The use of AI in social care is evolving quickly. Local authorities are increasingly adopting and evaluating tools that support recording, transcription and analysis to reduce administrative burden and give practitioners more time to focus on direct work with individuals and families.

Recent sector discussions have highlighted important concerns about how these tools are used in practice. In particular, there are legal and ethical risks when technology moves beyond supporting information capture and begins to influence professional decision-making.

Why This Matters

Social care operates in a context where decisions directly impact people’s lives. Assessments, referrals and plans can all carry legal weight and rely on the handling of highly sensitive personal information.

From a practice perspective, the key issues are very real. Clarity of consent, transparency in how records are created, accountability for decisions, and confidence in the accuracy of what is recorded all need to be explored.

There is also an ongoing discussion about how technology fits into professional judgement. Even with oversight, tools that summarise or interpret information can create uncertainty around who holds responsibility and how practitioners evidence decisions.

What Local Authorities Need to Think About

For local authorities, successfully implementing AI depends as much on how organisations use, understand and govern it in practice as on the technology itself.

At its best, AI plays a clearly defined role. It supports practitioners in their work without replacing professional judgement or decision-making.

Transparency about how technology is used is essential. People need to understand, in clear terms, how their information is being recorded and what role the tool plays. This helps maintain trust and ensures that consent is meaningful rather than procedural.

Within the system, there must be clarity about the record itself. Visibility into what a practitioner has written and what a tool has supported is needed so that professional judgement is clear and accountability is not diluted.

Implementation is Not a One-off Event

Just as importantly, implementation should not be treated as a one-off event. Ongoing oversight, with governance, legal and information management input and practitioner-led support, helps ensure the use of the tool continues to align with expected standards in day-to-day practice.

Where these conditions are in place, technology can genuinely support practitioners, improve efficiency while maintaining confidence in the quality, transparency and reliability of social care records.

Supporting Safe and Accountable Practice with Liquidlogic AI

Liquidlogic AI (FormFlow) supports structured data capture without generating or inferring assessment content. It maintains transparency, integrates with statutory workflows and handles sensitive data within secure local authority environments.

From a practitioner’s perspective, FormFlow supports the recording task rather than replacing professional judgement. It captures conversations, structures information and helps practitioners populate the relevant form. Practitioners then review, amend and finalise the record, retaining responsibility for its accuracy and completeness.

That distinction matters. The system does not make decisions about children, adults or families. It does not determine thresholds, eligibility, risk, outcomes or next steps. Instead, it creates draft content from the recorded conversation, and practitioners remain responsible for checking that the record is accurate, balanced and professionally defensible before they complete it.

Consent and Transparency Remain Part of Practice

Practitioners should explain recording clearly and ensure people understand why they are using it. If someone does not give consent, practitioners can continue to record information in the usual way.

The Practitioner Stays in Control

FormFlow may suggest draft answers or summaries, but these are not final records. The practitioner reviews, edits and confirms the content before the form is finalised.

FormFlow AI Does Not Learn from Local Authority Data

The model does not train or retrain on customer data. It uses information solely to complete specific tasks such as transcription, form population and practitioner queries, rather than to build or improve a broader model.

Information is Handled Within Controlled Environments

Users upload recordings into the case management process and link them to the relevant person, form or case note. The core Liquidlogic security model and role-based permissions control access, so users only see information they are authorised to access.

Recordings are Protected and Time-limited

The system encrypts recordings held on a device before upload and prevents them from being stored in public device areas, such as the camera roll. Once users upload the recording and finalise the form, the system removes the recording while retaining the transcript as part of the record where configured.

Outputs Can be Checked Back to the Source

Practitioners can review the transcript and, where needed, use cited excerpts to understand where a suggested answer or summary has come from. This supports transparency and helps reduce the risk of unsupported content being accepted into the record.

Local Authorities Control How it is Used

FormFlow does not simply switch on access everywhere. Authorities decide which forms, case note types, teams and users can use it. They can also exclude individual form fields where local policy or practice requires practitioners to complete them directly.

AI-generated Input is Clearly Identified

This approach maintains transparency by showing exactly how the information has been recorded. As a result, organisations can address key concerns around AI, including accuracy, confidentiality, consent, authorship and accountability, through the way the tool supports practice.

FormFlow helps capture fuller information and reduce duplication while keeping analysis, decision-making and ownership of the final record with the practitioner.

Where this Leaves AI and Social Work

The sector’s focus on AI risks and ethical issues is important and necessary. The challenge is not avoiding digital tools, but using them in a way that strengthens practice, decision-making and outcomes.

In a landscape where AI is developing rapidly, the priority remains clear: using these tools to support, not replace, professional judgement. Success will come from staying grounded in what matters most: strong relationship-based practice and confident, accountable decision-making.

FormFlow demonstrates how organisations can achieve this in practice by building transparency, safety and control into the process from the outset, ensuring AI supports good social work rather than distracting from it.

Next Steps

Find out how Liquidlogic AI enhances our social care software, supporting both children’s social care and adults’ social care software with intelligent, embedded automation. It helps teams streamline processes, improve data quality and focus more time on delivering better outcomes.

Read this article from Community Care to learn more about AI literacy and the discussions being had in the social care sector.

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