Best skills to learn for the future according to new data

Every career advice account on your feed is telling you to "learn AI," which is roughly as useful as being told to "get good at computers" in 1995. The advice is not wrong, it is just too vague to act on, and vague advice is exactly how people end up taking a random online course that does not actually move the needle on getting hired. The real data on what skills actually matter for the next five years is more specific, and more interesting, than the generic advice suggests.

Two of the most rigorous sources tracking this, the World Economic Forum and LinkedIn's own hiring data, agree on something that cuts against the simple "learn to code" narrative, the skills rising fastest are not purely technical, they are technical skills paired with a specific set of human ones, and the combination matters more than either alone. Here is what the actual research says you should be spending your time on.

What the data actually says about the next five years

Start with the scale of change, because it explains why this question matters more now than it used to. According to the World Economic Forum's Future of Jobs Report, drawing on a survey of employers worldwide, 39 percent of the core skills workers use today are expected to change or become outdated by 2030. The same report projects 78 million net new jobs created globally by that point, even after accounting for roughly 92 million roles displaced by automation and economic shifts, genuine growth, but growth that depends entirely on workers actually having the skills the new roles require.

Employers themselves see this gap clearly. Sixty-three percent cite the skills gap as their single biggest barrier to business transformation, and 85 percent say they plan to upskill their workforce, though most lack a structured way to actually do it. That gap between employer intent and employer execution is worth remembering, it means the burden of actually closing career skills gap often falls on individual workers who move first, not the organizations that are still figuring out how.

The technical skills climbing fastest

On the technical side, the WEF's own skills outlook chapter is specific rather than vague, AI and big data literacy is the single fastest-growing skill category, expected by 87 percent of surveyed employers to grow in importance, followed by networks and cybersecurity at 70 percent and general technological literacy at 68 percent. LinkedIn's 2026 Skills on the Rise report, built from actual hiring and profile data rather than employer surveys, backs this up with real market behavior, job postings requiring AI literacy grew more than 70 percent year over year, with AI engineering, operational efficiency, and AI business strategy topping the list of fastest-growing skills overall, a pattern CIO Dive's reporting on the same data confirmed independently.

AI literacy does not mean learning to code

Here is the detail most generic advice skips entirely. LinkedIn's own breakdown of what is actually rising fastest includes categories like AI for business, AI for design, responsible AI, and tech-enabled business transformation, alongside the more technical AI engineering roles, which means the fastest-growing AI literacy skills are not exclusively about writing machine learning code. They are about knowing how to apply AI tools to a marketing plan, a design process, or a business decision, a bar that is genuinely achievable without a computer science degree, and arguably more relevant to the majority of entry level roles than deep technical AI development ever will be.

The human skills that are not going away

If the technical side of this story gets most of the attention, the human skills side is where both organizations agree the story is incomplete without it. The WEF report found analytical thinking remains the single most essential core skill overall, considered critical by roughly seven in ten employers, with resilience, flexibility, and agility close behind at 67 percent. LinkedIn's hiring data shows the same pattern from a different angle, leadership and people management skills, specifically cross-functional collaboration, team management, mentorship, and executive and stakeholder communication, are rising fast enough to sit alongside the AI-related categories rather than trailing behind them.

The honest takeaway from both reports together is that this is not a choice between technical skills development and human skills, it is a combination employers increasingly expect from the same person, someone who can actually use AI tools productively while also communicating results, managing ambiguity, and working across a team, rather than someone who is purely technical or purely interpersonal.

The gap between knowing this and actually doing something about it

This is where a genuine opportunity sits for anyone early in their career willing to move now. LinkedIn's research found that two-thirds of executives expect their employees to proactively build AI skills within the next six months, yet fewer than half of US professionals say they currently feel supported in doing that advancement. That is a real, measurable gap between what employers want and what the existing workforce has actually built, and it is exactly the kind of gap a young professional with no entrenched habits or legacy workflow to unlearn can close faster than someone ten years into a career.

What this means for how you should actually spend your time

Put together, the practical path is more specific than "learn AI" ever was. Pick one applied AI skill relevant to the field you actually want, AI for business analysis, AI-assisted design, AI-assisted writing or research, rather than assuming you need a technical AI engineering background to be considered AI literate, since the data shows employers value application far more broadly than pure development skill. Pair that technical skill deliberately with one human skill the research consistently flags, analytical thinking if you want to strengthen how you solve problems, or collaboration and communication if you want to strengthen how you work with others, since the WEF and LinkedIn data both point toward combination, not specialization in isolation, as what actually gets rewarded.

Given that 39 percent of core skills are expected to shift within five years, the better mental model is treating skill-building as something you do continuously rather than a credential you earn once and set aside. The professionals getting ahead of this shift are not the ones with the most impressive single certificate, they are the ones who built the habit of updating what they know before their employer had to ask them to.