Read Our Blog On Culture Change

Most people in business are familiar with meetings. But let’s be specific: they’re familiar with reporting meetings - those calendar fillers where the aim is survival. These are not environments where innovation thrives. And yet, when organisations decide they want to be more innovative, they often expect it to happen inside the same meeting culture that has rewarded evasion and blame.

We’ve all heard the advice: “Fake it ‘til you make it.” Say it with enough confidence, and it sounds almost empowering. It’s a useful push to keep going despite feelings of self-doubt. But not far behind those words lies a quieter voice that whispers, “You don’t belong here.” That voice belongs to Imposter Syndrome - which can show up even when we’re not faking anything at all - the persistent belief that your success isn’t deserved.

Workplaces love a good shortcut. Roles, departments, and reporting lines help to make sense of who does what. But there’s a different kind of shortcut that quietly works against inclusion: stereotypes. These sticky labels flatten people into one-dimensional characters and distort how we relate at work. The problem with stereotypes is not only that they’re inaccurate. It’s that they flatten curiosity.

There’s always one. The late arrival with their mic on, crashing into the call mid-sentence while asking, “Can you hear me?” The person eating cereal on camera, or the mystery participant whose name is “iPad (3)” and hasn’t said a word in 45 minutes. The well-meaning multitasker, typing furiously on another screen. Or the over-sharer who doesn’t know when to stop. If any of these sounds familiar, you’ve lived through Zoom Doom.

The potential for collaboration between humans and AI opens the door to a new category of roles - what some are calling super jobs. These roles emerge when technology transforms not just how we work, but the very nature of the work itself. They blend human judgment, creativity, and emotional intelligence with the power of intelligent machines, data, and algorithms. We’re getting better at identifying the tasks AI can take over.

All too often segmentation simply involves grouping employees into different levels of seniority or into functions. It’s far more effective to segment employees according to their attitudes towards whatever the engagement campaign is aiming to achieve. Gen Z, Millennials and Boomers are just generalisations based on people’s birth dates. Millions of people within each ‘segment’ can’t all be the same.