What You’ll Learn In This Guide:
- Key findings from WSI’s 2025 AI Business Insights Report
- The “familiarity-training gap” and what it costs your business
- Real-world examples of ROI from AI-trained teams
- Four steps to formalize AI learning for measurable impact
- How to turn self-taught curiosity into a coordinated, revenue-driving capability
Most businesses know AI can drive growth—but far fewer have trained their teams to use it effectively. WSI’s 2025 AI Business Insights Report, based on feedback from over 600 SME leaders, reveals a growing gap between AI awareness and formal training. While teams experiment with tools like ChatGPT for simple tasks, competitors are automating customer acquisition, optimizing pricing, and uncovering new revenue streams. The message is clear: familiarity alone won’t deliver results. This guide explores why formal AI training is now a competitive necessity, the costs of hesitation, and the practical steps to turn AI curiosity into measurable business impact.
Because the gap is widening fast.
WSI’s 2025 AI Business Insights Report: What 600+ Business Leaders Revealed About AI Training
Earlier this year, we introduced our 2025 AI Business Insights Report, which assesses the extent to which AI is being adopted throughout the business world. We surveyed over 600 business leaders worldwide, with the majority of these leaders (90.2%) involved in small or medium businesses. The survey’s results form the core of the 2025 WSI AI Business Insights Report.
Why this research matters to you: These aren’t Fortune 500 executives with unlimited budgets and dedicated IT teams. These are business leaders just like you—running SMEs, managing tight budgets, and looking for practical growth strategies that actually work.
The results reveal a growing awareness of AI, with more teams outside of leadership and digital marketing adopting it. However, it appears that this adoption has yet to be formalized on a wide scale. Action is not being taken, budgets are not being allocated, no training is being provided, and AI use within businesses tends to be limited to specific silos and departments.
What this means for your competitive position: While everyone talks about AI, most businesses are still figuring it out. Your opportunity lies in being among the first 30% who move from experimentation to systematic implementation.
The survey unearthed three main takeaways:
- The Planning-Action Gap: Many businesses recognize the importance of AI, but they have not yet developed action plans to integrate it into their workflows. They are certainly not allocating any significant portion of their budget to it. Confidence is growing, but action plans and budgets have not caught up. Business impact: Companies that create formal AI strategies see 40% faster implementation and better ROI.
- The Familiarity-Training Gap: Businesses and individuals are quickly becoming familiar with AI, but formal training still lags. This is today’s focus: How to bridge the gap between knowing AI exists and using it to drive measurable business results.
- The Departmental Expansion (With Silos Problem): Whereas AI adoption used to be confined to company leadership, this is no longer the case. AI is now being used across departments—from operations to sales. However, progress is still slow in this regard, as silos form within business structures and prevent widespread adoption. If you’re not enabling your teams with AI, you’re missing out on performance gains in all parts of your business. The opportunity: Businesses with coordinated, cross-departmental AI strategies report 60% higher productivity gains.
After exploring the first takeaway and its implications, we now turn our attention to the second one: businesses and the individuals in them are increasingly au fait with AI, but for the most part, not much formal training is taking place to make the technology an integral part of everyday business operations.
Why focus on training first? Because it’s the fastest way to turn AI curiosity into AI results. While strategy and coordination matter, your team’s ability to effectively use AI tools is what determines whether your AI investment pays off or becomes expensive experimentation.
TAKEAWAY #2: Businesses and Individuals are Familiar with AI, but Formal Training Still Lags
The survey found that 59% of respondents were now familiar with AI technology. Last year, this figure stood at only 38%, so this is a very encouraging sign. It is apparent that AI awareness is rapidly growing. However, familiarity does not necessarily amount to full implementation, complete with formal training.
Just over half of the respondents who said they were familiar with AI have not had any formalized training in the use of the technology. Once again, this is an improvement over last year, when only 31% of respondents had received any formal AI training, but the survey still shows that most AI familiarity today arises from self-guided learning rather than structured training.
What this really means: We have a generation of business professionals who can recognize AI tools but can’t systematically leverage them for business growth. It’s like being familiar with cars but never learning to drive strategically—you might get where you’re going, but you’ll never optimize your route or maximize your fuel efficiency.
The Training Investment Reality
Forty-eight percent of respondents said they had plans to invest in AI training for their employees. This is a marginal increase over the 2024 number. However, 36% remain undecided. The majority of business leaders are still hesitant to invest in the adoption of AI.
Let’s break down what this hesitation actually costs:
The 48% with training plans: These businesses are positioning themselves to capture AI’s full potential—improved efficiency, reduced costs, and new revenue opportunities.
The 36% who are undecided: While they debate, their competitors are gaining ground. Every month of delay means missed opportunities and widening performance gaps.
The remaining 16%: These businesses risk becoming irrelevant as AI-trained competitors outpace them in efficiency, customer service, and innovation.
Question for reflection: Which group does your business belong to, and what is that choice costing you?
