Personal AI You Can Trust
When you can't tell your AI the whole truth.
Hi friends,
This week we welcomed Mark Suman from Maple to The Good Stuff. The conversation gets into something many AI discussions gloss over - the information business owners hold back from their AI tools tends to be exactly the information that would have materially improved the output. We get into why that matters and how to address privacy with your AI in this week's Good Stuff.
Three news items worth your time as well, including new research showing that privacy concerns are now the single biggest reason Australian SMEs are holding back on AI.
The Free AI Audit we launched last week is still live at otherstuff.ai/ai-audit. If you’re thinking about how to use AI in a way that respects you and doesn’t hand control of your business over to Anthropic then this will be a good place to start.
Now to this week’s Good Stuff.
What You're Not Telling Your AI.
Many people will say they care about privacy, and they mean it, but the day to day reality of running a business often pushes us toward whatever moves faster and gets the job done.
Customers need answers, staff need direction, cash has to be watched and problems have to be solved, so the business ends up using the tools that are easiest to reach, even when there is some discomfort about what those tools might be doing behind the scenes.
That is why many privacy arguments fail to land inside a small business.
They ask owners to care about privacy as a principle and to act as though an abstract concern should matter more than an immediate operational need, which is often a luxury that the day to day reality of running a small business doesn’t allow for.
AI changes that calculus because it moves the privacy question much closer to the centre of the business.
The problem with AI inside a small business is that the useful information is often the sensitive information.
These are the use cases that require client names, commercial terms, project history, contract details, employee information, customer records, pricing, margins, and the internal decisions that have not been made yet.
These are exactly the categories of information that businesses already work hard to restrict through permissions, contracts, confidentiality obligations, access controls, and internal processes.
That is what stood out in this week's conversation on The Good Stuff with Mark Suman from Maple.
Mark made the point that people have tolerated data extraction for years. They knew their email was being scanned, that social platforms were tracking them, and that the internet was gathering more than it admitted, but most carried on anyway because the trade-off felt distant enough to ignore.
AI brings that trade-off into the middle of your work.
A business owner might use it before they have decided what to do, trying to work out what to say to a client, how to handle a staff issue, whether a project is still profitable, or how to respond to a problem that has not yet been resolved. To be useful, the model needs the context around the decision, and that is where the privacy problem becomes more serious.
For small and medium sized businesses, this matters because a lot of the commercial value of AI becomes dependent on context.
A generic prompt can help with generic work, but the valuable use cases usually require information the business is already responsible for protecting.
You might be trying to understand why sales have slowed down, or whether a staff member is still right for a role, or whether the next hire is still financially feasible, or how to respond to a difficult customer without making the situation worse.
The more context you give the AI, the more useful the tool becomes, the better the reasoning can be, and the more specific the situation, the less generic the response.
This is where privacy becomes more than a defensive issue and becomes about performance and output.
When a business doesn’t feel safe being candid with its AI tools, sensitive information might leak, be stored, be used for training, or become subject to rules the business doesn’t control.
But you can also start editing or self censoring the context before the conversation begins, leaving out the detail that would actually change the quality of the output, like removing names, or describing the situation in a way that feels safer to share.
Then your AI gives an answer to that version of the problem rather than the real one.
This is why a watched AI is potentially a worse thinking partner. The model might be powerful, the interface smooth, the answer intelligent-sounding, but the person using it has become less truthful with it.
That is a limitation because the real promise of AI for SMEs is not that it can produce more words, but that it can help a small team reason, decide, document, automate, and execute with more leverage than they could before, and that promise depends on the business being able to bring the real problem into the room.
Many small businesses already trust big brands by default because everyone else uses them, and that kind of trust is mostly social proof.
The trust that makes AI genuinely useful in a business is something more specific. It’s what lets a business owner say the actual thing and bring the sensitive customer context, the awkward staff issue, the worrying cash position, or the uncomfortable strategic thought into the conversation without holding back.
If the safest version of an AI workflow is one where the owner never tells the tool anything important, then the business is leaving a lot of value on the table.
The tool can help with surface level work, drafting emails, summarising documents, generating first drafts of things where the details do not really matter.
The deeper work requires the details you’re withholding.
