AI prepared every decision. It did not raise the ceiling on scale
Every week, the meetings I sit in across the businesses I work with are recorded, and an AI system turns each one into four lists: decisions, risks, blockers and next priorities. It takes minutes. I rely on it. After months of reading those lists back to back, one thing is hard to miss. The system […] The post AI prepared every decision. It did not raise the ceiling on scale appeared first on e27…
AI systems have become proficient at streamlining decision-making processes for businesses. They generate lists of decisions, risks, blockers, and next priorities, helping to speed up the preparation of decisions. However, despite these advancements, AI cannot alleviate the burden of making high-level, owner-centric decisions.
In one instance, a software team decided to adopt an AI-first approach, resulting in more cost-effective builds. Nevertheless, crucial decisions regarding the validity of the project, its suitability, and responsibility remained firmly in the hands of individuals. Similarly, a manufacturer integrated production planning directly into the order screen, but it could not account for aspects such as absenteeism, varying festival schedules, and worker absenteeism. This underscores the importance of human judgment in making critical decisions.
A consumer brand discovered a cost counting error in their costing model but chose to accept it for now, highlighting the fact that AI cannot determine whether a known flaw is tolerable or not. In another case, an Indian equipment maker identified operational issues as the cause of fluctuating performance but needed a person to implement changes and take ownership.
AI can reduce marginal costs associated with expansion, but it does not diminish the attention required to ensure effective scale. The concept of scale, in this context, refers to the ability to add markets or customers without a proportional increase in cost, complexity, capital, or founder attention. The key to expanding scale lies in identifying and managing exceptions that require specific individuals with sufficient context to make decisions and be accountable for them.
The report indicates that AI adoption among Singapore's SMEs reached 23.4% in 2025, up from 14.5% the previous year. While answers are becoming cheaper, the responsibility of making accountable decisions remains a limiting factor. To scale successfully, businesses must build for fewer unshareable decisions, each with clear owners, and focus on developing individuals who can carry market judgments in their absence.
Written by urgent.news from e27's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
