Don’t go shopping (for tech) when you’re hungry​

Artificial Intelligence has quickly become the boardroom topic of the decade.​

Executives are under pressure to identify AI opportunities, improve productivity, reduce costs and modernise operations. Software vendors are promising

transformational outcomes. Internal teams are racing to identify use cases. Competitors are announcing AI initiatives.​

In the rush to embrace AI, many organisations are making a familiar mistake.​

They are going shopping while they're hungry.​

Most people know this is a bad idea. When you're hungry, everything looks appealing. You buy more than you need. You make decisions based on impulse rather

than logic. You arrive home with a trolley full of products that seemed like a good idea at the time but don't really solve the problem you set out to address.​

The same thing happens with AI.​

When organisations become excited about the possibilities of AI before understanding how work actually gets done, they often end up investing in tools, pilots

and technology solutions that create activity rather than value.​

The result is usually more complexity, not less.​

AI Doesn't Fix Broken Processes​

One of the most common misconceptions about AI is that it can solve operational problems on its own. It can’t. AI can accelerate a process, automate a task,

support decision-making and improve access to information. What it cannot do is compensate for poorly designed workflows, unclear accountabilities,

duplicated effort or fragmented operating models. In fact, automation and AI often amplify these problems.​

If your process contains unnecessary steps, AI can help you complete those unnecessary steps faster. If your process creates rework, AI can help generate rework

more efficiently. If your process creates poor customer outcomes, AI can help deliver poor customer outcomes at greater scale. Technology rarely fixes

operational complexity. More often, it exposes it.

The Productivity Problem Is Often a Process Problem​

Across Australia, productivity has become a major concern for executives, governments and industry leaders. Yet many organisations continue searching for

productivity improvements through technology alone. The reality is that productivity challenges are often hidden inside operational workflows. Work passes

through too many teams, decisions are escalated unnecessarily and employees develop workarounds to compensate for process weaknesses. What is worse is that

customers are forced to make repeated contact because issues were not resolved correctly the first time.​

These problems existed before AI arrived and they will continue to exist after AI is implemented unless they are addressed directly. The most effective

productivity improvements often come from simplifying work before introducing automation.

Understand Before You Automate​

Before investing in AI, ask yourself one question - do we understand how work actually happens today? And guess who does know – the frontline.​

One of the biggest mistakes organisations can make is designing AI or any process solution without involving the people who perform the work every day.

Don't Shop Hungry!​