AI for SME Operations: How Adrian Gan Runs a 10-Person Business Without a Bigger Back Office
Most SME owners hit the same wall as the business grows: orders go up, conversations pile up, finance gets messier, and the instinct is to hire. Adrian Gan, Managing Director of MIPOS.MY, asked a different question — and it changed how a 10-person team runs an e-commerce, retail, and POS installation business without a bigger back office.
Quick Answer
SMEs get the most value from AI by reducing repetitive work in customer service, finance, HR, and reporting — but only once the business pain point is clear. The pain point comes first. The tool comes second.
Many SME owners reach a point where growth starts to feel heavy. Orders increase. Customer messages increase. Finance becomes more complicated. HR admin takes more time. Reports are delayed. Margins become harder to see. The business is moving, but the owner is carrying more and more of the operational weight.
At that stage, the default move is to hire — one more admin person, one finance person, one HR person, one customer service supervisor. For Adrian, the question was different. Instead of asking “who else do I need to hire,” he started asking which part of the business was still too manual, too messy, or too dependent on one person. That single shift in framing changed how AI got used across the company.
Adrian Gan’s Business Context: A Lean SME With Many Moving Parts
Adrian runs MIPOS.MY, a business operating across e-commerce, retail showroom, and POS installation services. Like most SMEs, the team is lean — around 10 people are expected to manage a wide spread of functions across the business:
- E-commerce platforms such as Shopee, Lazada, and TikTok
- Retail showroom operations
- POS installation services
- Customer conversations across WhatsApp
- Finance reconciliation
- Platform fees and margin tracking
- Payroll, leave, and HR admin
- Internal tools and documentation
This is where SME growth gets difficult. From the outside, the business looks simple. Inside the operations, there are many small workflows quietly draining time, profit, and attention — and none of them show up on a P&L until margins start slipping.
The Problem Before AI: Growth Created More Manual Work
Customer Operations
The business handled thousands of WhatsApp conversations with customers, but had limited visibility into whether staff were following SOPs, whether service quality was consistent, or whether problems were surfacing early. Most of the time, issues only became visible once a customer complained.
Finance
Finance work meant reconciling orders, bank data, platform fees, and margins across different e-commerce channels — long hours of spreadsheet work, with no clear, immediate picture of true margin by platform. In an environment where Shopee and Lazada fees keep rising and pricing pressure is real, that blind spot is expensive.
HR and Admin
Payroll, leave tracking, payslip preparation, and tax-related calculations were also manual, and the business depended heavily on specific people knowing exactly how things were done. That created real operational risk: if one person was unavailable, the process slowed down or became inconsistent.
The Real AI Lesson: Know Your Pain Point First
One of the clearest lessons from Adrian’s implementation is this: AI becomes useful only when the business pain point is clear. When the pain point is unclear, AI becomes a distraction — testing tools, watching tutorials, building dashboards, trying to automate everything without ever solving the actual problem.
For Adrian, the pain points were specific and practical:
- Too many customer conversations to monitor manually
- No clear visibility of service quality
- Manual finance reconciliation across multiple platforms
- Unclear margins by channel
- Payroll and HR admin depending on manual processes
- Too much dependency on individual people
- Too much time spent rebuilding spreadsheets instead of reviewing exceptions
Once those pain points were named, AI had a business purpose. It stopped being about “using AI” and became about solving specific operational bottlenecks.
Strategy note: Before any AI tool conversation, write down the workflow that is costing you the most time, money, or visibility right now. That list — not a tool list — is where AI implementation should start.
The AI Implementation: Same Method, Different Departments
Adrian did not start with one big AI transformation project. He used a practical, repeatable method across the business:
- Find the most messy or repetitive process.
- Make the data visible.
- Use AI or automation to reduce the manual work.
- Keep humans accountable for review and decisions.
- Move to the next workflow.
This matters because many SMEs over-engineer AI in their own heads — assuming it has to mean a large system, a big consultant project, or a company-wide overhaul. Adrian’s story shows a more realistic path: solve one painful workflow, prove the value, then repeat the method.
AI in Customer Operations: From Hidden Conversations to Visible Service Quality
Before AI, customer conversations were scattered across WhatsApp — a lot of interaction, but limited visibility into what was actually happening inside those conversations. With AI, those conversations could be analysed more systematically. AI can support areas such as:
- Checking whether staff follow customer service SOPs
- Reviewing customer sentiment
- Flagging risky or unhappy conversations
- Transcribing voice messages
- Linking customer value to chat history
- Helping managers coach staff using real data
This shifts customer service from reactive to proactive — the business sees service quality earlier, instead of discovering problems only when a customer complains.
AI in Finance: From Spreadsheet Rebuilding to Exception Review
Finance is one of the highest-value AI opportunities for SMEs. Many owners do not struggle because they lack sales — they struggle because they cannot see their real margin clearly enough. For Adrian’s business, finance involved orders across platforms, bank transactions, platform fees, and margin reporting, all requiring heavy spreadsheet work before AI-assisted automation came in.
After automation, orders, platform fees, and bank data could be pulled into a pipeline, transactions matched, and exceptions flagged for human review. That changes the role of the team: instead of spending most of their time rebuilding spreadsheets, they spend it reviewing exceptions, understanding margins, and making better business decisions.
