Emergency services must start digital modernisation with a clear set of operational priorities — not with a shopping list of technologies — if they are to realise benefits from cloud, data and artificial intelligence, consultants from ANS have told The Emergency Tech Show 2026.
Start with outcomes, not tools
ANS warns frontline organisations that rushing to adopt cloud platforms or AI tools without first defining the outcomes they want risks wasted effort, higher costs and degraded resilience. The consultancy says leaders should identify the operational improvements they need — for example, greater resilience, reducing pressure on frontline teams, faster access to critical information or improved responses to changing demand — and use those goals to shape a practicable technology plan.
“The biggest mistake organisations can make is starting with technology rather than the outcomes they want to achieve.”
To build a realistic programme, ANS recommends a disciplined assessment of the current estate: legacy infrastructure, duplicated systems, data silos, security exposures, existing contractual commitments and the skills available in-house. Rather than attempting wholesale replacement, the consultancy argues that workloads should be triaged by criticality, business value and readiness for migration.
How Microsoft Cloud fits in
ANS describes Microsoft Cloud — including Azure and Microsoft Fabric — as a means to provide a centralised, governed data environment. By consolidating infrastructure, applications, data and security controls, the approach aims to make information more discoverable and reliable for operational teams while enabling analytics and automation that underpin modern AI capabilities.
The adviser says a trusted central data platform helps organisations put guardrails around information access and build the trustworthy datasets AI tools require, rather than scattering data across multiple unconnected systems.
Practical steps and tools
ANS uses a structured engagement it calls Navigator to help emergency services translate ambition into a phased roadmap. Navigator maps the current environment, outlines a target architecture and operating model, compares costs and identifies the transition steps needed to achieve measurable outcomes.
- Assess the existing estate and data landscape.
- Prioritise workloads by operational value and readiness for change.
- Define a target architecture that centralises trusted data and security controls.
- Plan phased delivery with clear metrics for cost, risk and operational benefit.
That process is designed to give senior leaders the information they need to make decisions about investment, timelines and the skills they must develop or buy.
| Operational priority | Typical technology action |
|---|---|
| Improve resilience | Consolidate infrastructure on resilient cloud platforms |
| Reduce frontline pressure | Provide faster access to actionable data and automation |
| Better information access | Create a governed central data platform |
| Respond to demand changes | Prioritise workloads ready for flexible cloud operations |
Barriers remain
ANS highlights persistent obstacles: ageing systems that are costly to change, organisational silos that block data sharing, limited in-house skills and the need for clear AI governance. The consultancy argues that addressing these issues up front reduces the chances of simply replicating past problems in the cloud.
Crucially, the firm stresses that cloud and AI are enablers for outcomes rather than ends in themselves. That distinction matters when budgets are constrained and public expectations of service availability and privacy are high.
For emergency services planning digital change, the message is clear: develop a roadmap that ties technology choices to operational benefits, use structured assessments to understand costs and risks, and adopt a phased approach that safeguards resilience while preparing data and governance for AI.
