Fewer Handovers: Where AI Helps Small Businesses

A customer sends an enquiry. Someone copies the details into a spreadsheet. Another person prepares the quote. Someone else follows up.

None of these steps is particularly complicated. But every handover takes time, and sometimes information gets lost along the way.

That's the problem behind an interesting argument Erik Ingvoldstad makes in his recent article, “From multidisciplinary teams to augmented humans”, published on the Acoustic blog on 5 October 2026.

Erik is the founder of Acoustic, an independent consultancy that collaborates with Runoan.

His article explores how AI is changing the way people work across different disciplines, and why reducing unnecessary handovers may matter more than simply adding more tools.

The Problem With Too Many Handovers

For a long time, solving a complicated business problem often meant bringing together several specialists.

A strategist understands the customer. A designer develops the experience. A developer builds the solution. Someone else manages the data or operations.

Each person brings valuable expertise.

But every time work moves from one person to another, some context can be lost.

The person who understands the customer's problem may not be the person building the solution.

Erik argues that AI is changing what's possible.

With the right tools, one person can now take an idea further before handing it to someone else. They might build a working prototype, analyse information or prepare a first draft without needing a separate specialist for every step.

That doesn't mean specialists are no longer needed.

The opportunity isn't to replace every specialist with one person using AI. It's to reduce unnecessary handovers while bringing in the right expertise when it matters.

Human judgment remains essential.

What This Looks Like in a Small Business

You may recognise the pattern.

A customer sends an enquiry through your website.

Someone copies the information into a spreadsheet.

Another person prepares a quotation.

Someone else follows up with the customer.

If the information changes, the process starts moving between people and systems again.

The problem isn't necessarily that anyone is doing their job badly.

It's that the process depends on information being passed around repeatedly.

AI and automation may help reduce some of those steps.

For example, a well-designed enquiry form could collect the right information from the beginning.

A simple application could calculate an indicative quotation using approved pricing rules.

An AI assistant could summarise a complicated enquiry and identify missing details.

And where the work genuinely requires several steps and different tools, an AI agent might help prepare the next action for human approval.

Not every improvement needs AI.

Sometimes, fixing the process is enough.

What the Research Tells Us

AI adoption is growing, but using AI and integrating it effectively into everyday operations are different things.

A 2024 OECD survey of more than 5,000 SMEs across seven countries, excluding Singapore, found that 31% were using generative AI. Among businesses reporting a skills gap, 39% said generative AI helped compensate for it.

The findings suggest that AI may help smaller businesses work with capabilities they don't always have in-house. But the survey doesn't establish that the same benefits will apply to every business.

In Singapore, the DBS Business Pulse Check, conducted between December 2025 and January 2026 with 730 companies, found that approximately 67% were applying some form of AI, while only 12% reported fully integrating it across their operations.

That gap is worth paying attention to.

Trying an AI tool is relatively easy. Making it part of a reliable business process is harder.

These figures are based on businesses reporting their own experiences. They provide useful context, not a prediction of what AI will achieve for your company.

What AI Still Can't Do on Its Own

AI can help people work across tasks that previously required more time, coordination or specialist support.

But there are limits.

It doesn't automatically understand your customers.

An AI system can analyse information you provide, but understanding what matters to a customer still requires business knowledge, context and judgment.

It isn't always right.

AI can produce convincing answers that contain errors. Important decisions, customer commitments and financial information need appropriate checks.

It can't fix unreliable business information by itself.

If your pricing is outdated, your records are inconsistent or your processes are unclear, adding AI may create more confusion rather than less.

It doesn't eliminate the need for expertise.

A working prototype isn't necessarily a secure, reliable production system. Specialists still matter for complex decisions, implementation, testing and accountability.

AI can help people do more, but it doesn't remove the need to know what good work looks like.

Independent Specialists, Fewer Unnecessary Handovers

This is where Erik's argument connects with how we approach work at Runoan.

We believe independent specialists can bring different experiences and perspectives to a project without every task needing to pass through multiple layers.

Sometimes, one person with the right tools can take an idea from discovery to a working prototype.

Sometimes, a project needs a designer, developer, strategist or another specialist.

And sometimes, the best result comes from bringing those people together.

The goal isn't to make everyone do everything.

It's to keep the people who understand the problem close to the people solving it.

Independent thinking and collaboration aren't opposites. The right combination can make work simpler and more effective.

Three Questions Before Adding Another Person or Tool

Before hiring someone, subscribing to another platform or introducing AI, consider three questions.

1. Where does information get retyped, delayed or lost?

Look for repeated data entry, unnecessary approvals and handovers between disconnected systems.

2. Who understands the customer, and are they involved in building the solution?

The closer that knowledge stays to the work, the less likely important context is to disappear.

3. Who checks the result before the customer sees it?

Whether work is completed by a person, automation or AI, someone should be accountable for important outcomes.

These questions can reveal opportunities for improvement before you invest in new technology.

Start With the Problem, Not the Technology ##

AI creates new possibilities for small businesses, but it doesn't mean every business needs an AI agent or a complicated digital transformation project.

Sometimes, a clearer process is enough.

Sometimes, a simple tool can remove hours of repetitive work.

And sometimes, AI helps one person take an idea further before bringing in the right specialist.

At Runoan, we bring together independent professionals to help SMEs BUILD, IMPROVE and SOLVE practical business problems.

We start by understanding what's not working, then explore the simplest useful way forward.

If you'd like to talk through where AI, automation or better digital tools could help your business, the first conversation is free.

Email hi@runoan.com or WhatsApp +65 8946 3370.