What strikes me most about AI today is not its complexity. It is how accessible it has become.
My mother is 84 years old and like many people of her generation, she has an active dislike for technology, which she proudly nurses. Nearly all of our conversations eventually gravitate towards a problem she is having with her mobile phone or her Sky TV, and she feels quietly vindicated as she hands me her phone or remote control to fix the problem. Yet when we introduced an Alexa device into her room, she took to it immediately.
She uses it to check the weather before a round of golf. She asks it to play her favourite Sergio Mendes records. She uses it to hear the latest news and find out what is happening in Thailand where my brother lives.
What's remarkable is that Alexa is powered by some of the most sophisticated technology ever developed. Yet it is also one of the simplest technologies she has ever used. I don’t even think that my mother even categorises it as technology, just a radio that can talk back.
That, for me, is an interesting lesson about AI. The technology itself may be extraordinarily complex, but using it often isn't.
It also seems that my mother is not alone, and when I researched the adoption of AI amongst older business owners, I found a Tech Hub Ireland / Enterprise Nation report that showed 76% of surveyed Irish small-business founders were using AI tools, but adoption was even higher among older founders: 87% among founders aged 46–55 and 79% among founders aged 56–65. That already suggests AI is significantly different from many previous technology shifts.
The change that is being driven by AI also reflects what happened with mobile phone adoption in many developing countries. For decades, access to telecommunications depended on expensive physical infrastructure.
Then mobile technology arrived.
Instead of having to replicate decades of infrastructure investment, many countries were able to leapfrog directly to mobile networks. The technology acted as a leveller and I believe AI has the potential to do something similar for small businesses.
SMEs typically have fewer barriers, faster decision-making and a greater ability to experiment. And in many cases, that means a small business can adopt and benefit from AI faster than a much larger competitor.
There is also a personal reason why I find AI so interesting.
Before founding my own business, I spent much of my career in a large corporation. One of the advantages of working in a large organisation is specialisation. If you work in marketing, you spend most of your time doing marketing. If you are an engineer, you spend most of your time engineering. If you are in sales, you spend most of your time selling. Running a small business is obviously very different.
As an SME owner, I quickly realised that the things I enjoyed doing and the things that created the most value for the business often represented only a small part of my day. The reality was that I was spending significant amounts of time on administration, reporting, invoicing, VAT returns, customer emails, scheduling, data entry and countless other tasks that simply needed to be done.
Most of this is unavoidable, but they are far removed from the reason most people start a business and this is where I believe AI can have its greatest impact.
Not by replacing entrepreneurs or employees, but by helping remove some of the repetitive, low-value work that consumes so much time. By reducing that burden, AI allows business owners to spend more time with customers, more time growing their business, more time innovating and more time focusing on the work they genuinely enjoy and where they create the most value.
For many SMEs, that may be the lowest-hanging fruit of all.
The reality is that all of this is no longer just theory. Research from Microsoft, McKinsey, Boston Consulting Group, Harvard Business School, Stanford and MIT is beginning to show where AI creates value at work — and, just as importantly, where businesses should start.
Based on this, I have put together 9 key insights on how AI can make a positive impact on small business owners.
Large companies may have bigger budgets, but they also have more complexity. Legacy systems, procurement processes, compliance reviews, IT backlogs and multiple approval layers can slow AI adoption down.
SMEs often have a different advantage: speed. In a small business, the person who understands the problem is usually close to the person who can approve a solution. That makes it easier to test a practical AI use case, learn quickly and improve the workflow without waiting months for a formal transformation programme.
For SME owners, this matters. AI does not have to begin with a major technology project. It can start with one repeated process, one admin burden or one customer-facing workflow that can be improved.
SME Takeaway:
Start with one focused, low-risk AI opportunity and build from there.
Research sources:
Microsoft Work Trend Index; AI adoption research.
For years, larger businesses had a clear advantage because they could afford specialist teams, consultants, analysts, software platforms and technical departments. SMEs often had to rely on the owner or a small number of staff to cover everything.
AI changes that equation. A small business can now access tools that help draft marketing content, analyse information, summarise documents, build simple workflows, support customer service and improve reporting without major infrastructure investment.
