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AI Research

Breaking the Legacy Trap

How AI changes the economics of modernising Scotland’s public services

Scotland spends heavily on keeping ageing technology running. New evidence suggests AI can fundamentally change the economics of replacing it.

Our latest research examines how AI-first analysis and software engineering can reduce the effort required to modernise legacy systems, shorten payback periods and help shift public-sector technology investment from maintaining the past to building services for the future.

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Executive summary

Deferring legacy system replacement used to be the rational choice. Modernisation was simply too expensive, risky, and slow to deliver ROI, making maintenance the defensible default.

AI is changing that calculation.

Storm ID’s delivery data shows that AI-assisted analysis and engineering drastically cut the effort needed to untangle legacy code and build replacements. Upgrades once deemed cost prohibitive are now viable.

The economics of legacy technology are changing

Three figures frame this opportunity

less effort to rebuild a legacy system with AI-first delivery, measured by Storm ID across task types with a full range of 15–60% depending on the system

28.6%

maintenance saving derived from a 2026 UK Government report that stated that legacy systems cost 40% more to maintain. (UK Parliament, 2026).

staff capacity released taken from Storm ID’s earlier research, (Automate tasks, not jobs, February 2026), which modelled the opportunity for improving automation and reducing the administrative burden through new digital services.

What AI changes

Bar chart: the saving is largest where the work is reading and writing code, smallest where people must decide. Effort saved against conventional delivery on one UK public sector programme delivered AI-first: AI-assisted Alpha build 71%, front-end prototyping 65%, requirements elicitation and definition 44%, technical architecture and design documentation 32%, project management and stakeholder engagement 7%, testing 0%. Across Storm ID’s AI-first legacy work, savings range from 15% to 60% depending on the system. Source: Storm ID delivery data.

Storm ID’s wider AI-first legacy modernisation experience suggests that savings vary considerably between systems, with an observed range of approximately 15% to 60% depending on factors such as source-code availability, architecture, integrations, data quality, technology and governance requirements.

What could this mean for Public Services in Scotland?

The research models an illustrative four-year scenario in which AI-first modernisation is applied to a growing proportion of Scotland’s legacy estate: from 10% in Year 1 to 40% by Year 4.

Three bar charts: three kinds of value, each building year on year, and never added together. Illustrative scenario with 10% of the legacy estate modernised in Year 1, rising to 40% by Year 4. Running costs avoided, in £m a year: 27.4, 56.4, 87.2 and 119.7, £291m cumulative. Engineering effort released, in £m a year: 15.9, 32.8, 50.7 and 69.7, £169m cumulative. Staff hours released, in millions a year: 3.6, 7.2, 10.8 and 14.4, building towards 36 million. Sources: Storm ID model (Appendix A); Storm ID (2026).

A route out of the legacy trap

The paper proposes that Scotland starts with a focused first wave of legacy modernisation, measures what happens and uses that evidence to determine how far and how quickly to scale.

  1. 1
    Create a Scottish public sector legacy technology inventory
    Build a shared view of legacy systems, their operating costs, risks, dependencies and replacement plans.
  2. 2
    Prioritise by value and feasibility
    Identify the strongest candidates for modernisation based on whole-life cost, service outcomes, operational risk and the wider opportunities for public-service reform.
  3. 3
    Create a common AI-first delivery and assurance framework
    Establish consistent standards covering approved tools, information protection, human accountability, security, architecture, testing, accessibility and traceability.
  4. 4
    Measure outcomes consistently from the first wave
    Track delivery time, effort and quality alongside operating costs, systems retired and outcomes for citizens and staff.
  5. 5
    Reinvest demonstrated benefits
    Where modernisation produces verified cashable savings, use an agreed proportion to support subsequent waves of change.

Read the full research

Breaking the Legacy Trap: How AI changes the economics of modernising Scotland’s public services

Explore the evidence, financial modelling, methodology and recommendations for creating a more systematic approach to legacy modernisation across Scotland’s public sector.

Download the full report (PDF 2MB)