AI and human skills: the role of HR in organizations

In 2025, companies significantly accelerated their investments in artificial intelligence. Yet, according to a studyby Forrester, 30 to 60% of employees with access to an AI tool simply stop using it. Even more surprising, 77% of employees believe that AI reduces their productivity, mainly due to the time spent learning, verifying results, or managing new tasks.

The conclusion is simple: investing in technology without investing in human skills is setting yourself up for failure.

Because the success of an AI strategy largely depends on how it is used. On the ability of organizations to prepare, support, and engage their workforce. And this is where HR becomes essential.

AI and human skills: definition and challenges

AI is transforming human work

Artificial intelligence is redefining the scope of human skills.

AI tools can automate certain tasks, accelerate access to information, and generate content at scale. According to McKinsey, existing technologies could theoretically automate tasks representing more than half of working hours in the United States.

These capabilities shift the need for human intervention.

Where employees were once focused on execution tasks, they are now expected to deliver higher-value activities: analyze, arbitrate, decide. As highlighted by Forrester, AI could enhance nearly 20%of jobs in the coming years, far more than it will eliminate.

Human skills at the core of value creation

This shift in tasks fundamentally changes expectations for employees.The World Economic Forum estimates that 39% of key workforce skills will be transformed by 2030.

Among the now essential skills:

• analyzing AI-generated results
• applying critical thinking to outputs
• making decisions in complex environments
• collaborating effectively with teams and tools

These skills, often referred to as soft skills, are becoming direct drivers of performance. Analytical thinking already ranks among the most sought-after skills, followed by resilience, flexibility, and leadership.

More to read: 9 AI challenges HR must adress in 2026

A strategic challenge for organizations and HR

These skills cannot be improvised. They must be developed, structured, and integrated into a real training strategy.

However, the gap is striking: according to Forrester, only 22% of workers have received formal training on AI, and only 25% master the basics of prompting.

Without proper support, AI remains underused, misunderstood, or used in risky ways. This is what is known as “Shadow AI”: autonomous, unregulated usage that escapes governance.

For organizations, the challenge is twofold:

• deploying powerful tools
• ensuring teams know how to use them effectively

92% of companies plan to increase their AI investments, but only 1% consider themselves mature in this area.

In other words: it is not AI that creates value, but how humans use it.

No employee buy-in? No AI projects.

Powerful tools… but underused

In many organizations, deploying AI solutions does not translate into real adoption. Tools are available, sometimes widely distributed, but rarely used in daily work.

This is partly due to a lack of understanding of use cases. Employees do not always know when or how to use AI, or how to integrate it into their tasks.

The tool is then perceived as optional or even burdensome.

The human factor: the main barrier to AI success

Contrary to popular belief, barriers to AI adoption are not primarily technical, they are human.

Several factors explain this resistance:

• fear of being replaced or monitored
• lack of trust in AI outputs
• difficulty changing work habits
• absence of clear guidelines on expected usage

Without support, these barriers lead to superficial adoption or even outright rejection.

From availability to adoption: a shift in mindset

Deploying a tool is not enough. It must be understood, tested, and integrated into daily practices.

This requires moving from availability to adoption:

• training on real use cases rather than features
• encouraging experimentation in a secure framework
• promoting best practices internally
• supporting managers in driving adoption

When management is truly involved, adoption improves significantly.

Change management: the key to successful AI initiatives

Like any transformation, AI adoption requires structured change management.

This includes:

• clear communication on objectives and benefits
• progressive upskilling
• a secure and shared usage framework
• ongoing monitoring of practices and results

Adoption challenges are not random. They are predictable human reactions tied to uncertainty and lack of trust.

Read more: AI in the workplace: why are HR teams on the front line

HR as architects of AI adoption

AI adoption is not just an IT responsibility. It depends on the organization’s ability to transform usage, skills, and work practices.

In this context, HR plays a key role:

• structuring skill development through tailored learning paths
• defining governance frameworks to prevent misuse while enabling experimentation
• supporting change by addressing fears and resistance
• aligning AI with talent management and career development

HR becomes a true architect of transformation.

When AI weakens the skills it is meant to strengthen

The risk of cognitive laziness

One paradox of AI is that it can weaken the very skills it is meant to enhance.

By automating thinking, information search, or content creation, AI reduces the cognitive effort required. In the short term, this saves time. In the long term, it can create dependency.

Employees may gradually delegate:

• situation analysis
• response structuring
• even reasoning itself

The risk: reduced human vigilance in the face of AI hallucinations.

Critical thinking: essential but fragile

As answers are generated instantly, the temptation is to accept them without question.

However, AI models do not produce truth. They produce probabilities, sometimes biased or incomplete.

Without critical thinking, employees may:

• validate incorrect information
• reproduce existing biases
• make decisions on weak foundations

The more convincing AI becomes, the greater the risk of overconfidence.

The gradual erosion of human skills

Another risk emerges: the gradual erosion of skills.

The less a skill is used, the more it deteriorates. This is especially true for:

• analytical thinking
• structured writing
• complex problem-solving

Over-reliance on automation can lead to a loss of intellectual autonomy.

Finding the right balance

AI should be framed, not restricted.

The goal is clear: use AI as an augmentation tool, not a substitute for thinking.

This requires:

• training employees to challenge AI outputs
• integrating verification steps into workflows
• encouraging active rather than passive usage
• valuing human skills in performance evaluation

AI can be a powerful productivity lever. But without structure, it can also weaken capabilities.

More to read:

• By 2030, HR will not do the same job
• What AI should NOT do for your HR
• When voice control makes its way into HR
• HR statistics: key figures for 2026
• What is a no-code solution