AI in the water industry, and how to avoid 'garbage in, garbage out'

For the last two days, Wave has been at Victoria University's Workshop on Application of AI, ML, Optimisation and Technologies in Water Management. We are hear both as a sponsor and participant.

The question on everyone's mind: is AI actually going to change how water utilities operate? The answer is that it's complicated.

AI has real potential here, from transforming customer interactions, helping utilities manage their networks, identifying leaks, reducing peak loads, and more. But the most interesting message from presenters across Australia and India was a note of caution: start by asking "what is the real problem we're trying to solve?", not "what can we do with AI?"

That's something we focus on heavily at Wave, and it's reshaped how we approach spatial analysis, water and energy modelling, reporting, and even meeting minutes.

What struck us most, though, was something beyond the technical content: how much this conversation benefits from the relationships being built between Australia and India, with academics and industry voices from both countries presenting side by side. Locally, we heard from Barwon Water and GWM Water on their approach to digital transformation, with genuinely interesting insights.

But as always, one thing was reinforced: AI in the water industry is only as good as the data behind it. Garbage in, garbage out.