For the most part, we took to these new things with some trepidation. It took us years to get our heads around AI; people didn't want to stream too often on their phones lest they risk a bigger data bill from their telco; and we basically had to have a pandemic before the world got used to holding meetings on Teams or Zoom more often than in person.

We adopted these changes largely because we had to. As the world moves, its incumbent on people to move with it. But sometimes, there's resistance to change: an inertia that keeps people stuck in the status quo.

And I get it. The status quo is comfortable, safe. Adopting new things is uncertain, maybe costly, and sometimes risky. I'd have hated to be the first person to bungee jump, drive a car or fly a plane, for example, particularly when I could happily walk on the ground instead of jumping towards it with a string around my ankles, and when the horse and cart had a comfortable seat.

As the saying goes, “if it ain’t broke, don’t fix it”. And sure, those things weren’t broken, and the reluctance to change tack when the current way of doing things is working is entirely understandable.

We see this all the time in business. To get change happening requires buy-in to change at scale, and that is a mountain many of them are simply unwilling to climb – particularly when the status quo is working.

The problem is that it works until such time as the business looks up and finds their competitors have whizzed past.

We help businesses automate and streamline the auditing and contract compliance processes to improve their spend analytics and optimisation. I only mention this as we're constantly encountering change inertia among organisations, and the bigger the business, the more pronounced the inertia. And the more pronounced the inertia, the higher the need to shake free of it before it becomes endemic.

Now is the time to understand that just because something "ain't broke" doesn't mean it can't be improved. Technologies that have taken the world by storm, such as AI and Machine Learning, are now being incorporated into everyday functions and creating incredible efficiencies in spaces we couldn’t possibly fathom just a few years ago.

Take Liberty Global, a UK-based Shared Service Centre focused on finance operations. The organisation processes 300,000 invoices annually for its customers, covering areas such as accounting, payment operations and payroll. It deployed an AI-driven Accounts Payable Control Centre which scanned its historical invoice data and soon uncovered around £150,000 of duplicate invoices waiting for payment, which were immediately cancelled. It also found £92,000 of duplicate invoices already paid, which the company raised credit notes against.

This is not an argument advocating for change for change’s sake. Some changes don’t make any sense for a business, and some may hinder it. But analysis of the options presented is paramount, looking not only at today’s needs and challenges but those of tomorrow.

Change is daunting, but it’s also necessary as the world evolves. If we didn’t move with the times, you might be reading this on a cart while juggling a street directory and steering a horse… which would be fine if that's all we knew. But give me the car and plane and streaming any day of the week.