An AI-drafted suitability report should never be treated as finished just because it reads well. Fluent writing is not the same as suitable advice, complete evidence, or firm approval.
That distinction matters for advice firms. AI can help reduce drafting time, structure information, and turn adviser notes into clearer client-facing language. But the final report still needs to be checked against the advice file, the client's circumstances, the firm's template, and the firm's review process.
The right review process lets advisers and paraplanners use AI for useful drafting work while keeping human judgement, file evidence, and firm standards in control.
Quick answer
To review an AI-drafted suitability report, check the source information, client-specific reasoning, recommendation, risks, charges, template fit, missing information, version history, and final human approval.
A practical review should answer three questions:
Did the draft use the right information?
Does the report explain the right recommendation for this client?
Has a qualified human checked and approved the final version before it goes to the client?
If the answer to any of those questions is unclear, the draft needs more review before it is trusted.
Why AI-drafted reports need a different review mindset
Traditional suitability report review is often focused on whether the report is complete, accurate, clear, and aligned with the advice file. Those checks still apply.
AI adds a second layer. Reviewers also need to ask how the draft was produced.
For example:
What information was available to the AI?
Was anything important excluded?
Did the AI use old, incomplete, or irrelevant information?
Did it infer something that was not in the file?
Did it smooth over uncertainty?
Did it make the reasoning sound stronger than the evidence supports?
Did it change the adviser's recommendation while improving the prose?
The risk is not only that AI makes obvious mistakes. The bigger risk is that it produces a polished draft that feels complete even when the underlying reasoning, evidence, or template fit still needs work.
That is why review should focus on traceability, reasoning, and approval, not just grammar.
1. Check the source information
Start by asking what the draft used.
An AI-drafted suitability report should be traceable back to the information in the advice file. The reviewer should be able to see whether the draft was based on the right fact-find, meeting notes, adviser instructions, product research, risk profiling information, capacity for loss details, and relevant client communications.
This is the first review step because every later check depends on it. If the source information is wrong, incomplete, or unclear, the report may read well while still being unreliable.
Reviewers should check whether the draft used:
the latest fact-find
the correct client objectives
adviser recommendations and rationale
attitude to risk details
capacity for loss notes
knowledge and experience information
income, expenditure, assets and liabilities, where relevant
existing arrangements
product or provider research
charges and cost information
meeting notes or call summaries
client preferences, constraints, and exclusions
any firm-specific compliance instructions
The key question is: can the reviewer follow the draft back to the underlying file?
If the source trail is not visible, the reviewer has to recreate the logic manually. That removes much of the value of using AI in the first place.
2. Check that the recommendation has not drifted
The report must match the advice actually given.
This sounds obvious, but it is one of the most important checks in an AI-assisted workflow. AI can sometimes make a recommendation sound broader, stronger, simpler, or more certain than the adviser intended.
Look for drift between:
the adviser's instruction and the draft wording
the agreed advice scope and the report narrative
the selected product or strategy and the explanation given
the client's stated objectives and the outcomes described
the firm's intended recommendation and any AI-generated summary
Recommendation drift can be subtle. For example, an adviser may have recommended a specific action for a narrow objective, but the draft may describe it as if the firm has carried out a full financial planning review. Or the adviser may have given a conditional recommendation, but the draft may make it sound unconditional.
Reviewers should pay particular attention where the recommendation is:
nuanced
conditional
based on trade-offs
replacing an existing arrangement
dependent on assumptions
linked to a specific client objective
subject to later review or further information
A useful test is to compare the recommendation section with the adviser's original instruction. If the draft has added meaning, removed caveats, or widened the advice scope, it needs correcting.
3. Check the suitability reasoning
Generic reasoning is one of the easiest problems to miss.
The draft should explain why the recommendation is suitable for this client, not why the product, wrapper, provider, or strategy is generally reasonable.
A strong suitability explanation connects:
the client's objectives
the client's current circumstances
the client's risk position
the client's time horizon
the client's capacity for loss, where relevant
the client's preferences and constraints
the recommendation
the risks and trade-offs
The reviewer should be able to see the chain of reasoning. The report should not simply list the client's circumstances in one section and then describe the recommendation in another. It should explain how the facts support the advice.
A useful test is whether the reasoning would still make sense if the client's name were changed. If it would, the report probably needs more client-specific work.
Weak AI-generated reasoning may include phrases such as:
"this meets your objectives"
"this is suitable for your needs"
"this aligns with your risk profile"
"this provides flexibility"
"this supports your long-term goals"
Those phrases may be acceptable if they are supported by specific reasoning. On their own, they are not enough. The reviewer should ask: why does it meet this client's objectives, in this situation, compared with the alternatives?
4. Check risks, disadvantages, and trade-offs
The report should make relevant risks, disadvantages, charges, limitations, and trade-offs visible.
AI drafts can sometimes soften these sections because the writing pattern favours smooth, confident explanations. A reviewer should make sure the report does not over-emphasise benefits while under-explaining the downsides.
Depending on the advice, risks and disadvantages may include:
investment risk
inflation risk
sequencing risk
withdrawal sustainability risk
loss of guarantees
loss of benefits
tax consequences
early exit penalties
product charges
platform charges
advice charges
reduced flexibility
market volatility
reliance on assumptions
the consequences of not reviewing the arrangement
The risks section should be specific to the recommendation. Generic risk wording may be useful as a base, but it should not replace client-specific explanation.
For example, if the advice involves moving from one arrangement to another, the report should explain what the client may lose as well as what the client may gain. If the recommendation depends on a long-term time horizon, the report should make that dependency clear. If withdrawals are being recommended, the report should explain the relevant sustainability risks.
