Core Skills We Need More Than Ever in the AI Age

With tech CEOs signaling strategic changes in worker requirements in the emerging “AI era,” knowledge workers are probably thinking about what skills will hold value for future career development. People just coming into the workforce need to be thinking about which core skills will help them to distinguish themselves as they establish their careers.

Core skills are not “how to use AI” – which can be learned. You’re going to need more than that.

The future of jobs – the World Economic Forum report

The World Economic Forum’s Future of Jobs Report for 2025 is based on data from 1000+ global companies across a wide range of industries. Looking ahead to 2030 (which sounds so far away, but it’s not), several macro-trends will impact work and workers:

1. Digital access and the AI-driven technology era, including AI and data processing, robotics, automation, and energy generation & management.
2. Increasing cost of living, reflecting concerns about inflation, workforce slowdowns & changes, and slower growth.
3. Climate change and mitigations, tied into physical and local challenges, increasing energy demands, and demands for environmental stewardship.
4. Demographic shifts in many geographies due to aging and declining workforce numbers in higher-income economies, against expanding working-age populations in lower-income economies.
5. Geoeconomic fragmentation, affecting companies with global operations and changing worker locations and market dynamics.

Looking at job trends as a result of these macro-trends, the WEF Report makes some predictions. They think the following types of careers will have the biggest increase in demand: software development, big data analysis, AI and machine learning specialists, cybersecurity, and general technology literacy, renewable energy engineers, environmental engineers, autonomous vehicle specialists, nursing, aging healthcare specialists, higher education, and software architecture & engineering. The highest demand change will be in farm workers, labourers, and agri-related jobs.

On the other hand, they think the demand for the following types of careers will decline the most: executive assistants, administrators, cashiers, data entry, clerks, and bank tellers.

Most knowledge worker roles will see at least a modest increase in demand.

Automation and output

How automation will impact work and work outputs is potentially a fundamental shift that we, as knowledge workers, need to get our heads around. In the WEF report, the analysts comment that the proportions of total task delivery that are human, tech, or a combo is that the automation parts (tech or hybrid) will increase significantly in the next 5 years. They also postulate that the total amount of work done by machines and humans may increase, with both performing higher-value tasks in the same amount of time or in less time than it takes now. The extent to which automation will impact output will vary depending on the industry.

Nevertheless, as more output and income are derived from automation, advanced machines, and algorithms, it’s an open question how much employees will get to share in this prosperity.

Strategically, leaders ought to be thinking about how tech can enhance human work, and how talent development and upskilling can help people to find and add value in this collaboration between tech and humans. What are the skills needed to differentiate the value provided?

What does the WEF report say about core skills?

Here’s the summary of which skills are increasing in priority, according to employers:

If you look at the list, there are many skills that align with learners, with thinkers, with curiosity. Don’t ever think that “soft skills” aren’t important:

The top 10 core skills are complemented by [skills] that reflect the important role of technical proficiency, strong interpersonal abilities, emotional intelligence, and a commitment to continuous learning demonstrate respondents’ expectation that workers must balance hard and soft skills to thrive in today’s work environments.

The bottom-left quadrant: Skills that could be substituted by Generative AI

These are the skills that have a relatively low rating now and as forecast for 2030. The hypothesis is that many of these skills are most likely to be taken up via Generative AI:

I have to say, though, that reading, writing, and mathematics should be a going concern for future talent acquisition. Not sure how one acquires critical thinking skills without the basics, for one. For two, these types of skills are highly correlated to creativity, innovative thinking, and technological literacy. Reading is also correlated with relationship-building competencies like empathy and open-mindedness. Besides that, these activities are undervalued success factors.

Which skills should you cultivate?

As a person dealing with all of this change, what are the core skills one should cultivate?

1. Self-efficacy, resilience, flexibility, and agility. It’s a pretty safe bet that our jobs and roles are changing, as are market conditions, customer needs, and the tech landscape. Those who can take ownership of their ability to manage the changes and continue to provide value will be more successful. Importantly, a lot of this will need to be built on “self” – you need to own your development.
2. Cognitive skills, creative thinking, and analytical thinking. Being able to come up with new or different ways of doing things will be important and not easy for AI. Digital transformation is going to accelerate how often businesses and teams are faced with unfamiliar situations or overwhelmingly complex problems. We need people who can bring truly powerful thinking skills to meet these challenges.
3. Leadership and social influence. Whatever the innovation, people inspire people. People build organizational trust and psychological safety. People make or break change management. We will continue to need people who can bring out the best in others, who can identify strengths and weaknesses, and coach people on those “soft” core skills that matter. People who have strong leadership skills will be highly valued.
4. Technical literacy, AI and big data, and critical thinking. Regardless of your role, you must develop tech literacy and critical thinking and get used to working with AI and big data. You’ll need to know what you are looking at, to evaluate quality, to curate information, to question recommendations, to consider fair use and equity in the data, and to make the most effective use of available tools and information.
5. Lifelong learning, curiosity. The perennial skillset. As automation takes over low-level tasks, you should expect that you will need to focus more on the new stuff, the unusual stuff, and the complex stuff. Learning and curiosity are the foundation for your ability to develop whatever new skills or competencies will be needed. We also need interdisciplinary thinkers to provide sense-making with so much data at hand. Be ready for the next opportunity.
6. Networks and cybersecurity. We all do our security training, but the emerging “change” is that we can’t see networks and cybersecurity is something one team does, and we just try to comply with basic safety standards. The more you understand how things work in a world of distributed data and given the numerous risks of using LLMs, having more than a passing knowledge of networks and cybersecurity will be helpful to you.
7. Design and UX. Making, creativity, design, prototyping, and testing based on hypotheses and a deep understanding of customers still require skilled people, even if we are using AI-based tools to speed up the process or build prototypes. We should expect design and UX to drive collaboration and co-creation among customers, colleagues, AND technology.

These skills continue to be important:

1. Reliability – being steady and stable.
2. Service orientation and customer service.
3. Empathy and active listening.
4. Resource management and operations.
5. Dependability and attention to detail.

Connecting the dots: How education and training need to change to support us

One final thought: We also need education and training to support us. This is true for adult lifelong learners like us, but maybe more importantly, for the generations who haven’t entered the workforce yet.

Educators at Marzano Research put it this way: We need to shift from collecting dots, to connecting dots.

Linda Naiman says “connecting dots” in the workplace is about seeing patterns, making connections across data sets, and generating innovative ideas —all capabilities that align with those core skills.