That does not mean AI is effortless. The challenge has shifted. Access is no longer the main barrier. Prioritisation is.
SMEs need to decide where AI can create the greatest practical value, which workflows are worth improving first and what support is needed to implement changes properly.
SME Takeaway:
Access is no longer the main barrier. The challenge is choosing where to start.
Research sources:
Microsoft, McKinsey and AI adoption studies.
One of the assumptions about AI is that it is mainly being driven by younger, more technical founders. Recent Irish small-business research suggests the picture is more interesting.
A Tech Hub Ireland / Enterprise Nation report found that while 76% of surveyed Irish small-business founders were using AI tools, adoption was even higher among older founders: 87% among founders aged 46–55 and 79% among founders aged 56–65.
That matters because it challenges one of the biggest myths about AI adoption. Older business owners are not necessarily resistant to AI. They are often resistant to complexity. When AI is simple, useful and connected to daily business tasks, adoption can happen quickly.
This also explains why AI may be different from previous technology shifts. A business owner does not need to understand the technical architecture behind a large language model to ask it to draft an email, summarise a document, improve a customer response or prepare a simple marketing plan.
SME Takeaway:
87% of founders aged 46–55 and 79% of founders aged 56–65 are already using AI tools in their businesses.
Research sources:
Tech Hub Ireland; Enterprise Nation.
Many business owners associate AI with advanced technology: machine learning models, complex data science or enterprise automation. In reality, many of the most valuable first projects are much simpler.
McKinsey’s research on generative AI highlights major value potential in areas such as customer operations, marketing and sales, software engineering and knowledge work. For SMEs, the practical version of this is usually more straightforward: customer enquiry support, marketing content workflows, proposal drafts, admin automation, reporting and internal knowledge search.
These are not futuristic projects. They are everyday business processes that already exist and already consume time.
SME Takeaway:
Start with work your business already does every week. The “boring” AI projects often deliver the fastest return.
Research sources:
McKinsey generative AI research.
The strongest early use cases for AI are often the least glamorous: email handling, meeting notes, information search, document summaries, customer replies, follow-up tasks and reporting.
Microsoft’s Work Trend Index has shown how much of the working week is consumed by communication, meetings, email and searching for information. In its 2023 report, Microsoft found that the average employee spends 57% of their Microsoft 365 time communicating in meetings, email and chat, while 62% of surveyed workers said they struggle with too much time spent searching for information.
That matters for SMEs because these are exactly the tasks that often fall on the owner, founder or small team. AI can help reduce the friction around finding information, drafting responses, summarising documents and turning scattered notes into useful outputs.
SME Takeaway:
The first AI project should often focus on reducing repetitive admin, not replacing skilled work.
Research sources:
Microsoft Work Trend Index; workplace productivity studies.
AI is no longer something businesses can treat as a distant technology trend. Microsoft and LinkedIn’s 2024 Work Trend Index found that 75% of global knowledge workers were already using generative AI at work, with usage nearly doubling in six months.
This creates both an opportunity and a risk for SMEs. The opportunity is that small businesses can now access powerful tools at low cost. The risk is that employees, competitors and customers may move faster than the business itself.
For SME owners, the goal is not to chase every new tool. It is to create a sensible, structured way to test AI and decide where it can create value.
SME Takeaway:
Move from curiosity to structured experimentation before competitors build an advantage.
Research sources:
Microsoft Work Trend Index 2024; industry adoption reports.
One of the most interesting findings from workplace AI research is that AI can be especially useful for less experienced workers.
A major study by Erik Brynjolfsson, Danielle Li and Lindsey Raymond examined the use of a generative AI assistant among customer support agents. The research found productivity gains of around 14–15% on average, with much larger gains for novice or lower-skilled workers.
For SMEs, this is particularly relevant. Small businesses often cannot afford large training teams, extensive onboarding programmes or specialist departments. AI can act as a support layer, helping people draft better responses, find information faster, follow processes more consistently and learn while they work.
SME Takeaway:
AI can help small teams improve capability without immediately increasing headcount.
Research sources:
MIT, Stanford, NBER and related productivity studies.
