Scotland’s public sector is facing a monumental moment, defined by the struggle to maintain quality of services amid constrained resources and shifting demographics.

Amid these struggles is a growing debate on the implementation of AI and how this emerging technology can be used to enhance efficiency and producvitiy across industries.

But public services in Scotland have special considerations, ranging from ethical implementation, the need to retain and create jobs rather than replace them, and looming digital exclusion and outdated tech uptake.

This is why Storm ID created the report Automate taks, not jobs: The AI Opportunity for Scotland’s public services, which details how effective AI implementation can save Scotland’s public services – from the NHS to education – its most precious resource: time.

Storm ID’s research assessed 50 high-volume public sector services acrorss Scotland with the strongest potential to save staff time through credible AI use cases, including NHS Scotland, Education, local authorities, Police Scotland, and other public bodies.

Acorss these industires, Storm ID estimated baseline savings of about 178 million staff hours per year, with the largest amount of savings going to the NHS (80m hours).

But how does Storm ID think Scotland’s public services can achieve these time savings?

Through purposeful automation, rather than job replacement. Enhancing the ability to complete common tasks quickly, rather than trying to auotmate entire jobs, would save time and allow workers to focus on more important, specialised tasks.

This would require workforce engagement from the very start of designing AI systems to public services, as well as ongoing monitoring to ensure continuous imporvement.

Within these systems though, Storm ID discovered that based on the senstitivity and risk of the data invovled, around half of the top 50 services assessed would require a private deployment AI model to ensure security.

To mitigate risk to jobs and security, Storm ID is calling on Scotland to prioritise high-volume, lower-risk services first, which can help demonstrate value quickly and demonstrate institutional capability.

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Storm ID suggests the creation of shared, reusable AI components for common service patterns used across different public services.

This must be accompanied by robust governace and assurances, with clear accountability, cyber controls, auditing, and human oversight.

A mixed infrastructure strategy is also advised, combining UK public cloud with private AI infrastructure.

Workforce enablement should be a core deliverable when assessing the affectiveness of AI adoption, rather than the ability to reduce headcount.