Who Owns AI Skills Development?

This article was cowritten with Marjaana Murtomaa, a Splended advisor.

"Who is responsible for ensuring that our people develop AI skills?"

Is it HR? The leadership team? IT? The AI experts?

The answer is simple: everyone.

To truly integrate AI into the way we work, we need robust organizational cultures. We need curiosity, experimentation, knowledge sharing, learning leadership, and individual responsibility. We also need transparency –?because AI skills shouldn’t be the domain of a few experts but a shared capability across the organisation. And, just as importantly, we need courage. Learning AI means stepping outside of comfort zones, embracing uncertainty, and being willing to fail in the pursuit of growth. For example, in one company, the AI lead was being very open about her own hesitations and qualms about using AI. She also publicly reported on use cases where AI was unable to yield tangible results.?

AI learning starts with curiosity

The biggest myth about AI is that learning it requires technical expertise. In reality, AI is becoming more accessible: but only to those who are curious enough to explore it.

At one company, a finance manager started using ChatGPT to automate reporting tasks. She wasn’t a data scientist, but by testing the tool, asking questions, and iterating, she found ways to save hours of manual work. What happened next? She shared her learning with her team, inspiring them to experiment.

Curiosity is the starting point. If we wait for formal training programmes before engaging with AI, we risk falling behind. In fact, it becomes more engaging to participate in training once you’ve mastered the basics.?

How to encourage curiosity:

• Give employees time and space to test AI tools in their daily work
• Normalise learning in public—share insights, failures, and experiments
• Recognise and celebrate AI-driven improvements, no matter how small

Curiosity alone is not enough—developing AI skills requires courage. Employees must be willing to test new tools, ask difficult questions, and challenge traditional ways of working. It takes courage to embrace AI despite uncertainty, to admit gaps in knowledge, and to risk failure in the pursuit of learning.

A senior HR leader was initially unsure about using AI for interview scheduling, worried it might create a rigid or impersonal candidate experience. However, after trialling an AI-powered scheduling tool, she found it significantly reduced delays, improved communication with candidates, and freed up recruiters’ time to focus on more strategic aspects of hiring. Seeing the positive impact, her team became more open to exploring AI in other areas of recruitment.

You can build courage in learning about AI by:

• Encouraging employees to share not only successes but also setbacks and lessons learned
• Creating a psychologically safe environment where risk-taking is valued
• Providing support and reassurance—reminding teams that AI learning is a journey, not a test

Experimentation: learning by doing

AI skills are built through hands-on experience. We need to simulate real-life situations, not practice with random use cases that don’t apply in our line of work.?

Consider a product design team exploring how AI could support their work. Instead of waiting for an AI expert to teach them, they run a one-week learning sprint, testing AI tools for ideation, prototyping, and customer insights. At the end of the sprint, they will have concrete lessons. Some tools work, some don’t, but most importantly, they have first-hand experience.

How to create a culture of experimentation??

• Encourage teams to test and reflect, even small AI wins count
• Provide low-risk environments for AI exploration
• Empower cross-functional learning: bring IT, business, and design teams together

Sharing knowledge: the power of learning in public

One of the biggest challenges organisations face is AI knowledge staying siloed. If only AI specialists understand the tools, adoption slows down.

In one company, a software developer built an AI-powered script to automate a tedious manual process. Initially, he kept the tool to himself, thinking, “It’s just a small hack.” But after presenting it in a company-wide AI forum, multiple teams saw its potential and adapted it to their own needs.

Knowledge grows when it’s shared. If AI learning happens behind closed doors, it benefits no one.

How to encourage AI knowledge sharing:

• Set up AI knowledge-sharing sessions—let people showcase what they’ve learned
• Create an internal AI playbook: a shared resource for AI tips & best practices
• Reward transparency: highlight and reward those who actively share AI knowledge

Learning leadership: leading by example

AI skills development isn’t just an HR initiative—it’s a leadership responsibility. Leaders don’t need to be AI experts, but they do need to set the tone.

A great example comes from a CEO who openly documented her AI learning journey. She shared how she was using AI to automate emails, generate insights, and refine strategy documents. Seeing their leader embrace AI in a real and personal way made employees more open to experimenting themselves.

How leaders can support AI learning:

• Show vulnerability—it’s okay not to know everything
• Encourage AI discussions in team meetings
• Lead by example—test AI tools and share experiences

Individual responsibility: No one is "too busy" for AI

Some employees hesitate to engage with AI, thinking:

?"That’s IT’s job." "I don’t have time to learn AI." "I’ll wait for formal training."

The reality??

AI is a skill like any other. Just as professionals upskill in new technologies, business models, or industry trends, AI needs to be part of everyone’s professional development.

Organisations can create the right conditions for AI learning, but ultimately, individuals need to take responsibility. Whether it’s testing an AI-powered assistant, joining an internal AI learning group, or simply staying informed, everyone has a role to play.

How to promote individual AI ownership:

• Set personal AI learning goals—one small step at a time
• Integrate AI into daily work instead of waiting for formal training
• Encourage peer-to-peer learning—mentoring, small group sessions, and AI buddies

The key takeaway: AI skills development is a collective effort

• AI skills development is not one department’s responsibility, it’s everyone’s.?
• Organisations need transparency in AI knowledge—learning should be shared, not siloed.
• AI upskilling isn’t a one-time event—it’s a continuous process that requires curiosity, experimentation, and leadership.

The future of AI learning: a shared journey

AI is more than just technology—it’s a way of working, thinking, and evolving. The organisations that thrive will be those that embrace AI as a skill to develop, a habit to nurture, and a shared opportunity.

Progress isn’t about waiting for perfection; it’s about taking that first step, experimenting, and learning together.

So, who owns AI skills development? We all do. And that’s what makes it so powerful.