In short: Successful AI adoption in the food industry is driven by culture, not technology. It starts with leadership and governance, and follows five steps: (1) leadership & governance, (2) training everyone, (3) defining the “why”, (4) preparing reliable data, and (5) choosing the right AI model and tools.
If you are the CEO of a food company, there are some questions you should ask yourself when it comes to Artificial Intelligence (AI) adoption:
- Have I given my employees the resources to cope with this revolution?
- Have I set up clear governance rules for my company?
- What should I use AI for?
- Am I aware of the opportunities it offers and the risks it conveys?
For those of us who have already lived six decades in this world, the AI revolution is probably the biggest one we have experienced in our lifetime. At least it is for me.
Not only because it makes all the existing knowledge in this world available to any of us, but also because of the exponential changes happening in this field on a weekly basis since the launch of ChatGPT in November 2022, when generative artificial intelligence was made public.
Step 1: It starts with Leadership and Governance
Yes, as is the case with Food Safety Culture, AI adoption starts with Leadership and Governance. Do you know what your main responsibility in terms of AI as a CEO of your company is?
Isn’t it to help your employees cope with the most radical transformation they have experienced during their career, not to say during their life, so that they can better serve the purpose of the company and the expectations of the customer – making sure, for a food company, that the products we deliver are healthy and safe?
Step 2: Train everyone, not just a happy few
The second step in AI adoption for a company should be the training of everyone and not of a happy few.
If you have been working on your team members’ employability and have already invested to allow them to grow within the company, then helping them acquire the necessary skills to deal in a smart and responsible way with AI seems like the right thing to do.
As leader of the company, your second step should also be to clarify the governance rules in relation to the use of AI within your company.
You should be aware of the risks if you don’t work on governance, because AI is a reality that is present in most households. If this is not enabled within the company, you can be sure that your employees will be tempted to use it at home to reduce their workload.
Step 3: Define the “Why”
In terms of culture, defining and sharing the “why” – why we do things the way we do them within the company – is the key success factor and the third step.
AI is not just a tool; it is what enables everyone within the company to be better, to focus on their areas of excellence, and to speed up processes with limited added value.
The benefits are invaluable, especially when we are talking about making our food safer.
One of the reasons why more than 80% of AI projects fail is because the “why use AI” is not defined and the expectations in terms of ROI are not realistic.
I learned recently that there is much more to expect in terms of combined individual productivity than in complex projects that try to embrace all the departments of the company at once. Then you can make visible the potential of artificial intelligence for the different areas of the company.
Step 4: Prepare the “What” – AI needs reliable Data
Streamlining processes and getting rid of low-value tasks is one of the benefits of AI, but probably the most important one is to help us analyse data and accelerate decision processes based on it.
Managing (collecting, cleaning, updating) data is our fourth step. Finance, HR, Marketing, Purchasing, Supply Chain, Maintenance, Production, Quality: you name it.
In all these departments, work on data must be done to optimize the analysis with AI:
- Which data do we have?
- How reliable is it?
- Which data do we need?
Only then can you harness all the potential of artificial intelligence for the benefit of your customers and your company.
Step 5: Choose the “How” – the right AI model and tools
After the first steps and some phases of trial and error – yes, you should allow yourself to fail – it will be easier to choose the models and tools that will better fit your purpose and that will guarantee the best security for your data.
Choosing the right model is the fifth step. The choice will depend, of course, on the business cases you choose to explore.
Be aware that it is better to start small and to scale up afterwards. This is a recommendation that applies to all projects related to systems implementation, but it is even more true in the field of AI due to the constant evolution in the capabilities of AI models.
How far is your company in its AI strategy?
So, tell me: how far are you in your company in setting up the AI strategy that you will need if you want your company to survive?
Don’t hesitate to reach out if you want some help in this process.