Does This Sound Like Your Business?
✓ Your team uses ChatGPT for occasional tasks but doesn’t have systematic AI workflows
✓ You know AI could help your business, but you aren’t sure where to start with formal training
✓ Different departments are experimenting with AI tools in isolation
✓ You’re concerned about the investment in training vs. uncertain returns
✓ Your competitors seem to be doing AI ‘stuff’ but you’re not sure what
If you checked 2+ boxes, you’re experiencing the familiarity-training gap firsthand.
The Bottom Line on AI Familiarity vs. Training:
Familiarity gets you comfortable with AI. Training gets you results.
Familiarity says: ‘We use AI tools sometimes.’
Training delivers: ‘25% productivity increase in Q1, $50K cost savings in operations, 40% faster customer response times.’
The competitive reality: While you debate training investments, businesses with formal AI programs are already measuring ROI and scaling their advantages.
Why Does AI Hesitation Matter? (The Real Cost of Waiting While Competitors Act)
AI hesitation is more important than many people may think. AI may still be an emerging technology, but even at this early stage of its development, it is already showing itself to be a useful tool for maximizing efficiency and even profitability across a variety of business sectors.
It is revolutionizing customer relationship management and is even being used effectively for employee upskilling and making operational processes more efficient. It has been shown to increase productivity and save time (which means it saves money).
In addition, it helps with cybersecurity through functions such as network security monitoring, fraud detection, and endpoint protection. AI is already boosting productivity and profitability across departments. The problem is that too many businesses and their leaders are nowhere near realizing these benefits because they are reluctant to adopt the technology and institute formal training.
Here’s what AI hesitation is costing you right now:
While you wait, trained competitors are using AI to:
- Cut operational costs by 20-30% through automated processes
- Respond to customer inquiries 5x faster with AI-powered support
- Identify new revenue opportunities through predictive analytics
- Reduce manual work by 40% across departments
Time cost: Every quarter you delay formal AI training, competitors with trained teams pull further ahead.
Even though few businesses are formally training AI, there are plenty of individuals who understand its potential and are teaching themselves to use it. We are seeing the rise of the self-taught AI professional. Rather than waiting for their employers to take hold of the technology and start teaching them how to use it, they are learning independently through experimentation, online resources, and knowledge sharing. This demonstrates commendable initiative, but it also raises questions about the depth and consistency of AI knowledge across organizations.
The self-taught professional opportunity (and risk):
- Opportunity: You likely have team members with AI curiosity and basic skills already
- Risk: Without coordination, they’re using different tools, inconsistent methods, and potentially missing your biggest AI opportunities
Smart business move: Harness this existing interest through formal training that channels their enthusiasm into systematic, business-focused AI implementation.
There is a disconnect here that is not uncommon with the introduction of new technologies. Informal, self-taught familiarity generally precedes formal adoption and training. Without formal AI training, businesses miss out on its full potential—no matter how many employees are dabbling with it. Although the tools are becoming more accessible, they are not being introduced in companies through the human elements of knowledge transfer from trained experts, contextual understanding, and strategic application. Self-teaching can only go so far. Collaborative human exchange is essential for the complete adoption and optimal implementation of AI. By investing in formal training that balances technological capability with human judgment, businesses create an environment where AI serves as an extension of human expertise rather than a replacement for it.
Historical pattern recognition: Remember when websites were optional? When social media was ‘just for kids’? When mobile optimization was ‘nice to have’?
The pattern: Early adopters gained significant advantages. Late adopters spent more to catch up and never fully closed the gap.
AI follows the same pattern—with one key difference: The implementation timeline is accelerated. What took years with previous technologies is happening in months with AI. The good news is that you still have time to be an early adopter, but that window is closing faster than previous technology shifts.
The Next Strategic AI Steps: Formalizing Learning and Turning Familiarity into Applicable Skills
If your business is among those that have yet to begin formal training in the use of AI tools, there are steps you can take to rectify the problem. And the good news? You don’t need to start from scratch. Your team’s existing AI familiarity gives you a head start—now you need to systematize it for maximum business impact.
Most businesses see measurable improvements within 60-90 days of implementing these four steps.
Step 1: Develop Structured Learning Paths
Organizations should create clear AI learning pathways tailored to different roles and skill levels. This approach ensures that self-taught knowledge is supplemented with structured education addressing potential knowledge gaps.
Start here for SMEs:
- Marketing Team: AI for content creation, customer segmentation, and campaign optimization
- Sales Team: AI for lead scoring, proposal generation, and customer insights
- Operations: AI for process automation, data analysis, and efficiency improvements
- Leadership: AI strategy, ROI measurement, and ethical implementation
Time investment: 2-4 hours monthly per person, with immediate application to current projects. Pro tip: Begin with your most AI-curious team member as a pilot, then expand successful approaches to other roles.
Step 2: Implement Learning-by-Doing Programs
Combine formal training with hands-on projects that allow employees to immediately apply new AI skills to real business challenges, reinforcing learning while delivering tangible value.
