“That’s how we’ve always done it.” 

These words are often spoken without much thought, but they can quietly cripple an organisation’s growth and efficiency. In the age of AI, it’s one of the most dangerous phrases.

Behind those words is a stubborn refusal to change. A clinging to business-as-usual (BAU) thinking in a world that’s anything but. While AI presents bold new ways of working, many organisations are still trying to retrofit it into outdated workflows, expecting transformation while keeping their processes comfortably familiar.

At Via, as we help ambitious businesses align their people, processes and tech, we’re seeing business leaders misunderstand AI, thinking it’s just another tool to plug in and gain some efficiency. 

AI demands a shift in thinking.  

The organisations that win the game of business in the next 6, 12, 18 months won’t be the ones that simply digitise old habits. They’ll be the ones willing to redesign work from the ground up and whose people embrace and help shape new roles. Shifting from doing the work to managing the AI that does.

Let’s explore why BAU and AI don’t mix, and how you can prepare for what’s next.

The comfort trap: how “normal” becomes the enemy of “excellent”

Many organisations continue to use old processes or technology simply because everyone is used to them. Over time, inefficiencies creep in quietly. An extra manual step here. A quick workaround there. A bit of custom code that no one documents. What started as a clean system slowly becomes a “Frankenstein setup”.

Without a regular rhythm of review and refresh, even the best-designed process can evolve into a maze. And when teams stop questioning the workflow, the mess becomes invisible. Like a frog being boiled alive, chaos grows slowly, but everyone remains comfortable. Meanwhile, operations slow down, efficiency is lost, and innovation flatlines.

Actions to take this week:

Stress-test your comfort zone by having each team’s processes reviewed by someone not part of the team:

• Which time-consuming processes are executed regularly?
• Why are they executed that way?
• What would break if we stopped or altered the flow?

Don’t automate: redefine the work itself

Many businesses approach AI by attempting to replicate existing processes. But AI doesn’t thrive in legacy logic. It thrives in environments designed for outcomes. The real shift is this: your people will stop doing the work and start managing the AI Agents that do. 

The question shouldn’t be “how do we do this faster?”, but “what are we actually trying to achieve?” and remaining open to a different way to get there. Without clarity on the outcomes, you’ll simply automate inefficiencies and force a Ferrari to follow the safety car.

Actions to take this week:

Choose one core process and redesign it: start from a blank page. Don’t try to “fix” what you already have; start by defining what outcome you need. Define:

• The ideal outcome (What does excellence look like?)
• The decisions involved (think compliance: where is human supervision absolutely necessary?)

What work can an AI agent take over (not as a supporting agent, but as an independent operator)

AI might feel like magic, but it’s not

Businesses want AI to do magical things. But AI is just automation; it will replicate your bad processes and amplify them.

Trying to implement AI into a business full of fragmented systems, shadow processes, and legacy tools is like a fast car without a destination: it will go fast, but it will get you nowhere.

Transformation is a systems game. To deploy AI successfully, you need simple, streamlined processes and clear performance markers.

Actions to take this week:

• Pick one workflow and articulate it in bullet points and short sentences.
• Feed the outline of your process into ChatGPT to critique and provide alternative ideas on how to optimise or rethink the process entirely.
• Discuss the proposed changes with the team to gather their perspective and insights.

Readiness > hype

It doesn’t matter how exciting the technology is if your organisation isn’t ready to adopt it. Most failures happen not in the tech stack, but in the people stack, when teams don’t understand, support or believe in the change.

Successful AI adoption isn’t about being early. It’s about being prepared. That means having a clear vision, a plan for upskilling, and systems that are built to flex, not fracture, under pressure.

Action to take this week:

Take our Change Readiness Assessment to evaluate your leadership, process maturity, and team alignment.

It’s a fast, honest look at where you are and where you need to get to.

You can’t step into the future by dragging the past with you. AI isn’t a plug-and-play fix; it’s a reinvention of how work happens. If you’re trying to make it fit inside your current systems, you’re not really innovating.

Stop thinking about AI in terms of “I have to keep up” and start thinking about “what do I let go of”.

Need a clearer picture of what to tackle first? Start with our free Change Readiness Assessment. It’s your blueprint for leaving BAU behind and building something better.