AI is no longer a futuristic buzzword. It’s embedded in the tools businesses use every day, from customer service chatbots to predictive analytics. Yet research shows that 51% of SME decision makers admit they don’t understand AI well enough to use it strategically (Omdena).
That lack of understanding isn’t just academic. It blocks real ROI. Because if leaders don’t “get” AI, the organisation will never move beyond surface level automation.
The gap isn’t in technology. It’s in leadership knowledge. And until SMEs close it, they’ll struggle to compete.
The Real AI Barrier: Leadership, Not Technology
What most businesses do
They hand AI to technical teams or outsource it entirely. Leaders assume AI is a “tool problem” rather than a leadership capability.
What effective businesses do
They treat AI knowledge as a core leadership skill. Leaders don’t need to code models — but they must understand enough to:
- Ask the right questions.
- Judge ROI vs hype.
- Spot ethical and brand risks.
If leaders stay in the dark, AI becomes a bolt on. If they engage, AI becomes a growth driver.
Related reading: How AI and Automation Help Businesses Save Time and Increase Efficiency.
Why 51% Still Don’t “Get” AI
- Hype Overload
Leaders are bombarded with jargon — generative AI, neural networks, multimodal inputs. Most tune out. - Skill Gaps at the Top
Many SMEs invest in staff training but forget senior management. The boardroom remains the blind spot. - Risk Aversion
Without knowledge, AI feels risky. Leaders avoid committing budget or time. As a result, pilots stall. - Misplaced Focus on Tools
AI isn’t about “which platform.” It’s about workflows, customer journeys, and business impact.
Building AI Confidence in the Boardroom
1. Upskill Management, Not Just Teams
- Most brands do: Send staff on AI bootcamps.
- Effective brands do: Run leadership workshops, giving decision makers fluency in AI’s business use cases.
2. Link AI Directly to P&L
Leaders need frameworks to map AI use cases to margin, LTV, or efficiency. For example, predictive churn modelling can reduce revenue leakage.
3. Establish AI “Trading Rituals”
Make AI part of weekly decision making. Instead of dashboards gathering dust, use AI to surface anomalies, highlight risks, and propose options.
4. Test Without Tech Debt
Start with small, non invasive pilots (customer service replies, automated reporting). These prove value without locking into expensive systems.
Avoiding the Pitfalls
AI can drive growth — but only if leaders avoid three traps:
- Shiny object syndrome: Don’t chase tools without strategy.
- Overpromising automation: AI won’t fix bad processes.
- Delegating AI knowledge away: Leaders must stay engaged to judge value.
FAQ
Q1: Do SME leaders need to learn coding to understand AI?
No. They need business fluency: what AI can do, where it fits, and what ROI looks like.
Q2: How can SMEs start closing the AI knowledge gap?
Begin with leadership workshops, small pilots, and linking AI to real financial outcomes.
Q3: Isn’t AI too expensive for SMEs?
Not anymore. Many tools (e.g., Zapier, Make.com, ChatGPT) offer low cost entry points. The challenge is strategy, not budget.
Q4: What’s the risk of ignoring AI?
Falling behind competitors who use it to scale efficiency, personalise experiences, and cut costs.
Conclusion
AI isn’t optional anymore. But too many SMEs stall because leadership knowledge hasn’t caught up. The real AI gap isn’t technical — it’s strategic.
Leaders who upskill themselves, link AI to P&L, and integrate it into weekly decision making will outpace those stuck chasing shiny tools.
Ready to clear the grey around AI? Book a discovery call and see how Mostly Grey Digital helps SMEs build AI confidence that translates into growth.
Key Takeaways
- 51% of SME leaders admit they don’t understand AI (Omdena).
- The barrier is leadership knowledge, not access to tools.
- Upskilling management is critical — not just training staff.
- AI should link directly to P&L, not sit as an isolated experiment.
- Small, low risk pilots build confidence and momentum.