Wigan Council: AI transforms adult social care

How one council used AI to cut drafting time in half, save 107 days on meeting minutes, and deliver £72,000 in efficiencies — while achieving the highest CQC score in England.

The challenge

Rising demand, shrinking budgets, and a workforce buried in paperwork.

Wigan Council’s adult social care team faced the same pressure as every council in England. Social workers were drafting needs assessments, case notes, and meeting minutes by hand — a single needs assessment could take two to three hours. Meeting minutes consumed days of officer time every month.

The administrative burden wasn’t just slowing teams down — it was affecting staff wellbeing, driving up sickness absence, overtime claims, and recruitment costs. The council needed to reduce that burden without compromising the quality of care, at scale, across 300+ social workers.

The approach

Six months embedded with frontline teams

This wasn’t a technology project handed to social workers. It was a co-design process that started with the people who do the work.

Agilisys spent six months embedded with Wigan’s ASC team, logging over 100 hours shadowing social care workers to understand how they engage with residents and where administrative tasks consume the most time.

A champion group of 20 social workers tested and refined every tool based on frontline feedback. Nothing went into production until practitioners were confident it worked for them.

6 months
embedded with frontline teams
100+
hours shadowing real casework
20
champion social workers testing tools
What was built

Four AI tools, all integrated into Microsoft 365

Practitioners don’t switch systems. AI fits into the tools they already use.

Live

Needs Assessment Agent

Social workers click record on a mobile app during a conversation with a resident. The tool transcribes the conversation and produces a first draft in 15 minutes — down from two to three hours.

Needs Assessment Agent →
Live

Minutes Agent

Produces structured meeting minutes from recordings, halving manual documentation time and improving compliance with statutory deadlines.

Minutes Agent →
In development

Case Auditing AI

Helps managers review historical assessments and case notes, identifying where social workers are excelling and where additional support is needed.

In development

ASC Chatbot (Nava)

Handles high volumes of queries at the ASC front door, helping residents find information and enabling self-service.

The results

CQC Outstanding — 95 out of 100

The highest CQC adult social care score in England. CQC inspectors explicitly cited the AI tools in their assessment.

These aren’t theoretical savings. They’re measured, realised efficiencies from live service delivery — freeing practitioners to spend more time with the residents who need them.

The £72,000 in efficiencies breaks down to £59,000 saved by PA teams over 12 months and £13,000 saved by ASC business support staff over three months — from meeting minutes automation alone. The needs assessment savings are on top of that.

Staff wellbeing improved too: the council saw reductions in sickness absence, overtime claims, and recruitment needs as administrative pressure eased.

This wasn’t AI replacing human judgement. It was AI removing the administrative friction that stopped skilled practitioners from doing their best work.

95/100
CQC score — highest in England
50%
reduction in drafting time
107 days
of work saved on meeting minutes
£72k
in realised efficiencies
15 min
to produce a first-draft assessment
300+
social workers using AI daily

“I cannot believe how much time it saved me, allowing me to have much more meaningful conversations with the service user.”

— Adult Social Care Practitioner, Wigan

“Our partnership with Agilisys and our use of AI and specialist tech has played an important role in supporting our teams — reducing administrative burden, improving consistency, and allowing practitioners to get the best outcomes for our residents.”

— Cllr Keith Cunliffe, Deputy Leader, Wigan Council

CQC inspectors explicitly cited the AI tools as part of what made Wigan’s adult social care service outstanding. This is regulatory endorsement of AI in statutory care — not just an efficiency story.

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Beyond social care

The same tools, across more council services

Housing

The platform analysed 4,500 tenant survey responses in three months, supporting compliance with the Regulator for Social Housing’s requirements and providing data for strategic decision-making.

HR & Recruitment

Job application evaluations compare applications against essential criteria, ensuring fairness, reducing unconscious bias, and improving hiring efficiency.

Governance

A multi-disciplinary GenAI Working Group categorises every use case by risk level. As Lead Council for the Co-operative Council Innovation Network, Wigan is co-developing a value-led AI Guidance Framework for the sector.

Why it worked

Four things made the difference

Co-design with practitioners

A champion group of 20 social workers shaped every tool. Not designed for them — designed with them, over six months of embedded collaboration.

Deep understanding of the work

100+ hours of shadowing real casework meant the tools reflect how social care actually works, not how a technologist imagines it works.

Embedded in existing workflows

No new logins, no new systems. AI works inside Microsoft 365, where staff already spend their day.

Ongoing iteration

The partnership didn’t end at deployment. Regular workshops continue to explore new uses for AI, with tools refined based on practitioner feedback.

This is the Agilisys model: embed, co-design, prove, then scale. It’s why 300+ social workers use these tools daily, and why the council continues to expand AI into more service areas.

Try it

See how this could work in your council

A free AI Prototyping Day gives your team a working prototype built on your real processes — in a single day.

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Explore

See all our adult social care AI

Needs assessments, meeting minutes, case auditing, and more. See every tool we’ve built for ASC teams.

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