The most valuable questions are sometimes the ones we feel least comfortable asking in a place you don’t fully trust.
AI turns that into a product problem.
The best tools won’t simply be the ones with the strongest models, they’ll also be the ones that create the conditions for candour, whether that comes through stronger privacy, local control, open source infrastructure, or clearer boundaries around how memory and context are handled.
The exact implementation will vary but the principle is the same - the AI has to be somewhere the business can tell the truth.
This is easy to miss because so much of the AI conversation is still dominated by demos. A demo can ask a polished question because a demo is designed backwards from the answer. The context is clean, the data is fake, the problem is contained, and nothing serious is at stake.
That is why so many AI demos feel impressive and slightly unreal at the same time.
They show what the tool can do when the world has already been arranged to make the tool look good. A real business doesn’t work like that.
You’re not simply asking the AI to draft an email or summarise a document. They are trying to work out what the situation actually is before deciding what to do about it.
Last week, we talked about whether businesses are giving Anthropic, OpenAI, and Google an off switch on their business.
This week's conversation with Mark points to another version of the same underlying issue.
Even before a platform can switch you off, you may already be switching yourself off inside it, withholding the information that would make the tool genuinely useful, using AI only for the safe outer layer of the business, asking polished questions because the real ones feel too sensitive to type.
The work that actually moves the business forward requires that real context.
If you’re thinking about privacy in this context inside your business, we’d love to chat.
We got into this and more this week in the Big Episode 57 of The Good Stuff with Mark Suman.
Three Things in AI for SMEs
1. The numbers on Australian SMBs and AI are now very hard to ignore — Margin Up
Intuit published its 2026 AI Impact Report this week, built on data from more than 5.3 million QuickBooks businesses and surveys of 34,000 business owners across Australia, the US, UK and Canada. Among Australian SMBs already using AI, 79% report productivity gains, a significant jump from 37% in mid-2024, and around 43% report increased revenue as a direct result. Regular AI adoption among Australian SMBs has nearly doubled over 18 months, from 40% in July 2024 to 69% in January 2026, while daily use has almost tripled in the same period. The same report found that across all four markets, more businesses report increasing employment as a result of AI than reducing it. NAB News
What it means for you: The businesses that have genuinely integrated AI are starting to pull away from those that haven't. The report describes the gap as "the difference between a business that grows and one that treads water."
Intuit 2026 AI Impact Report →
2. Appearing in AI-generated search results is becoming as important as Google rankings — Capital Up
As Australian consumers increasingly use ChatGPT, Gemini, and Perplexity to research products and services, appearing in AI-generated answers has become as important as Google rankings for many businesses. Unlike traditional SEO, which rewards consistent effort over time, AI search visibility tends to reward businesses that have clear, well-structured information about what they do and who they serve across the web. Most SMEs have not started thinking about this yet, which means the window to build that presence early is still open. LinkedIn
What it means for you: If a potential customer asks an AI tool which accountant, tradie, or consultant to use in your area, whether your business shows up is increasingly a function of how legible you are to AI systems, not just search engines. This is a new kind of compounding asset and most businesses aren't building it yet.
Side note - if you’re thinking about SEO currently and how to keep up we have a service coming soon that could help. 👀
AI Rank Lab — Australian AI search visibility →
3. Privacy concerns are the single biggest reason Australian SMEs aren't going further with AI — Risk Down
From the same Intuit report: in Australia, privacy and security concerns were the most commonly cited barrier to AI adoption, mentioned by 39% of respondents, a figure higher than the US at 36%, the UK at 35%, and Canada at 36%. Australian SMBs are more privacy-conscious than their English-speaking counterparts, and it is showing up in where they draw the line on what they will and won't put into an AI tool. Insidesmallbusiness
What it means for you: This week's episode sits right in the middle of this finding. The hesitation is real, it is widespread, and it is costing businesses more than they probably realise in terms of the value they are leaving on the table by editing what they put in. The question worth sitting with is whether the tool you are using has actually earned the candour the work requires.
Intuit 2026 AI Impact Report →
That's all for today
If this resonated, we’d love for you to forward this newsletter to one person who might enjoy exploring these ideas too. See you next week!
Cheers,
Pete & Andy