Reducing Time Write-Offs with Better AI-Driven Time Capture

Most firms have the same story about time recording:

people do it late, if at all;
partners write off chunks of time because they do not feel justifiable; and
everyone suspects that real effort is disappearing between the cracks.

AI‑assisted time capture will not magically fix all of this. But used properly, it can reduce write‑offs and under‑recording by making it easier to:

spot work that never made it into the system;
make time entries more accurate and descriptive; and
give partners better information when they decide what, if anything, to write off.

This article looks at how better AI‑driven time capture can help reduce write‑offs, with a focus on realistic workflows in UK firms.

1. Understand why time gets written off

Before thinking about tools, be honest about why write‑offs happen. Common reasons include:

time was never recorded in the first place (especially for short or “informal” tasks);
entries are too vague or poorly described to be defensible to clients;
work reflects inefficiency that partners do not feel comfortable passing on;
cross‑subsidy: partners choose to eat time on one matter to preserve a relationship.

AI can help mostly with the first two:

making it easier to capture everything that happened; and
improving the clarity and quality of narratives.

It cannot and should not override a partner’s judgment about value or relationship management.

2. Use AI to surface missing or thin time

AI‑driven time capture typically works by:

observing events in your systems – emails sent, documents edited, calls and meetings, tasks completed;
suggesting candidate time entries based on these events;
allowing lawyers to accept, edit or discard suggestions.

To reduce write‑offs, focus on patterns like:

completely missing time – work where there are clear signals of activity but no recorded time;
thin narratives – entries like “work on matter” for 1.2 hours where more detail would support billing.

Dashboards for partners and team leads might show:

matters with high activity but low recorded time;
individuals with large proportions of suggested time entries discarded;
days with intense email/document work but very few entries.

The goal is not surveillance; it is giving teams a chance to spot and correct under‑recording while events are still fresh.

3. Improve narratives, not just numbers

Clients and in‑house counsel often object to bills because descriptions do not explain value. AI can help by:

turning raw activity logs into clearer narratives (“Review and respond to opponent’s revised offer, considering cost and risk implications”);
standardising language for common tasks across the firm;
prompting lawyers to add client‑friendly context (“prepare for conference with counsel on liability issues”).

A good workflow is:

AI proposes a time entry (duration + description) based on recent work.
The lawyer reviews and adjusts wording, adding nuance and removing inaccuracies.
The final entry is saved and later reviewed in billing, supported by a clear narrative.

Over time, this can reduce the need for write‑downs driven purely by embarrassment at poor descriptions.

4. Make it easy to correct and allocate time

AI suggestions are approximations. People need quick, low‑friction ways to:

merge multiple suggestions into one coherent entry;
re‑allocate time between matters where activity touched more than one file;
correct durations that are clearly off (for example, emails sent hours apart but treated as continuous work).

Design matters here:

mobile‑friendly interfaces for people working away from the desk;
daily or weekly “review sessions” where lawyers can confirm or adjust suggestions in one sitting;
simple ways to flag suggestions that are consistently unhelpful (“stop showing me this pattern”).

The less painful it is to adjust entries, the more likely people are to keep time accurate — and the less nervous partners will be about billing it.

5. Give partners better visibility at billing time

When partners review bills, they often see only:

total hours;
high‑level narratives; and
maybe a handful of detailed entries.

With AI‑assisted capture and better descriptions, they can also see:

clearer breakdowns of what was done when;
how much time was spent on avoidable re‑work vs value‑adding analysis;
where clients received extra, unbilled support.

This helps partners:

make more informed write‑off decisions;
explain bills more confidently if challenged;
adjust staffing or process for future matters.

Over time, patterns of frequent write‑offs in particular workflows can guide process or pricing changes.

6. Be transparent internally about goals and limits

AI time capture can feel threatening if poorly explained. To keep trust, be clear that:

the aim is to help people record genuine work, not to catch them out;
lawyers remain in control of what gets recorded and billed;
partners will not treat AI suggestions as hard evidence that someone “must have” billed more.

Training should emphasise:

how to use suggestions as a memory aid, not an obligation;
how to correct and decline entries;
when to talk to supervisors if suggestions do not reflect reality.

Culture matters as much as technology in reducing write‑offs for the right reasons.

7. Use metrics to learn, not to punish

Finally, treat metrics about AI time capture as learning tools:

how much additional time is captured compared with manual‑only recording;
whether narrative quality improves (fewer billing queries, fewer internal write‑downs);
where certain patterns (for example, constant unrecorded short tasks) suggest the need for staffing or process changes.

Share high‑level findings with teams, not to shame individuals but to:

celebrate improvements;
agree sensible norms (for example, “we always record short but valuable client calls”);
refine prompts and workflows.

Where OrdoLux fits

OrdoLux is being designed with AI‑assisted time capture as a core capability, not an afterthought:

it can suggest time entries based on emails, documents, tasks and notes linked to each matter;
lawyers can accept, edit or discard suggestions quickly, from desktop or mobile;
richer narratives and matter context make billing reviews easier;
matter‑level logs show how time entries were created and adjusted, supporting internal and external scrutiny.

The aim is not to drive up hours for the sake of it. It is to capture the real work that already happens, so partners can make informed decisions about pricing, write‑offs and value — with AI quietly doing the tedious tracking in the background.

This article is general information for practitioners — not legal advice, not financial advice and not specific billing guidance for any client or matter.

Looking for legal case management software?

OrdoLux is legal case management software for UK solicitors, designed to make matter management, documents, time recording and AI assistance feel like one joined‑up system. Learn more on the OrdoLux website.