The argument that SMEs need to embrace AI to remain competitive is easy to turn into a technology slogan. Pelumi Ololade Pelumi made a more practical version of that case in a July 2026 interview with The Guardian Nigeria, describing everyday SME work such as stock monitoring, customer questions, order tracking and appointment management as areas where automation can remove operational friction. The useful question for an owner is not whether AI is fashionable, but where it can make a constrained business work better.
Pelumi's case begins with ordinary operational bottlenecks
In The Guardian Nigeria interview, Pelumi discusses observing small businesses handling routine work manually and argues for practical automation built around real problems. He also identifies resistance to changing familiar processes and disconnected automation as adoption difficulties.
That framing is useful beyond the businesses discussed in the interview. Competitive value rarely comes from owning an AI tool. It comes from removing a delay, improving access to information or making a repeatable process more dependable.
Start where limited capacity hurts customers
An SME cannot improve every process at once. Look for work where constrained capacity is visible to customers: enquiries that wait, appointments that need repeated coordination, routine updates that interrupt skilled staff or information that has to be copied between systems.
These are better starting points than an abstract ambition to become AI-first. They give the business an observable before-and-after comparison and make it easier to decide whether the new process deserves further investment.
Do not confuse availability with competitiveness
AI can produce an immediate draft or response, but speed alone is not an advantage if the answer is inaccurate or creates additional work. The competitive test is the complete outcome: did the customer get a useful next step, did staff avoid unnecessary administration, and did the business retain appropriate control?
A slower human route may still be right for unusual, sensitive or commercially important cases. Good adoption decides where speed is valuable and where judgement remains the differentiator.
Connected workflows matter more than isolated tricks
Pelumi's warning about piecemeal automation deserves attention. Automating a single step can leave staff manually bridging the gaps around it. A generated reply that never updates the customer record, or a booking bot that cannot recognise an existing commitment, may simply relocate effort.
Map the whole journey before expanding. Decide which system holds the record, how information moves, who owns exceptions and how a human receives context when the automated route ends.
Small firms should learn before they scale
Adoption does not require a company-wide transformation on day one. Trial a bounded use case with representative work. Keep permissions proportionate, establish a manual fallback and inspect errors rather than hiding them.
The point of a pilot is organisational learning as much as technical testing. Staff discover what information the system needs, managers see where rules are unclear and the business develops a better sense of which tasks benefit from AI.
Competition is also about knowledge and process quality
Two firms can buy access to similar AI models and get very different results. The business with clearer service information, cleaner records, explicit decision rules and employees who understand the workflow has a stronger foundation.
This is why AI adoption can expose existing weaknesses. If nobody knows which policy is current, an AI assistant does not resolve the ambiguity. It may distribute it faster. Improving the underlying knowledge can be as important as choosing the technology.
Keep the competitive claim in proportion
Not every SME needs the same AI capability, and refusing a particular tool is not automatically a competitive failure. Some processes are low-volume, highly personal or already efficient. Technology should earn its place.
Pelumi's interview is best read as a problem-first argument for adoption rather than a command to automate everything. SMEs should understand what AI and automation can now do, because competitors and customers will increasingly encounter these capabilities. But understanding includes knowing where not to deploy them.
Embrace AI by becoming better at choosing
The durable advantage is not early adoption for its own sake. It is the ability to identify a useful problem, test a controlled intervention, connect it to the surrounding workflow and learn from the result.
For a small business, that discipline protects scarce money and management attention while still allowing experimentation. AI can widen what a compact team is capable of doing, but competitive value appears only when the technology improves an operation that customers or employees actually experience. The practical SME response is therefore neither fear nor indiscriminate enthusiasm: it is informed, selective adoption tied to evidence.