It’s no secret that artificial intelligence (AI) is ramping up among businesses. Recent insights from Harvard Business Review’s Global Entrepreneurship Monitor research show that the most ambitious entrepreneurs are placing significant emphasis on AI.

More entrepreneurs are waking up to its benefits: the number of European business leaders integrating AI tools to conduct business grew by 5.5 percentage points between 2023 and 2024. Further research reveals that over 60% of European businesses have implemented dedicated AI teams.

It’s no longer a question of if but when AI will make its way into an organization’s business processes, no matter the size. Ahead of that, entrepreneurs must have the right action plan in place to get their teams AI-ready, otherwise they risk falling behind. Here are some tactics for preparing teams for working with AI, reducing anxiety, and maximizing positive results.

Apply the 80/20 rule for AI upskilling

Don’t expect teams to become tech wizards or data scientists when strategizing AI deployment. What’s important is to upskill employees in the fundamentals of using AI. In most cases, AI tools aren’t being integrated throughout every process.

Before diving into educating teams on working with AI technology, entrepreneurs need to pinpoint where it makes sense to hone in on. Focus on the core workflows where AI is being used and upskilling accordingly. Here’s where the 80/20 Rule—that 80% of value is derived from 20% of effort—comes into play.

In most cases, AI is used in repetitive workflows that involve a lot of low-stakes tasks. That could include processes like:

• Analyzing and summarising data and generating insights accordingly.
• Providing customized product recommendations.
• Forecasting project needs in the early stages.

Prompting AI tools, critically analyzing AI outputs, and understanding AI’s limitations and risks are core areas to upskill. That way, entrepreneurs can unlock AI’s value and turn teams from AI novices into AI natives.

Bridge the gap between theory and practice

Small businesses make up 99% of the EU’s business landscape, and that works in their favor to make AI training easier and more manageable. AI education shouldn’t be a one-off exercise. Tools are constantly evolving, and so must training alongside them. Theory-heavy training won’t resonate with teams, though—practical workshops are much more effective for building confidence and clarity in using AI tools. A shocking 42% of European employees view AI as a threat to their jobs, and a hands-on approach is the best remedy for that anxiety.

Developing masterclasses with distinct parts or modules that focus on specific tools is an excellent blueprint for practical training. Maintaining a flexible structure, where employees can initially choose which workshops to partake in, can help nurture confidence and acceptance of AI.

Some employees will more naturally embrace AI tools. Celebrate the successes of these “AI champions” to build momentum around these team members as mentors for less experienced colleagues. This can also help alleviate anxieties around AI.

Measure what matters

Strong AI education is all about monitoring progress. Very few are going to be AI maestros when they first set out to use these tools. However, there are useful parameters to guide AI training blueprints.

For example, in interior design, useful core metrics include project timeline reductions and faster times to approvals. These metrics can be applied to goalpost KPIs for upskilling team members. KPIs are non-negotiable for adequate training in any skill area, as they ensure businesses are on the right track with their AI deployment, boosting efficiency and productivity, and securing ROI without harming customer relationships or undermining workflows.

An additional KPI that’s highly relevant in Europe’s climate-conscious landscape is nurturing awareness around sustainability measures. That could both cover how to use AI tools to uncover the most energy-efficient options in production or workflows, as well as understanding the environmental impact of AI in the first place.

Lean into the European competitive edge

European businesses face unique challenges in AI adoption. The region’s human-centric approach to AI means stricter compliance—the EU’s AI Act is the first of its kind. Yet these challenges can also be an opportunity for European entrepreneurs to lead responsibly: compliance-first adoption is an important trust-building aspect of AI strategy, from education to deployment.

European businesses tend to be small, and may not have the resources to implement APIs as easily. They may need to be more selective and efficient with the AI tools they integrate. This actually sets the basis for a more agile and targeted AI strategy that’s easier to train and expose teams to.

Another competitive advantage is that European businesses tend to be more culturally and linguistically agile: three out of five Europeans can speak a language other than their mother tongue. Why is this relevant to AI upskilling? It shows that most European businesses have a unique edge. They tend to be better at adapting to new forms of communication, working styles, and navigating different languages.

This is an extremely important competitive advantage when it comes to leveraging and maximizing AI. European teams can be empowered to help refine multilingual AI tools in languages other than English.

Cultural nuance is crucial to many businesses, especially those operating in different markets, but many AI tools aren’t adept at navigating that. Here’s where multilingual and multicultural teams should be trained to step in. They can be familiarized with critiquing the output of an AI tool based on cultural and linguistic nuances, particularly if AI is being used in customer-facing workflows.

For instance, a Spanish-based business has made sure to instruct AI tools in generating more personable outputs that align with the warm customs of the local market. That alignment can make or break leveraging these tools to meet customer expectations. When done correctly, it also leads to better ROI gains and a stronger competitive edge over rivals that might still be leaning on outdated and less streamlined processes.

Maximizing business impact from AI requires a strong training backbone for using AI. The teams working alongside the tools need to be empowered in applying them to their everyday work. For that to happen, entrepreneurs should apply hands-on, iterative training centered around the 80/20 rule to upskill, while turning to their unique competitive advantage.