How financial advisers are using AI in 2025

Financial planner Ian Else did a deep dive to see how AI could save him time during the client review process. He found he could save 3 hours per client.

Once again, Timeline's conference, this year 'Adviser 3.0' was a blast. Among the famous names like Chris Hoy and Tim Peake, a standout breakout session came from Heather Murray, presenting 'AI for Non-Techies' —in other words, people like me.

It's becoming clear that AI will do for financial services what the internal combustion engine did for transport: it will be convenient, time-saving, and will probably end the world.

On the journey home, I started thinking: if a financial planner really committed, how could they leverage AI and technology to streamline their business? So, I took a deep dive into my own review process to find out.

Before anyone @s me, this was an experiment. I haven't rolled it out to clients yet.

Here's how my review process currently breaks down:

• Scheduling the meeting/requesting fact find updates: 10–15 minutes
• Meeting prep (including info review and cashflow updates): 60–90 minutes
• Holding the meeting: 60–90 minutes
• Meeting notes and updating the fact find: 90–120 minutes
• Post-meeting email: 20 minutes
• Annual suitability report: 90–120 minutes
• Actions (fund switches, income withdrawals, etc…): 0–60 minutes
• 'Your work is complete' email: 10 minutes

That totals around 7 to 9 hours per client. This is about what I expected.

Assuming a working year of 219 days (365 days minus weekends, holidays, and leave), I have roughly 770 hours to spend on reviews — enough for about 100 clients if I dedicate half my time to this work.

But what would I need to do to hypothetically serve 200 clients?

1. Scheduling meetings and requesting updates

This was a straightforward automation. I already use a Google Sheet to track client review dates. I set up a Zapier automation to send a bespoke GPT-generated email with a Calendly link four weeks before a meeting is due.

Time saved: 12 minutes per client

2. Pre-Meeting Preparation

Rather than reading last year's meeting notes and suitability report, I now upload all relevant client documents into NoteBookLM (an AI-powered summarisation tool by Google). It produces an audio summary I can listen to while doing other tasks.

Time saved: 20 minutes per client

3. Meeting notes and fact find updates

I've used Otter AI for five years, but I recently switched to industry-specific tools like Marloo and Saturn. With Zapier and ChatGPT, I can automatically update the fact find using transcribed meeting notes.

Time saved: 60 minutes per client

4. Annual suitability report

While I haven't fully implemented this yet, the writing is on the wall: AI will soon be capable of generating compliant reports using client objectives, actions, performance data, and fees.

Estimated time saved: 60 minutes per client

5. Post-meeting and completion emails

This is another quick win. Using my review spreadsheet, I toggle one column from 'true' to 'false', triggering an email generated using meeting notes and a GPT trained to replicate my tone —whether formal, casual, or somewhere in between.

Time saved: 30 minutes per client

The result

Altogether, I could save around 3 hours per client, bringing the total time down to 4–6 hours. That change boosts my potential capacity to 154 clients without adding admin support.

It's not quite 200, but it's a significant leap. And I believe there's still more efficiency to unlock.

Thinking beyond reviews

I've started exploring platforms like Notion to build customised workflows based on client-specific data. This led me to a bigger question: what is the future of traditional back-office systems?

Why should I manually upload documents and then search for them? Instead, I could create an AI-driven filing cabinet that locates any information in milliseconds. It's not just about reducing hours — it's about fundamentally changing how we work.

Final thought

The next three-to-five years are going to bring exponential growth in AI's capabilities. Will we see Artificial General Intelligence (AGI) in that time? Maybe. But what I do know is this:

If you don't start using AI now to streamline your business, you may not have a business.

You don't need to be a tech wizard to get started. But you do need to start.

Ian Else is a financial planner at 4 Financial Planning, based in Bristol.