TL;DR SUMMARY: Phishing email examples are no longer limited to clumsy scams and obvious spelling mistakes. AI phishing can make messages more personalised, better timed and more convincing across email, voice, text and collaboration tools. Phishing training needs to reflect that reality by helping people practise safer decisions in context, with real-time support when the threat looks like ordinary work.
AI phishing and real-world pressure
For years, phishing training taught people to look for broken grammar, strange links and suspicious urgency. Those lessons still have value, although they’re carrying less of the load now. Attackers can use AI to improve language, imitate tone, scale campaigns and tailor messages to specific roles or situations. The old signals haven’t vanished; they’ve become easier to hide.
Traditional phishing simulations can still play a useful role, especially when they help teams practise recognition and reporting. Their shortfall appears when they become too neat, too predictable or too detached from the messy reality of work. If the exercise looks nothing like the threat landscape people are actually navigating, it may create confidence around threat identification without building the behaviour needed in the moment.
Modern phishing email examples are often convincing because they fit neatly into the working day. A finance request lands near quarter end. A supplier update arrives during a busy project. A login prompt appears after a system migration. The message doesn’t need to be perfect. It only needs to arrive at the right moment, when attention is split and action feels routine.
Alan Bulley, an experienced CISO with a background spanning information security, risk, resilience and programme leadership across financial services and consumer goods, gives the article’s core tension a sharper edge. AI hasn’t invented every risk from scratch, although it has made familiar risks “faster, bigger and easier to scale.” Phishing was already a human risk problem, and AI lowers the barrier for attackers who want to make that risk more believable.
Where does phishing training need to go next? Click rates can still contribute to the picture, although they shouldn’t dominate it. Reporting rates, repeat risky actions, time to report and role-based exposure often tell a richer story. Just as importantly, the experience shouldn’t feel like a gotcha exercise. When users feel punished, mistakes go quiet. When they feel supported, there’s more room for hesitation, challenge and reporting.
Real-time guidance can help close the gap between training and action. A nudge that appears when someone is about to interact with a suspicious message can create a small but meaningful pause. Tools such as Redflags sit in that moment, where the aim is not to replace judgement but to give it a little more space before a risky action is completed.
Phishing training needs to evolve because attackers already have. The aim should be measured preparation, not paranoia. People need help recognising when normal work has been subtly reshaped into a risky decision, then enough support to choose a safer route without feeling they have failed for needing the prompt.
Key takeaways
- AI phishing makes attacks more convincing by improving timing, tone and personalisation.
- Simulation quality matters more than simply running frequent campaigns.
- Reporting behaviour is often as important as click behaviour.
- Real-time nudges help employees respond more safely in the moment.
