For many SME operators and searchers, artificial intelligence can seem like a luxury, something reserved for tech giants with vast budgets and dedicated engineering teams. But this perception is outdated. A fundamental shift has been underway: AI tools are now more accessible, practical, and vital for maintaining a competitive edge than ever before.
The question facing small and medium enterprises is no longer if they should adopt AI, but how to do so strategically, balancing innovation with limited resources and day-to-day operational realities.
To explore this, we spoke with two experts from the Moonbase Capital community who are on the front lines of AI adoption:
- David Ferrin, Managing Director at Projecting by Izertis and part of our Advisory Board, is a financial services leader and founder of Delta AI, which builds practical, cost-effective AI solutions – which he left to focus full time on Projecting which deliver projects in Financial Services.
- Joining him is Ahmed Bakir, Data and AI Consultant at Moonbase Capital, with over 24 years of global experience in data science, enterprise tech, and public-sector AI deployment.
We asked for their insights on what AI can really mean for SMEs.
Redefining AI: Beyond the Hype
The first step for SME leaders is understanding what AI actually means in practical terms. David emphasizes this point:
“I would probably define what AI is, because I think a lot of tools have AI already integrated in them. Just using Outlook or Google Mail or Google Drive, you’re using a lot of AI.”
This perspective is crucial for SME operators who may feel overwhelmed by AI’s technical complexity. Many businesses are already benefiting from AI capabilities built into existing software subscriptions. Microsoft’s Copilot, Google’s productivity suite, and numerous specialized business applications now include AI features that can immediately enhance productivity without additional investment.
Ahmed reinforces this operational focus:
“Much of the successful AI applications are at an operational level serving specific functions within an organization, and hence take place under the hood.”
Rather than pursuing transformational AI projects, SMEs often achieve better results by identifying specific workflows where AI can reduce manual effort and improve accuracy.
Practical Implementation Without Breaking Operations
The fear of operational disruption prevents many SME leaders from exploring AI applications. However, successful implementation follows established project management principles rather than requiring revolutionary changes.
David advocates for systematic planning:
“It’s about being systematic and making sure that you’re running it as if you were running a big project.”
This means defining current processes clearly, establishing testing protocols, and maintaining backup systems during transitions.
Consider a practical example: An SME looking to automate invoice generation should implement changes during low-activity periods, run parallel systems temporarily, and test with friendly customers before full deployment. This approach mirrors how successful businesses have always managed operational changes.
Ahmed recommends starting small:
“Taking small, gradual steps towards change is always the best approach for companies wanting to modernize their operations while maintaining their core business disruption-free.”
Pilot projects running alongside existing operations allow teams to adapt gradually while providing value to stakeholders.
Avoiding Common Implementation Pitfalls
SME leaders face unique challenges when evaluating AI solutions, particularly distinguishing between marketing promises and practical capabilities. David warns:
“The biggest issue is knowing what is possible and what is out there. There’s a lot of hype.”
His experience with a seemingly simple meeting scheduling project illustrates this challenge.
Despite numerous AI-powered tools in the market, none handled the client’s specific requirements around delegated calendar access and multi-person coordination.
“There were things that a human could do really easily, even if it takes a lot of time and effort, but it’s easy. And the tools that were in the market at that point weren’t able to do it properly.”
Ahmed, on the other hand, identifies three critical pitfalls SMEs must avoid:
- Lack of organizational readiness: AI implementation requires stakeholder alignment, team training, and process changes. Success depends on adequate resource allocation and realistic timelines.
- Absence of technology and data strategies: effective AI applications require proper data collection, storage, and processing capabilities. SMEs must establish these foundations before implementing AI solutions.
- Inadequate technology infrastructure: budget considerations should include servers, cloud platforms, and connectivity requirements that scale with business needs.
The solution involves finding knowledgeable support to assess what’s genuinely achievable versus what’s marketed as possible. For moderately technical SME leaders, experimenting with individual AI tools can provide valuable learning before committing to integrated solutions.
Strategic Opportunities for Competitive Advantage
Despite resource constraints, SMEs can leverage AI for significant competitive advantages in specific areas.
1. Marketing
Marketing represents one of the most accessible applications. David explains:
“You can ask it not just to do the article, but to do four bullet points for your social media posts. Then you can use a different AI to generate a nice image to put on a social media post.”
This approach transforms marketing from a resource-intensive activity requiring specialized skills, into a manageable process where business knowledge guides AI execution. SME leaders who understand their value propositions can generate professional marketing content, social media campaigns, and customer communications without hiring specialists.
2. Research
For searchers specifically, AI offers opportunities to enhance due diligence processes, automate financial analysis, and improve deal sourcing efficiency. Document analysis, market research, and financial modeling can all benefit from AI augmentation while maintaining the human judgment essential for investment decisions.
Ahmed suggests that unique competitive advantages emerge from integrating proprietary data and processes:
“One way to find unique opportunities or niches is by integrating proprietary data, processes or knowledge into AI models.”
An investment firm serving niche markets could incorporate its specialized knowledge into AI tools, creating automated analysis capabilities that competitors cannot easily replicate.
3. Customer Service
Customer service automation presents another practical opportunity. Advanced solutions like those from companies such as Happy Robot can handle routine inquiries with human-like interactions, allowing SMEs to provide better customer service without expanding staff.
The key insight is that SMEs don’t need to build AI from scratch. Ahmed notes:
“There is often no need to build solutions in-house, except in cases where companies have complex processes or large proprietary data that need to be integrated.”
Most competitive advantages come from thoughtfully applying existing AI tools to specific business challenges.
Conclusion
The AI landscape for SMEs is defined not by technological sophistication but by practical application and strategic implementation. Success comes from understanding that AI augments human capabilities rather than replacing them, focusing on operational improvements rather than transformational changes, and maintaining realistic expectations about what current technology can achieve.
SME operators and searchers who approach AI strategically, starting with clear objectives, implementing gradually, and focusing on proven applications can achieve significant competitive advantages without the resources of tech giants. The opportunity exists not in building the most advanced AI systems, but in thoughtfully applying accessible AI tools to create measurable business value.
At Moonbase Capital, we recognise that SMEs navigating technological transitions need partners who understand both the opportunities and constraints of operating with limited resources. As AI continues evolving from experimental technology to essential business capability, the advantage will belong to operators who act thoughtfully rather than those who wait for perfect solutions.