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Build AI skills by starting with the work your team actually does: identify recurring tasks and skill gaps, teach everyone a shared baseline, practise relevant scenarios by role, and make human review and safe-use rules part of each exercise. Track whether people can complete and check the work, then adjust the plan as needs change.
Why build AI skills across the team?
Small and medium-sized enterprises (SMEs) account for over 99% of companies and 60% of business-sector employment in OECD economies, according to the OECD’s 2025 report. In its late-2024 survey of more than 5,000 SMEs in Austria, Canada, Germany, Ireland, Japan, Korea and the United Kingdom, 31% said they used generative AI. That figure describes the surveyed businesses, not every small business or country.
Survey respondents reported that generative AI helped improve performance and compensate for skill gaps and labour shortages. They also raised concerns including copyright and legal or regulatory issues. These are reported experiences and concerns, not a guarantee of results or a determination of your business’s obligations. The practical implication is to develop both the ability to use AI and the judgment to decide when its output needs checking or should not be used.
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How to build AI skills in a small business
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Choose work problems before choosing courses or tools
Ask staff where work is repetitive, where capacity is tight, and where missing skills slow a process. Select a small number of recurring tasks to practise on, such as preparing a first draft or organizing information, if those tasks fit your business. Define what a useful result would look like and what a person must verify. OECD survey findings indicate possible benefits for some SMEs, but do not establish that every workflow is a good AI candidate.
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Set a shared AI-literacy baseline
Give everyone a practical introduction to what generative AI can do, where it may be useful, why its answers need human judgment, and which business rules apply. Do not limit learning to technical specialists. The OECD’s 2025 analysis, “Bridging the AI skills gap: Is training keeping up?”, found that only a small percentage of courses in the subset of countries it analysed included AI content, and that most programs with AI content focused on advanced skills. The OECD argues for broader general AI literacy; the summary does not give a single percentage to apply to all courses or countries.
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Practise realistic scenarios by role
Use exercises drawn from the tasks each person or role handles. Have participants try the task, assess the output against agreed criteria, correct it, and explain what they changed. Include examples where the tool produces an incomplete or unsuitable answer, so that checking is practised rather than merely discussed.
Microsoft’s “Transform your business with AI” learning path is listed as a beginner course for business leaders and owners, with planning and responsible adoption among its topics. Microsoft Learn for Organizations also describes AI learning resources for business and technical roles. These are vendor-provided examples, not a complete or provider-neutral curriculum; check the live pages for current content.
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Learn individually, then compare examples together
Self-paced material can help people learn at different speeds, while a group session lets the team discuss how AI affects its actual work and compare approaches. Microsoft’s SMB guidance recommends combining online resources with group training and notes that group learning can reveal employees interested in becoming AI champions. A champion can share examples and help colleagues practise, but should not replace clear ownership of business rules or review.
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Build safe use and human review into every exercise
For each scenario, agree what information may be entered, which outputs need verification, who is responsible for final decisions, and what to do when an answer is uncertain or raises a concern. The OECD reports SME concerns about copyright and legal or regulatory matters; Microsoft’s learning path includes responsible adoption and governance or security topics. Neither source sets the legal requirements for your location, so check the rules applicable to your business and sector.
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Track progress and revisit the plan
Choose a measure tied to the task rather than a generic count of courses completed. For example, check whether staff can carry out the scenario, recognize an output that needs correction, and follow the agreed review process. Microsoft Learn for Organizations describes plans, milestones and tracking features; use them if helpful, or keep a simple team record. There is no universally established training metric for every small business.
Review the selected tasks and rules when workflows, tools, or business needs change. Keep what is useful, revise exercises that no longer match the work, and add learning where staff are still unsure.
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How to choose a training route
Self-paced learning, a facilitated workshop, and advisory support can each suit different constraints. Compare them against the team’s actual needs rather than treating a provider’s course list as the curriculum.
| What to compare | Questions to ask |
|---|---|
| Fit with the work | Does the content reflect the roles, workflows, and recurring tasks your team selected? |
| Audience and level | Will all staff gain basic AI literacy, or does the offering mainly train specialists in advanced skills? |
| Practice and feedback | Will people try realistic tasks and get a chance to assess and improve their work? |
| Responsible use | Does it address human review, governance, security, and the safe-use expectations relevant to your business? |
| Time, cost, and access | Can a small team participate within its budget and schedule, and can staff access the material they need? |
| Progress | Can you tell whether staff can apply the skills to the chosen work, not just whether they attended? |
These are decision criteria, not a ranking of providers. Microsoft Learn for Organizations describes curated resources, plans, milestones, and tracking, but its availability and contents can change. For a starting point on readiness, the OECD SME AI Readiness Tool is a pilot for G7 SMEs; it takes about five minutes, requires no technical expertise, and describes its results as indicative—not an official OECD assessment or endorsement.
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Keep learning connected to business priorities
A useful plan is small enough to practise and specific enough to review: chosen tasks, a shared baseline, role-based exercises, agreed checks, and a way to see whether people can apply them. Microsoft 365’s Brenna Robinson has emphasized aligning an SMB’s AI plan with the vision its leadership has already communicated. Make the connection explicit by explaining which work the team is practising and what responsible, useful performance looks like.
The OECD’s AI Skills for Business Competency Framework, added in July 2025, is another reference point for thinking about business AI skills. Use frameworks and courses to inform a plan, but adapt practice and expectations to your own work, team, and applicable rules.
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