Social work has as paperwork problem. Solving it could make more space for human connection

In a West London flat, an outreach social worker sits across from a senior resident, gently guiding the conversation to uncover key details about their daily routine. The resident, who has dementia, recently experienced a significant disruption: their spouse and primary caregiver was hospitalized. Now, vital support for medication, meals, and safety checks is absent.

The social worker listens intently, knowing they’ll later need to meticulously catalog what they’re observing. They’re trained to listen for clues about unspoken needs—a new symptom, a next-of-kin contact—all of which can help guide the individual’s care.

While the immediate priority is managing the crisis at hand, the social worker faces the subsequent, time-consuming task of completing case paperwork—a daunting requirement that can involve several or possibly dozens of forms. Ultimately, their role involves building a support network for the resident, connecting them with doctors, care facilities, local agencies, and more. Effective resource allocation hinges on comprehensive records, a process traditionally burdened by time-intensive documentation. This is where AI is proving to be a powerful ally.

Until recently, the social worker would have been juggling note-taking, active listening, and natural conversation, potentially missing important details. But with the help of new AI tools, they can focus on staying present, knowing they’ll have a full transcript and summary of the conversation when they’ll later need to document details of the visit.

Freed from the burden of nonstop documentation, they can observe more, miss less, and make better, more compassionate care decisions.

Documentation’s essential role in social work

Jason Codrington, manager of the adult social care intake team at Ealing Council—the local authority for one of London’s largest boroughs—has witnessed many cases like the earlier scenario. He emphasizes that in this line of work, capturing as many details as possible shapes care plans, funding, and interventions. "We need to respond quickly, and we need to be able to evidence our decisions," he says. "The pace is high, and when you're dealing with complex situations, documentation provides accountability." 

There’s a delicate balance social workers must strike between decisive action and empathetic care. Social workers have to be part first responder, part therapist, and part administrative assistant. “It’s right there in the name: social worker,” he says. “There’s something supportive and therapeutic that happens when you have someone alongside you in these moments of challenge. That’s what social workers are driven to do: be there.”

Codrington points out that social work is rooted in presence and empathy, but genuine engagement is complicated by the demands of documentation. Across the field, a British Association of Social Workers (BASW) report found that care workers spend 65% of their week on paperwork. Another study found social workers spend just 20% of their time on face-to-face interactions. In some specialized fields like child protective services, a single case can require 400 forms totaling 2,500 pages, with individual workers managing 40 to 80 cases monthly.

But in the past year, AI has begun to ease this tension. It’s part of a wider transformation in knowledge work that has entered other industries from documentary filmmaking to archaeology and beyond. Now, developers of productivity tools are focusing on the social services sector, leveraging AI to assist care workers by automating their most tedious administrative tasks and giving them more resourcing for the human parts of their jobs.

AI’s potential in easing casework loads

At Ealing Council, Codrington leads a team of ten social workers who serve one of London's most diverse populations. They are often the initial point of contact for adults who need support with daily tasks, and their clients range from senior residents experiencing cognitive decline to younger adults who have conditions like multiple sclerosis or cerebral palsy. Each day presents new challenges requiring immediate attention, sensitive assessment, and importantly, thorough documentation.

"We’re often dealing with clients at their most vulnerable," Codrington says. "When you’re sitting across from someone, you’re not just asking questions. You’re listening for what they might not say directly. You’re listening for the things that can’t always be captured in a quick back-and-forth." Sometimes, this means recognizing that politeness can mask a critical need for urgent intervention.

One of the most widely adopted tools in the social work field is Magic Notes, an AI-powered transcription and summarization system launched in early 2024. With ‌client consent, Magic Notes allows social workers to record their case conversations and use the software to transcribe and structure the information into a professional report that meets their council’s formatting requirements. (Codrington emphasizes the importance of adhering to specific council templates to prevent the loss of critical information.)

Instead of spending hours documenting a meeting from memory, a social worker instead receives a near-instant summary that they can review, edit, and finalize in a fraction of the time required by traditional case paperwork. "Any tool that helps you focus in that space and not be overwhelmed or burned out by it is a massive help," Codrington says. 

The impact has been swift, and in less than a year, Magic Notes has been rolled out across a third of England’s social care teams. According to the Ealing Council, during their pilot phase in 2024, the time social workers spent on administrative workload was reduced by 48%, freeing up time that had previously been spent on documentation.

Magic Notes has also proven useful for some social workers who may face additional casework challenges. Those who don’t speak English as a first language, for instance, can conduct assessments in their native language and then generate English summaries. This can eliminate hours of checking spelling and formatting. The tool’s adaptability allows users to tailor it to their needs—whether for structure, speed, or clarity.

Magic Notes is part of a broader trend of tech platforms attempting to tackle social work’s paperwork problem. Social Work Magic provides AI-powered templates for care workers, handling safety plans and tracking client interventions. Netsmart's Bells AI aims to streamline healthcare documentation. Clinical Notes AI transforms real-time conversations into structured treatment plans. Should these tools gain widespread adoption, frontline workers in social services and healthcare could have the capacity to dedicate more time to client interaction.

Creating more space for human work

While AI can streamline transcriptions, summaries, and other administrative tasks, comprehensive casework extends beyond initial visit notes. A single home visit might lead to half a dozen follow-ups: an assessment report, a care plan, a risk evaluation, letters to doctors, emails to housing authorities, and internal memos flagging concerns for colleagues. Every interaction necessitates documentation—not only for accountability, but to coordinate care across teams. 

“Records are everything,” Codrington says. “Without proper documentation, people slip through the cracks.” 

A key advantage of AI in social work is its ability to synthesize disparate notes into cohesive, shared information. In collaborative care settings where multiple professionals often collaborate on a single case, each person may have their own documentation style. AI tools can help pull everything together to flag critical details like late medication refills. The data can also reveal broader trends, such as identifying neighborhoods with higher hospital admission rates or pinpointing areas where resources are strained, helping councils to plan more effectively.

Social workers are also discovering unique ways of using AI to help manage their individual workloads. Some dictate notes on their way back to the office, knowing they’ll have a formatted report waiting when they sit down at their desk. Others review reports at the end of the day, using AI as a second set of eyes before finalizing casework. While human oversight remains essential for review, refinement, and approval, AI tools can significantly reduce the burden of starting from scratch.

“Social workers are figuring out their own ways to make it work,” says Seb Barker, co-founder and COO of Beam, the social impact startup behind Magic Notes. “The goal has always been to lighten the load and get them to focus on the stuff that matters.” 

So far, easing some of the cumbersome documentation and heaps of paperwork is a promising application of AI technologies in a field that’s already prone to worker burnout. Crucially, this shift has allowed care workers to spend less time at a desk and more time in the field. “Thus far we haven’t been taking on more cases,” Codrington says. “We’re doing more for the people we already serve.”

Codrington sees promise in AI tools, but the real test will be in longer-term results. Meaningful impact will likely be measured by improved client outcomes, such as faster interventions, more comprehensive care plans, and increased face-to-face interaction. And of course, a key marker of success will be improvements to the wellbeing of social workers themselves.

Picture that West London living room scene again: a social worker listens attentively, unburdened by exhaustive note-taking and focused entirely on the individual before them. Free from distractions, the conversation flows uninterrupted—save for a shared tea break.