Learnings from Fonterra’s AI journey
Chris Kane – Director Global Engineering and Technical at Fonterra Co-operative shares learnings from Fonterra’s AI journey so far.
If your business is anything like Fonterra then you will be getting a lot of consultants and organisations reaching out and promising to solve all your problems, simply with the use of AI.
The hype is certainly real, and it feels like we are now at a tipping point where there are genuine, realisable benefits to be gained from embracing AI.
This is in part due to the rapid reduction in the cost of computing while at the same time the amount of structured and unstructured data available is increasing exponentially.
We know that foundation of AI is data, almost everything we use today is tracking your data, including your fridge and washing machine.
To manage this, data centres continue to multiply in scale and capacity, one such data centre being built for a reported $100 billion USD would consume more energy that the whole of Ireland. Scale unfathomable until now.
But it’s worth noting that AI has been around for over 50 years, and we all use it in our everyday lives, at Fonterra we have been longtime users of AI to support in how we manufacture our products.
For example, we use machine learning to try predict upcoming issues, and image cognition to monitor our packing lines, and have advanced process control to optimise quality and output.
What we are now experiencing with GenAI and this ability to create new and creative content is driving the next wave of transformation in how we think about AI at Fonterra.
At Fonterra we have formed a structured process that allows enough space to purposefully innovate and experiment with AI.
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Prioritise smartly:
Be clear on prioritising the big problems to solve – AI can do many things but is not needed for every scenario. We want to make sure its anchored in solving the right business problems and closely aligned to strategy. The domains we are focused on are innovation, sustainability and cost leadership, so for example, optimising our energy consumption brings real value to our farmer shareholders and de-risks the co-op.
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Quality Data at the centre:
Ensure we have information we can trust, that is secure, assessable and protected. Starting with clean data sets and having policies for data retention and use are the foundations for creating value from AI.
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Culture and governance is key:
Democratise knowledge, ensuring that all your people are educated in AI, understanding governance, value generation and risk minimisation. We have communities of practice, share learnings and have a great governance framework across the co-op.