AI in HR: From Manual Payroll to Structured Workflow
HR is another area where small businesses carry hidden inefficiency. Payroll, leave tracking, timesheets, payslip generation, tax calculation, and employee communication look simple individually, but they consume real time every month. With AI and automation, the workflow becomes more structured:
- Timesheet checking
- Leave validation
- Payslip preparation
- Tax calculation support
- Email communication
- Monthly payroll workflow
This reduces manual dependency and improves consistency — and for a lean SME, every manual recurring process you remove is one less cost to growth.
Where Is Your Business Losing Time, Money, or Visibility?
Before you decide what to automate, get a clear read on where your operations are leaking time and margin.
Take the DigitalAI Readiness Assessment Join DigitalAI Business ClubThe Business Impact: 10 People + AI = Bigger Capability
Adrian’s case shows AI is not only about saving time — it is about increasing business capability. With around 10 people, the company supported work that would normally require more back-office headcount, across several roles:
- IT support through AI coding agents and internal tools
- Finance support through reconciliation, fee tracking, and margin reports
- HR support through payroll, leave, and tax workflow automation
- Admin support through CRM, documentation, and customer intelligence
The estimated cost avoidance was around RM16,000+ per month across several functional roles. The business also analysed around 38,000+ customer conversations and tracked around 44,000+ orders across platforms.
But the deeper value is not the cost saving alone — it is visibility. The owner can see more. The team can act faster. The business can grow without becoming heavier.
“The only way a 10-person SME survives and grows is by being smarter, not bigger.”
Do Not Spend So Much Time That You Become the Developer
This is one of the most important lessons for SME owners. AI is powerful, but it can also become a rabbit hole. Business owners start by learning one tool, then automation, then coding, then databases — and before they realise it, they have stopped leading the business and become the developer.
That is rarely the best use of an owner’s time. The goal is not to become technical for its own sake. The goal is to understand enough to:
- Identify the right business pain point
- Ask better questions
- Make better decisions
- Guide the workflow design
- Choose the right tools or partners
- Measure business impact
AI should serve the business. The business should not become trapped serving the AI project.
Why SME Owners Should Look for a Mentor or AI Advisor
Many SME owners know AI can help, but are not sure where to start. This is where a mentor or AI advisor earns their place — not by showing tools, but by helping the owner think clearly about priorities.
Instead of “which AI tool should I learn?”, the better question is: “Which pain point should we solve first so the business becomes easier to run, more visible, and more profitable?” A good AI advisor helps SMEs:
- Identify the highest-value pain point
- Avoid tool overwhelm
- Design simple AI-assisted workflows
- Decide what to automate and what to keep human
- Connect AI implementation to business outcomes
- Prevent overbuilding
- Build capability without losing business focus
That is the difference between AI learning and AI implementation.
The Strategic Lesson: AI Is Leverage, Not Just Automation
The strongest lesson from Adrian’s story is that AI should not be viewed only as automation. Automation means doing tasks faster. Leverage means giving a small team bigger capability — and that is what SMEs actually need.
It is not just about faster content, faster reports, or faster replies. It is about better visibility, better control, better decisions, and better margins. AI becomes strategic when it helps the owner answer business-critical questions:
- Where are we losing money?
- Which customers need attention?
- Which platform is profitable?
- Which process depends too much on one person?
- Which work should be automated?
- Which decisions still need human judgement?
That is when AI moves from tool usage to business transformation.
Key Takeaway for SME Owners
Do not start your AI journey by asking, “What tool should I use?” Start by asking, “Where is my business losing time, money, margin, visibility, or control?” Once the pain point is clear, AI becomes easier to apply. You do not need to become the developer — you need to stay focused on the business outcome and work with the right mentor or advisor to implement faster and smarter.
FAQ: AI for SME Operations
How can SMEs start using AI in operations?
Start by identifying one painful, repetitive, or costly workflow. Common starting points include customer service, finance reconciliation, reporting, HR admin, documentation, and follow-up processes.
Do SME owners need to become AI developers?
No. SME owners need to understand the business problem, define the desired outcome, and work with the right advisor or implementation partner.
Why is pain point clarity important in AI adoption?
Pain point clarity prevents the business from wasting time on random tools. It focuses AI implementation on areas that improve time, cost, visibility, accuracy, margin, or growth.
What is the biggest benefit of AI for SMEs?
Leverage. AI allows small teams to operate with better visibility, faster workflows, and stronger business capability without immediately increasing headcount.
What should SMEs avoid when implementing AI?
Avoid chasing too many tools, overbuilding systems, automating unclear processes, or spending so much time learning the technical side that the owner loses focus on business growth.
Should a lean SME hire more people or implement AI first?
Map where the business is losing time, money, margin, or visibility before hiring. Often the next hire is solving a symptom of a manual workflow that AI and automation can fix first.
Know Your Pain Point. Then Apply AI With Clarity.
Adrian’s story is a practical example of what SME AI transformation looks like — not hype, not headcount replacement, not becoming the developer. It is a smarter operating model where a lean team does more, sees more, and decides faster.
Start With the Readiness Assessment Join DigitalAI Business Club