Many organisations are now experimenting with AI, but experimentation is not the same as business impact. Having access to ChatGPT, Microsoft Copilot, Gemini or Claude does not automatically improve a business process.
The real value comes when AI is applied to a specific workflow: reducing a manual step, improving response time, creating a better handover, summarising information or helping staff complete a task more consistently.
This is why SMEs should avoid starting with the question: “Which AI tool should we use?” The better question is: “Which business process should we improve first?”
Before implementing AI, it is worth mapping the process: what happens now, who does what, where information gets stuck, which tasks repeat and where AI could remove friction.
SME Takeaway:
The question is not “Which AI tool should we use?” It is “Which business process should we improve first?”
Research sources:
Microsoft Work Trend Index; McKinsey; Deloitte and industry surveys.
The most successful AI adoption will not simply involve doing the same tasks a little faster. The bigger opportunity is to redesign how work moves through the business.
For an SME, that might mean changing how customer enquiries are captured, summarised and followed up. It might mean redesigning how quotes are prepared, how marketing content is planned, how internal knowledge is accessed or how weekly reporting is produced.
BCG has argued that generative AI value depends on understanding where the technology can improve work and productivity, rather than applying it randomly across the organisation.
For small businesses, this is a vital point. AI should not just be bolted onto existing processes. It should help business owners rethink where time is being lost, where customers are waiting too long, where staff are repeating work and where better workflows could create real value.
SME Takeaway:
AI should not just speed up poor workflows. It should help create better ones.
Research sources:
BCG; Microsoft Work Trend Index; workplace productivity research.
The research points to a simple conclusion: AI is most valuable for SMEs when it is practical, focused and connected to real workflows.
Using published productivity research from Microsoft, McKinsey, NBER and Sage, I created an illustrative model of a typical Irish SME. The example looks at common weekly tasks across a small business and estimates how much time could be reclaimed by applying AI-supported workflows.
The result is significant: a small business could potentially save around 16.5 hours per week across routine, low-value and repetitive work.
For many SMEs, these are the low-hanging fruit. They may not sound exciting, but they are exactly where AI can create early value.
At Bowsy, this is the thinking behind our AI Project Teams. We help Irish SMEs identify practical AI opportunities, map the workflow and implement useful solutions through supervised graduate and postgraduate project teams.
The goal is not AI for the sake of AI. The goal is simple: less admin, better workflows and more time for the work that creates value.
To find out more visit https://www.bowsy.ie or reach out to us at: hello@bowsy.ie
Sources:
· Microsoft Work Trend Index 2023 — Will AI Fix Work?
https://www.microsoft.com/en-us/worklab/work-trend-index/will-ai-fix-work
· Microsoft and LinkedIn Work Trend Index 2024 — AI at Work Is Here. Now Comes the Hard Part
https://www.microsoft.com/en-us/worklab/work-trend-index/ai-at-work-is-here-now-comes-the-hard-part
· McKinsey — The Economic Potential of Generative AI: The Next Productivity Frontier
https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
· NBER — Brynjolfsson, Li and Raymond, Generative AI at Work
https://www.nber.org/papers/w31161
· Stanford SIEPR — Generative AI at Work
https://siepr.stanford.edu/publications/working-paper/generative-ai-work
· Enterprise Nation — Female, older and rural entrepreneurs leading Ireland’s tech revolution
https://www.enterprisenation.com/learn-something/female-older-rural-entrepreneurs-leading-ireland-tech-revolution/
· Tech Hub Ireland / Enterprise Nation — Natural Fit for Business PDF
https://a.storyblok.com/f/102007/x/3bcaa97dbd/tech-hub-ireland-report-natural-fit-for-business.pdf
· ThinkBusiness — Who are the early adopters of AI in Irish SMEs?
https://www.thinkbusiness.ie/articles/ai-adoption-small-business-confidence-gap/
· BCG — How Generative AI Is Transforming Business
https://www.bcg.com/capabilities/artificial-intelligence/generative-ai
· BCG — AI at Work: Momentum Builds, but Gaps Remain
https://www.bcg.com/publications/2025/ai-at-work-momentum-builds-but-gaps-remain