The reviewer should also check balance. A report that reads like a sales document is not doing the same job as a suitability report.
5. Check charges and cost explanations
Charges are often included in suitability reports, but the quality of the explanation can vary.
A reviewer should check that the report explains relevant costs clearly and consistently with the advice file and disclosure documents. The report should not leave the client to piece together the impact from separate documents without context.
Depending on the advice, check for:
initial advice charges
ongoing advice charges
platform charges
product charges
fund or investment charges
transaction costs
exit fees or penalties
whether VAT is relevant
how costs affect the recommendation
whether lower-cost alternatives were considered, where relevant
The important review question is not only "are charges present?" It is "does the client have a clear explanation of the costs connected with this recommendation?"
If the AI draft has pulled charge information from an old source, rounded numbers incorrectly, or described charges in inconsistent language, the reviewer should correct it before approval.
6. Check the firm template
The draft should follow the firm's existing suitability report template.
That includes:
section order
approved wording
required paragraphs
formatting expectations
advice-area-specific content
signposting
risk warnings
disclosure wording
internal review markers
required appendices or supporting documents
If AI improves the prose but breaks the template, the firm has gained a writing problem disguised as a time saving.
This matters because templates are not only about presentation. They reflect the firm's agreed process and review standards. A report that looks better but misses a mandatory section, moves a key disclosure, or changes approved wording may create more review work.
Reviewers should also check whether the AI has over-written firm-standard language. Some wording may be editable; some may need to remain exactly as approved. The workflow should make that distinction clear.
7. Check missing information and open questions
A good AI-assisted workflow should make gaps visible.
Reviewers should not have to guess whether a section is absent because it is not relevant, not available, or simply missed. Missing information should be flagged clearly before the report is treated as ready.
Common gaps include:
unclear objectives
incomplete fact-find details
missing risk profile information
unclear capacity for loss
missing charges
missing provider or product details
unclear existing arrangement information
no explanation of alternatives
no reason for replacement advice
missing tax assumptions
unclear client preferences
no adviser rationale for a nuanced recommendation
The reviewer should decide whether each gap is acceptable, needs adviser input, or means the report cannot progress.
This is an important difference between AI drafting and ordinary proofreading. A proofreader may correct what is on the page. A reviewer of an AI-drafted suitability report also needs to notice what is not on the page.
8. Check version history and changes
Reviewers should understand what changed between the AI draft, adviser edits, paraplanner edits, and final version.
Version history matters because suitability reports often move through several hands. If AI creates the first draft, an adviser amends the rationale, a paraplanner updates charges, and a reviewer asks for changes, the final file should make it clear which version was approved.
Useful questions include:
Who generated the draft?
What source information was used?
Who edited the draft?
What material changes were made?
Were reviewer comments resolved?
Which version was approved?
Was the approved version the one sent to the client?
This does not mean the process needs to become bureaucratic. It means the firm should avoid an invisible drafting trail where no one can reconstruct how the report reached its final form.
9. Check security, permissions, and client data handling
Because suitability reports contain sensitive client information, firms should also consider how any AI-assisted drafting tool handles client data, permissions, and security.
Reviewers and operations teams may want to understand:
who can access the client file
who can generate or edit drafts
whether permissions follow the firm's existing access model
how client data is handled
whether data is used to train external models
how outputs are stored
how audit trails and approvals are managed
how the firm controls access when people join, move roles, or leave
This is not only an IT question. It affects how confidently the firm can use AI in a regulated advice workflow.
You can read more about Templi's approach to security here: templi.ai/security.
10. Check final human approval
The final report needs the firm's normal human approval before it is sent to the client.
AI can support the workflow, but it should not become an invisible shortcut around the review process. The adviser, paraplanner, supervisor, or compliance reviewer should know what they are approving and why.
Before final approval, the reviewer should be comfortable that:
the recommendation is accurate
the reasoning is client-specific
the risks and disadvantages are clear
costs and charges are correct
the report follows the firm template
missing information has been resolved or documented
the source trail is clear
the final version is the version being issued
The approval step should be visible, deliberate, and consistent with the firm's normal process.
Practical review checklist
Before trusting an AI-drafted suitability report, check:
Source trail: Can you see what information the draft used?
Advice scope: Does the report reflect what the firm actually advised on?
Recommendation: Does it match the adviser's instruction?
Client-specific reasoning: Does it explain why the recommendation suits this client?
Risks and disadvantages: Are the main trade-offs clear and balanced?
Costs and charges: Are charges accurate, relevant, and explained?
Template fit: Does the report follow the firm's approved structure and wording?
Missing information: Are gaps flagged rather than hidden?
Version history: Can the firm see what changed and who approved it?
Security and permissions: Is client data handled appropriately?
Final approval: Has the right human reviewed and approved the final report?
What this means
Reviewing an AI-drafted suitability report is about more than proofreading.
The firm needs to check source traceability, client-specific reasoning, template fit, risk disclosure, charges, version control, security, and human approval. The draft may be faster to produce, but it still needs to be reviewed with the same seriousness as any other suitability report.
The best AI-assisted workflows make this easier. They do not ask advisers and paraplanners to trust a black box. They help teams see the source information, identify gaps, edit the rationale, preserve firm-standard wording, and approve the final version before it reaches the client.
Related reading
Next step
See how Templi supports AI-drafted suitability report review.
Templi helps advice teams draft suitability reports inside their own templates, with source information, missing details and human approval kept visible.