Practical application approach:
- Week 1: Learn the AI tool or technique
- Week 2: Apply it to a current business challenge
- Week 3: Measure results and refine approach
- Week 4: Share learnings with the team and identify the next application
Example projects that deliver immediate value:
- Use AI to optimize email subject lines (measure open rate improvements)
- Implement a chatbot for common customer questions (track response time gains)
- Apply AI data analysis to identify top-performing marketing channels (redirect budget accordingly)
Each learning project should deliver measurable business improvement within 30 days.
Step 3: Encourage Knowledge Sharing
Set up internal communities of practice where teams can swap insights and examples. Not only does this tap into existing expertise, but it also reduces redundancy and accelerates the adoption of real-world solutions.
Simple knowledge sharing systems:
- Monthly ‘AI Wins’ meetings: 15 minutes where team members share successful AI applications
- Shared digital folder: Collect useful prompts, tools, and results that others can replicate
- ‘AI Tool of the Month’: One person researches and demonstrates a new AI capability
Benefits for business owners:
- Reduces training costs (team members teach each other)
- Ensures AI knowledge spreads organically across departments
- Creates accountability for AI adoption
- Identifies your natural AI champions for advanced training
Knowledge sharing can double the impact of your training investment by spreading successful applications quickly.
Step 4: Bridge the Confidence-Competence Gap
While self-directed learning is valuable, structured education provides the foundation and confidence needed for effective AI implementation across all departments. Invest in targeted training programs and collaborate with experienced AI consultants to transform tentative AI familiarity into actionable expertise, enabling leaders to make decisions with greater confidence and achieve measurable results.
Signs you need professional training support:
- Team members are hesitant to use AI for important tasks
- Different departments are using conflicting AI approaches
- You’re not seeing measurable ROI from current AI experiments
- You want to implement AI but don’t know where to start
Professional training ROI:
- Accelerated timeline: Get results in 60 days instead of 6 months
- Risk reduction: Avoid costly mistakes and compliance issues
- Strategic focus: Ensure AI investments align with business goals
- Confidence building: Team feels empowered to use AI systematically
Professional AI training typically pays for itself within the first quarter through improved efficiency and better decision-making.
Which Step Should You Start With?
- If your team is already experimenting with AI, start with Step 3 (Knowledge Sharing) to coordinate existing efforts
- If AI adoption is inconsistent across departments, begin with Step 1 (Structured Learning Paths)
- If you want immediate business impact, focus on Step 2 (Learning-by-Doing Programs)
- If you’re overwhelmed by AI options, jump to Step 4 (Professional Guidance) to create a strategic foundation
How WSI Can Help Fill the AI Training Gap (Turn Your Team’s AI Curiosity into Competitive Advantage)
With self-taught AI competence, you run the risk of keeping your AI familiarity at a surface level. If you take these four steps, you can develop deep AI competence across your organization.
WSI offers custom AI Adoption Roadmaps that combine the concepts of AI with practical, hands-on applications specific to your industry and unique business goals. These are not generic training courses and strategies. Each Roadmap is designed specifically for one business—like yours. Your Roadmap provides context-specific knowledge and can transform your team’s tentative AI knowledge into fully developed, professional mastery that generates measurable results.
Don’t stand by and passively allow AI adoption to progress informally, potentially sacrificing or at least delaying your opportunity to enjoy its benefits. Instead, take active steps to make AI an integral part of your operations.
That’s the WSI difference: We don’t just teach AI tools—we help you implement AI strategies that directly impact your bottom line.
Stop treating AI as an experiment. Start treating it like the business driver it is.
If you’re serious about AI adoption, start with training that delivers results. Book a consultation with a WSI AI Consultant and get a personalized roadmap for your team.
FAQs
Q: What is the “familiarity-training gap” in AI adoption?
A: It’s the difference between knowing AI tools exist and having the structured skills to use them for measurable business growth. Many teams dabble in AI without the training needed for consistent, high-impact results.
Q: Why is formal AI training important for SMEs?
A: Training turns AI from a casual experiment into a strategic growth driver—improving efficiency, cutting costs, and identifying new revenue streams across departments.
Q: What’s the risk of relying on self-taught AI skills?
A: Self-taught use can create silos, inconsistent methods, and missed opportunities. Without coordination, teams may duplicate efforts or overlook AI’s highest-value applications.
Q: How quickly can AI training deliver results?
A: Many SMEs report measurable gains—like faster customer response times, reduced manual work, and improved ROI—within 60–90 days of structured training.
Q: Where should a small business start with AI training?
A: Begin with the roles most curious about AI, focus on hands-on learning tied to current business challenges, and expand training across departments for greater impact.
Q: How can WSI help bridge the AI skills gap?
A: WSI creates custom AI Adoption Roadmaps that combine strategy, hands-on application, and role-specific training—ensuring your team can apply AI to drive measurable business results.
