all be cultivated through practice and diversity of experience!
By focusing our efforts on developing both human and AI skills and developing the habits of embracing change and lifelong learning, we can give ourselves the best chance of thriving in the age of AI.
