AI for Tasks and Deadlines: Extracting Action Points from Correspondence

For most litigators and private client lawyers, the real problem is not a lack of information; it is that tasks and deadlines are buried in long email chains and letters.

“Did we agree to file by Friday or next Wednesday?”
“Who is supposed to chase the expert?”
“Did counsel want a draft by close of business or just ‘this week’?”

AI will not run your cases for you. But it can reliably pull out action points and dates so you do not miss things or spend half an hour re-reading threads.

This article looks at practical ways to use AI to extract tasks and deadlines from correspondence and feed them into your case management system — with humans still firmly in charge.

1. Decide what counts as a “task” or “deadline”

Before you involve any technology, be clear about definitions. In most matters you are looking for:

Tasks – things someone in the firm needs to do (draft, review, send, file, attend).
External actions – things clients, opponents, experts or counsel need to do.
Deadlines – hard dates (court deadlines, contractual dates) and soft dates (“by the end of next week”).
Dependencies – tasks that only make sense after something else has happened.

A simple internal standard might be:

“If a reasonable supervisor would expect to see it on the file as an action point, it should appear in the task list.”

You can teach AI to help identify these items — but only if you have a clear idea of what you want in the first place.

2. Use AI to read correspondence and propose actions

Modern language models are very good at turning messy text into structured lists. A typical pattern is:

Take an email thread or letter.
Ask AI to extract:
- tasks for the firm;
- tasks for the client;
- key dates and deadlines;
- questions that still need answers.
Present the result as a table or checklist for a human to review.

A sensible prompt might be along the lines of:

“Read this correspondence and list any actions and deadlines. For each item, include: (1) who is responsible (‘firm’, ‘client’, ‘opponent’, ‘court’, ‘counsel’), (2) what needs to be done in one sentence, (3) any date or time reference, and (4) whether the date is hard or approximate.”

The aim is not to let AI decide what must be done, but to surface candidates so fee-earners and PAs are not starting from a blank page.

3. Keep humans in charge of what goes on the record

Once you have an AI-generated list, a fee-earner or supervised member of staff should:

accept items that are correct and useful;
edit the wording where necessary (“call client” → “call client to discuss revised offer and explain costs risk”);
discard items that are noise or misunderstandings.

Important principles:

AI’s output is a draft, not the official task list.
The “owner” of the matter decides which tasks actually get created and allocated.
Ambiguous or high-risk actions (for example, anything involving undertakings or court commitments) should always be considered carefully, not added automatically.

In OrdoLux, this might look like a pane next to the email: suggested tasks on the left, approved tasks turning into real entries on the right.

4. Turn dates and times into proper deadlines

Email language about timing is often vague:

“by close of play on Friday”;
“early next week”;
“within 7 days of service”.

AI can:

normalise plain-language dates into actual calendar dates, where context allows;
flag when the wording is ambiguous, so a human can decide how to interpret it;
link deadlines back to the underlying document (order, contract clause, directions order).

Good practice is to:

include the original wording in the task or deadline description (“Order requires service ‘by 4pm on Friday 14 March 2025’”);
store the relevant document or email alongside the task, so nobody has to hunt for the source;
distinguish between court / contractual deadlines and internal planning dates.

AI should help you avoid misreading dates, not take responsibility for interpreting them alone.

5. Connect extracted tasks to people and matters

A tidy list of tasks is only useful if it is linked to:

the right matter;
the right owner; and
realistic time estimates.

To keep this under control:

let AI suggest the likely matter from email headers, but always allow humans to override;
default ownership to the fee-earner who received or sent the correspondence, with options to reassign;
encourage short descriptions that make sense when read later in isolation (“Review draft report on title – focus on easements and restrictions”).

The goal is a world where:

action points surface from email and letters automatically;
fee-earners approve and refine them in seconds;
tasks then sit in the same place as everything else on the file.

6. Logging and supervision

Because tasks and deadlines are so closely tied to risk, it is useful to keep a record of:

which tasks originated from AI suggestions;
who approved them;
any significant corrections or deletions.

This is not about blaming individuals; it is about:

improving prompts where AI regularly misses or misreads certain patterns;
giving supervisors a fast way to see what has changed after big correspondence days;
being able to explain to regulators or insurers how you manage risk.

A light-touch approach — a simple “AI-assisted” flag on tasks plus occasional file reviews — is often enough.

Where OrdoLux fits

OrdoLux is being built around the idea that tasks and deadlines live inside the matter, not in fee-earners’ heads or private to-do lists.

AI features are designed to:

read emails and letters already linked to the matter;
propose structured tasks and deadlines in a review pane;
let fee-earners and PAs approve, edit or reject those suggestions with one click;
keep a clean audit trail of what was suggested and what was adopted.

That way, AI reduces the mechanical work of hunting for action points, while partners keep full control over what the firm actually commits to do — and by when.

This article is general information for practitioners — not legal advice or guidance on your firm’s specific compliance obligations.

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.