AI Risk, Accuracy & Human Review

AI tools are genuinely useful, but they fail in ways that are easy to miss precisely because the output looks so polished. A confident, well-written paragraph can contain an invented figure, a misremembered rule, or a leaked piece of private data. The skill that matters most isn’t avoiding AI — it’s using it with your eyes open, so the convenience never quietly turns into a problem. A few habits around accuracy, privacy, and review cover the vast majority of the risk.

The big three risks

Three risks come up again and again. The first is hallucination: the model states something false with total confidence — a made-up statistic, a fake citation, a policy detail that doesn’t exist. It isn’t lying; it’s predicting plausible words, and plausible isn’t the same as true. The second is privacy: pasting confidential customer data, personal information, or unreleased plans into a tool that isn’t approved can leak it or feed it into training. The third is security: AI-generated text or code can carry mistakes or hidden instructions, so it shouldn’t be trusted blindly or run without checking.

Catching hallucinations

The defence against hallucination is simple in principle: verify anything that matters before you rely on it. Treat names, numbers, dates, quotes, legal points, and citations as unconfirmed until you’ve checked them against a trusted source. Imagine a copilot drafts a report that includes “revenue grew 23% last quarter.” If that figure wasn’t in your data, it may be invented — a reviewer who checks the source catches it before it reaches a client or a board. The more consequential the claim, the harder you check. A quick way to build the habit is to highlight every specific number, name, and date in an AI draft and treat each highlight as a question you still owe an answer to.

If an AI tells you a fact you would have to defend to your boss, a client, or a regulator, verify it from the source. Confidence in the wording is not evidence it’s correct.

Protecting privacy and security

Be deliberate about what you put into AI tools. Don’t paste confidential customer data, personal information, passwords, or unreleased material into public consumer tools — use the enterprise version your company has approved, where data isn’t used for training and stays within agreed limits. For anything AI-generated that does something — code, formulas, automated messages — review it before it runs, just as you’d review a junior colleague’s work. And be alert to instructions hidden in content the AI reads, which can try to make it misbehave; if an output seems to be acting on an instruction you never gave, stop and check.

Building the review step

The reliable way to manage all of this is a clear human-review and approval workflow: define which AI outputs need a human sign-off before they go out, and who signs off. Low-stakes internal drafts might need only a quick read; anything customer-facing, financial, legal, or irreversible should pass through a named reviewer. Write the rule down so it’s consistent rather than left to chance. The point isn’t to slow everything to a crawl — it’s to match the level of checking to the level of risk. Done well, the workflow becomes invisible: trivial drafts move fast, and the few outputs that could really hurt you get the second pair of eyes they deserve.

Spot it: which risk is this?

Read each situation and decide for yourself, then tap a card to flip it and check your answer.

Sort the outputs

Drag each AI output into the bucket that matches the right level of review — or tap an item, then tap a bucket. Hit Check placement when you’re done.

How to use it

Before you send or publish AI output, run a quick mental checklist: Did I verify every fact that matters? Is any of this confidential, and is the tool approved for it? Does anything here take an action, and has it been reviewed? Who needs to approve this before it goes out? Adopt phrases like “let me check that figure against the source” and “is this an approved tool for customer data?” Make verification and approval the normal final step, and you get the speed of AI without inheriting its mistakes.