Overcoming the 5 Biggest Blockers to AI Upskilling

Artificial intelligence (AI) is transforming how we work, but many business leaders are still struggling to grapple with AI upskilling and reskilling. IDC’s InfoBrief, commissioned by Deel, AI at Work: The Role of AI in the Global Workforce, identifies the five most significant blockers for businesses in preparing their existing workforce for an AI-driven future:

• Limited employee engagement (57%)
• Budget constraints (51%)
• Lack of expert training staff (45%)
• Difficulty identifying skills gaps (34%)
• Fast pace of AI evolution (12%)

AI presents us with a generational shift, changing everything from worker experience to how countries compete for technological leadership. This means that overcoming these blockers involves rethinking our approaches to reskilling.

Here’s a step-by-step look at the main blockers to AI upskilling, with guidance on how to tackle each one.

The 5 biggest AI upskilling/reskilling blockers

1. Limited employee engagement

This is the most significant blocker, as employee engagement is the cornerstone of any upskilling strategy. Engagement can drop for several reasons, and rebuilding it takes more than sending periodic email nudges.

The mistake we see the most frequently is implementing a one-size-fits-all training program, which assumes all employees will engage with AI in the same way. But your marketing team has very different needs from your software engineers. While it’s important to make sure everyone has the same foundational knowledge (for example, your internal AI policies), the more personalized the training is across functions, the more value employees will see in it.

Managers should also be prepared to connect the dots between the training and their team’s daily work, and to raise their hands if what they’re being asked to learn is of no value. This avoids AI training being something teams feel pressured to complete simply “because leadership said so.”

Employee engagement is heavily influenced by workplace culture. AI is highly experimental, and teams need a ‘safe-to-fail’ environment to be curious and test out new tools. This kind of openness also encourages them to raise their hands when they spot potential issues, such as accidental bias or broken workflows. This turns AI learning into a collaborative experience rather than a prescribed to-do list, greatly enhancing engagement.

Another factor to keep in mind is employee sentiment. AI adoption can be a source of anxiety, with many workers fearing for their job security or feeling unsure of their place in an AI-assisted workplace. Pulse surveys and feedback loops can measure the impact this has on your teams, opening up a dialogue.

2. Budget constraints

AI training is becoming a fact of the modern workplace, whether your organization has widely implemented it or not. With secret AI use at work on the rise, even foundational training can ensure your teams are using it safely and compliantly – something well worth the investment.

While massive overhaul programs may be the right choice for some organizations, accessible, continuous microlearning can be just as effective and more cost-effective. Start with low-cost, high-impact initiatives such as peer teaching, internal workshops, and curated public resources. Leverage these to gauge your organization's appetite for AI knowledge, identify knowledge gaps, and start a dialogue with your employees about AI upskilling in a budget-friendly way. Depending on your location, there may also be government-led initiatives to support AI reskilling, such as the Artificial Intelligence Skills Alliance (ARISA) project in Europe or the U.S. federal government’s America’s AI Action Plan.

However, the most effective training will be tailored to your business, and eventually, you’ll need to educate your teams in your specific workflows and policies. Focus spending on scalable platforms that can adapt to your needs and evolving AI technology, rather than on one-off training sessions.

With Deel Engage, you can choose between our course library or build your own custom content in minutes, thanks to our AI-powered learning management system. Track the ROI of your L&D strategy by connecting learning metrics (completion, engagement) with performance outcomes.

3. Lack of expert training staff

Identify early adopters of AI within your organization, and create internal ‘AI mentors’ to participate in cross-functional training activities. Not only is this budget-friendly, but it also creates growth opportunities for these employees.

As you adopt new tools, lean on the vendor’s training resources. Many offer free enablement content tailored to enterprise use. If your arrangement doesn’t include tailored training, they may alternatively offer online office hours or on-demand courses.

Many people learn faster and retain more information when they learn by doing. AI copilots and simulations used to demonstrate real use cases (coupled with the safe-to-fail culture previously mentioned) give employees a sandbox to learn practical skills without fear of breaking something. This is much more effective than bringing in a consultant to deliver expensive lectures.

4. Difficulty identifying skills gaps

Typically, this blocker arises because leaders lack an understanding of which AI skills are needed. This affects even those who run routine skills gap analysis, paralysing L&D efforts. While your needs will differ depending on your organization, here are what we consider to be the most important skills:

Foundational: Basic AI literacy (for every employee)

• Understanding AI basics & terminology
• Recognizing AI strengths and limits
• Using common AI tools (ChatGPT, Copilot, etc.)
• Writing and refining prompts
• Data literacy & interpretation
• Ethical and privacy awareness
• Identifying automation opportunities
• Evaluating AI output critically
• Collaborating effectively with AI tools
• Knowing company AI policies

Advanced AI skills

• Building and fine-tuning AI models
• Data engineering and preprocessing
• Machine learning fundamentals
• AI governance and risk management
• Advanced prompt engineering
• Workflow automation and orchestration
• Integrating AI into business systems
• Creating custom GPTs or assistants
• Monitoring model performance
• Designing AI ethics and compliance frameworks
• Strategic workforce planning with AI insights

Skills-mapping tools, such as Deel Engage, can help you to visualize competencies and readiness gaps. This information is easily shared with employees, allowing them to clearly see their skill level, understand their growth opportunities, and access the learning needed to access them all in one platform. When learning is directly tied to advancement, engagement increases.

5. Fast pace of AI evolution

The key is to keep your L&D strategy light, flexible, and agile. That means focusing on continuous micro-learning, training in foundational skills before anything else, and leaning on AI-assisted learning to automatically keep up with any changes.

The fast pace of AI can make any upskilling initiative feel overwhelming, but that’s exactly why a rigid, one-time training program won’t work. Instead, regular learning sprints, short on-demand modules, and adaptive content recommendations ensure employees can continuously improve their AI skills.

As AI becomes the norm in the modern workplace, its rapid evolution is a reason to prioritize training, not to postpone it.

The way forward with AI upskilling

The organizations that master AI upskilling today will be the ones leading in AI innovation tomorrow, and they will do so by understanding that:

• Engagement grows when learning feels relevant, practical, and supported by leadership.
• Budgets go further when learning is continuous, measurable, and scalable.
• Expertise can be built internally through mentorship and applied learning.
• Data-driven skills mapping turns uncertainty into strategy.
• Agility is key to keeping pace with AI’s rapid evolution.

True AI leadership is about more than implementing the latest tools and attracting top talent. For a future-proof workforce, it’s about creating an environment where people can learn, adapt, and grow, and feel ready for whatever change is coming their way.