AI for Accountants: Using AI to turn client data into advisory conversations
A free one-hour session for UK accounting firms. Learn a practical workflow for connecting existing client financial data to upcoming regulatory changes, and turning that analysis into advice worth charging for.
Reserve Your Seat
What the session covers:
- Five types of analysis you can run today: Trend and variance, profitability deep-dives, regulatory impact modelling, cash flow scenario planning, and anomaly detection. All using data your clients already have.
- A worked client example: A construction business, 62% labour costs, 18.5% gross margin, and three regulatory changes arriving at once. Mick models the combined impact live and shows how it becomes an advisory conversation.
- A prompt you help build live: Attendees shape a real analysis prompt together during the session. You leave with something you can run on your own client data the same week.
- The GDPR guardrails: What's compliant, what isn't, and the one engagement letter update most practices haven't made yet.
Agenda
- Why clients now expect interpretation, not just information
- Five types of analysis you can run on existing client data today
- Connecting financial analysis to regulatory change
- Building a prompt together live from a real client scenario
- GDPR guardrails for AI use with client data
- How this turns into a client conversation and a fee
- Q&A
Mick Seddon
Founder, Sustainability Suite and The Green Accountants
Mick has run an accounting practice for over 30 years. He was one of the earlier advocates in the profession for building advisory services ahead of compliance automation, and he tests everything he teaches on his own clients first.
After the session
All registrants receive the full recording. Live attendees who complete the short feedback form also receive:
- Workflow guide: Step-by-step for running AI-assisted financial analysis on client data.
- Prompt library: Tested prompts for trend analysis, profitability deep-dives, and regulatory impact modelling.
- Engagement letter clause: A template covering GDPR-compliant AI use for advisory services.
Live Attendee Bonus:
The workflow guide, prompt library, and engagement letter clause are exclusive to those who join live and complete the brief feedback form.
What this looks like in practice
The session is built around a real client scenario, worked through live. Here is the example Mick uses.
The client
A construction business. Labour costs at 62% of revenue. Gross margin at 18.5%.
Three regulatory changes are arriving at once. None of them appear in the management accounts. All of them are material to how the business operates.
National Insurance increase
Adds £60,000 to the annual cost base on a payroll of £4.8M.
Retention payment legislation
Locks £890,000 in a trust account, creating immediate working capital pressure.
IR35 reforms
Affects how the business can structure its subcontractor mix going forward.
The advisory output
"You're facing a £60,000 annual cost increase plus significant working capital constraints arriving at the same time. Let's model your pricing adjustments, review your subcontractor structure, and prepare for the retention account requirements before they hit."
The analysis that produced this took around 90 seconds to generate. The session walks through how to build it, how to verify it, and how to take it into a client meeting.
"If AI gives you an answer you can't explain, you shouldn't be using it."
This session is about recovering the time you currently spend on research and formatting, so you can focus on the judgement that clients actually pay for.
Worth an hour if:
- You want a repeatable method for turning client financial data into advisory conversations, without building it from scratch.
- You're using AI in your practice already but haven't found a workflow that holds up in client-facing situations.
- You can't make it live. Register anyway and the recording will come to you automatically.
Reserve your place
Free to attend. Register below for the live session and the recording.