Why AI skills are crucial for AI ROI

AI investment is at an all-time high, but fewer than half of business leaders believe their workforce is ready to use it effectively. The uncomfortable truth? The next phase of AI won't be won by who adopts first, but by who builds the skills to sustain real value.

There's a widening gap between what AI can do and what companies are prepared to deliver. According to McKinsey, 30-40% of current work activities could be automated by 2030, yet 44% of business leaders believe their workforce isn't ready for AI adoption. Organisations that don't build internal capability risk turning even the most advanced tools into costly shelfware.

To turn AI from potential into performance, business leaders need to stop treating skills as an afterthought and start seeing them as the foundation for practical AI integration.

Why the skills gap is killing AI ROI

AI adoption is accelerating, but a growing disconnect between tools and workforce capability is stalling progress.

Research shows 34% of CEOs admit they lack the digital knowledge to lead AI effectively. That uncertainty cascades downward with 22% of employees reporting minimal or no training on AI tools. This isn't a minor training gap; it's a strategic risk that directly undermines return on investment.

The impact is predictable: low adoption rates, missed opportunities, and diluted ROI. C-suite leaders are 2.4 times more likely to cite employee readiness as a major barrier than technical issues. The message is clear: AI adoption isn't primarily a technology challenge, it's a people challenge.

Training is the key to ROI

While 76% of CEOs are investing in upskilling, the scope and speed vary widely. Too many businesses focus narrowly on technical teams and overlook broader functions.

To capture real value, training must be built into every stage of transformation:

• Make it role-specific: Training should be job-relevant and accessible across all functions; from HR and marketing to procurement and customer service.
• Build structured pathways: Move beyond ad hoc workshops to systematic capability-building programmes with clear progression.
• Focus on application: Use pilots that provide quick feedback, measurable outcomes, and visible wins.

AI adoption accelerators are designed to support businesses in building practical capabilities and helping teams identify where AI can drive the most value. Rather than starting with tools or models, the focus should be on practical capability-building, to help teams identify high-value use cases and build confidence in applying AI in real operational settings.

This hands-on approach not only accelerates adoption, but also reveals what kind of training and support actually moved the needle. It reinforces a core lesson that when employees are equipped to work with AI in the context of their day-to-day challenges, organisations are far more likely to achieve measurable, scalable impact.

Embedding AI literacy across the business builds trust, accelerates adoption, and empowers employees to innovate with confidence. It also drives more ethical, transparent decision-making. That's what regulators, clients, and stakeholders now demand.

Why human expertise still drives automation

AI may be powerful, but it operates without context. It can analyse patterns and automate decisions, but only humans can interpret those outputs through the lens of business strategy, social nuance, or ethical responsibility.

Human oversight prevents AI from reinforcing bias, misclassifying data, or producing harmful outcomes. These are the risks that multiply when systems train on flawed or incomplete datasets. From product recommendations to policy decisions, contextual judgement transforms AI insights into meaningful action.

Employees trained to work alongside AI don't just use it, they improve it. They spot inefficiencies, identify new use cases, and refine systems based on real-world feedback. This co-creative relationship transforms AI from a static tool into a dynamic partner for change.

People enable performance. Training delivers returns

To unlock AI's full value, organisations must treat training as core infrastructure, not a bolt-on. The next wave of transformation won't be won by those who spend the most on platforms, but by those who best prepare their people to use them.

That means aligning technology investments with serious commitment to training, support, and change management. Executives need to take ownership of these cultural and capability shifts, and it's not something that can be delegated to IT. Leaders who embed learning into their own development and champion organisation-wide upskilling consistently see stronger, faster returns.

Without a workforce that understands, trusts, and actively applies AI, even the most advanced systems will underperform. Companies must rethink transformation strategies to put human-AI collaboration at the centre; not as a future aspiration, but as a present-day imperative.

Looking ahead, organisations that thrive will be those building human capability and technical readiness in parallel. The path forward demands execution, rather than continuous experimentation.

The bottom line for executives

The critical question isn't "what tool should we buy?" but "what skills do our people need to make this work?" That's the shift that separates leaders from laggards.

Those who invest in people and systems today will be best positioned to lead in tomorrow's AI-driven economy. The organisations that act now on skills will be the ones turning AI into lasting ROI.

At AND Digital, we offer an end-to-end service that combines strategic insight, technological capability, and cultural change to help you build a future-proof AI strategy. Get in touch today to discover how we can partner with you on your journey to success.