Issue 01 · 7 July 2026
The standards body published its AI guidance. It's a list about judgement, disclosure and competence, which is either a disappointment or the whole point.
The Take
The Financial Planning Standards Board put out eight principles for using AI in financial planning at the end of June. Read them and you notice something straight away. Not one of them is about technology.
Investigate a tool before you adopt it. Tell clients you're using it. Critically evaluate what it produces. Watch for bias. Don't put client data into public-facing tools. Keep learning enough to judge the thing competently. Make sure it doesn't hollow out the professional character of your advice. Understand how it shapes what you end up recommending.
That's a list about judgement, disclosure and competence. Near enough the same list you'd write for handing work to a new paraplanner.
I reckon that's the most useful thing about it, and it's the bit that'll get missed. The instinct when a standards body publishes AI guidance is to go hunting for which tools got approved. There's no approved list here, and there won't be, because approval was never the mechanism. The mechanism is that you stay responsible for the output no matter what produced it.
Which is good news if you've been putting this off waiting for somebody to bless a product. You don't need permission. You need a written-down position on those eight things and about an hour with your team to agree it.
FPSB chief executive Dante De Gori put it plainly: trust, professional judgment and accountability remain essential. None of those three are things you can buy.
Also Worth Knowing
Marshan's case study is worth the half hour. A sole practitioner in a regional area starts using AI properly: she discloses it to her clients, strips names out before anything goes in, pays for accounts so her inputs aren't used for training, and pressure-tests the outputs against her own professional view. Textbook. Word gets around about how well she's doing, and she picks up fifteen new clients. Her licensee's AI policy is still sitting in draft six months later. Then the discipline quietly erodes: client details start going in without being anonymised, model outputs get waved through unverified, and eventually she posts an AI-written case study about those first two clients, in a small community where people can piece together who they are.
Nobody in that story did anything reckless. That's exactly the point, and it's why "have we had a problem yet?" is the wrong question to put to your team. The numbers underneath give it away. On the FPSB research Marshan cites (the international standards body, so read it as a global picture rather than an Australian one), around 64 per cent of practices are using or planning to use AI, 45 per cent have an AI policy at all, and only 17 per cent have one the research called comprehensive. So roughly half are using this stuff with no real rules around it. And if your licensee's policy is still in draft, you aren't waiting for a policy, you're operating without one. Write your own practice-level position this month, then diarise a quarterly look at it. The drift is slow enough that only a calendar catches it.
PlannerPal deepened its tie-up with Iress so advisers can launch it straight out of Xplan with single sign-on. What comes with it: AI meeting intelligence, document generation, suggested CRM updates, a CRM updater spanning around 400 Xplan data fields, and a dashboard showing where client records have gaps. Iress's Jamie Grant framed the logic well, saying advisers want the benefits of AI "within the systems they already know and trust". One precision point, because it matters: Grant is Iress's head of product for UK Wealth and this is a UK arrangement, not an Australian launch.
Two things worth taking from it anyway. First, the direction of travel. AI is reaching Xplan through partner integrations rather than as a native Iress feature, and that tells you the shape of the next couple of years better than any roadmap slide will. Second, look at what the tooling actually does. A CRM updater across 400 fields and a data-completeness dashboard are not glamorous AI. They're an admission that the real constraint in most practices is messy client data, not clever reasoning. That happens to be the same conclusion you'd reach by spending an afternoon mapping your own practice, and you don't need to wait for a partnership announcement to start.
Two items this fortnight rather than the usual three or four. It was a quiet stretch, and padding it with something off-topic would waste your five minutes. Past issues live here.
Issue 01 covers the fortnight to 7 July 2026 and was published to this archive on 2 August 2026, when the Brief launched. It was not emailed at the time.
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