Sutherland's regeneration push needs an AI rework rule

Sutherland is approaching an unusually important development window. Highland Council is due on August 20 to update its Economy and Infrastructure Committee on implementation of the North, West and East Sutherland Pride in Place programme, which brings £19.6 million over ten years for locally shaped regeneration.

By Gleb Tsipursky

That scale of investment naturally raises questions about projects, infrastructure and community priorities. It should also raise a less visible question for local businesses: how will they decide whether new technology is actually making work better?

Artificial intelligence is increasingly accessible to small firms. A shop can use it to draft promotions. A tourism business can use it to shape customer responses. A contractor can use it to summarize documents or prepare first drafts. Those uses can be genuinely helpful, especially in rural areas where time and staffing are scarce.

But the fastest first draft is not the same thing as higher productivity.

An AI-generated answer may save ten minutes and then create twelve minutes of checking, correction, context restoration or customer follow-up. A polished-looking output can still contain the wrong price, an outdated opening time, a missing exception or a confident statement that no employee would have made without checking.

That is why Sutherland businesses should adopt a simple rework rule before scaling AI across routine work.

For 30 days, pick one recurring task and keep a basic ledger. Record the time saved on the first pass. Then record the time spent checking facts, correcting language, restoring local context, handling exceptions and repairing downstream mistakes. The useful number is the net result.

This is not an argument for avoiding AI. Highlands and Islands Enterprise is already offering digital and technology support that includes AI adoption, and its AI Scotland work is designed to help small and medium-sized businesses move beyond experimentation while building leadership and long-term capability.

The point is to make adoption measurable.

A second safeguard is just as important: name the person who owns the final decision. AI can help prepare an answer, but a human should approve consequential claims involving prices, bookings, grants, safety, contracts, sensitive data or promises to the public. Accountability becomes weaker when everyone assumes the tool or someone else checked the work.

This approach fits rural business particularly well. AI can help a small team do more without pretending that local knowledge, judgment and trust are optional. It can extend capacity while keeping responsibility close to the people who understand the customer, the community and the consequences of a mistake.

Pride in Place is about giving local people more influence over regeneration. The same principle should guide business technology: use tools that expand local capacity without surrendering local judgment.

Sutherland does not need to choose between innovation and caution. It needs a way to tell useful innovation from expensive rework. A one-month ledger and a named human reviewer are a practical place to start.

Gleb Tsipursky, PhD, a behavioural scientist, CEO of Disaster Avoidance Experts, and author of The Psychology of AI Adoption at Work: From Resistance to Results (Georgetown University Press, 2026) available here