As the food industry moves towards net zero commitments, new artificial intelligence (AI) solutions focus on transforming sustainability data management.
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To achieve net zero goals, the United Nations (UN) urges that net zero commitments require credible action for a living climate. Net zero refers to reducing carbon emissions to a small amount of residual emissions. Natural and other carbon dioxide (CO2) removal measures can then absorb and durably store these, resulting in zero atmospheric emissions.
More than 9,000 companies across more than 140 countries have joined the Race to Zero, a coalition that pledges to take immediate action to halve global emissions by 2030.
Decarbonisation, the process of reducing greenhouse gas (GHG) emissions such as carbon dioxide and methane to lower the overall carbon footprint, revolves around moving to a low carbon economy that eventually becomes carbon neutral.
AI is tipped as an ever-advancing area of technology and solution to help the global food systems achieve their net zero emissions goals. The AI for Decarbonisation’s Virtual Centre of Excellence (ADViCE) is working to develop innovative technologies for decarbonisation applications to support the transition to net zero.
Research by the Global e-Sustainability Initiative and Accenture Strategy has found that digital technologies have the potential to reduce global CO2 emissions by 20% by 2030. Identifying and developing these technologies means countries and businesses can potentially avoid the tradeoff between economic prosperity and environmental protection.
In 2022, the global AI market was estimated to be worth $103.7 billion, with PwC indicating that this number could grow to $15.7 trillion by 2030. Through its experience, one company engaging in AI research, Boston Consulting Group, suggests that AI can help reduce GHG emissions by up to 10%, the equivalent of 2.6 to 5.3 Gigatons of CO2.
Food manufacturers are exploring AI’s role in supply chain decarbonisation and efforts to move towards net zero. “AI will certainly play its role in decarbonisation, from augmenting human analysis and decision-making to simply making the sustainability domain accessible and understandable,” a spokesperson for Mondra, an AI-driven environmental insights platform, told Ingredients Network. “AI will enable us to mobilise so many more people and organisations in the food system on the net zero journey.”.
Alongside the BRC Mondra Coalition, Mondra has been working to transform sustainability data management by handling product footprinting and supply chain decarbonisation. Its aim is to help move the food industry towards net zero.
On 23 October, Mondra launched Sherpa, an AI assistant that can query and analyse user product, ingredient and environmental impact data from Mondra’s platform. It aims to enable better environmental and operational decision-making for grocery producers and retailers.
Together with non-governmental organisations (NGOs), the government and the British Retail Consortium, the food industry is striving to collaborate to establish a unified standard for measuring product-level performance and farm data to ensure accuracy and the availability of comparable data.
Mondra saw that the biggest challenge food companies face in getting to net zero is measuring and managing Scope 3 emissions (those that occur in the supply chain). “Mondra’s approach to collaborative decarbonisation is ground-breaking,” said Jason Barrett, founder and CEO of Mondra. “We are essentially giving retailers the platform and tools to support planet-positive category evolution whilst de-risking their business and taking advantage of the commercial opportunity presented by the net-zero economies.”
Where tech innovations can help make food systems more effective and efficient, Mondra strives to adopt them as they become available. “Generative AI has been on our radar for a while, our CTO has been speaking about the impact it has in modern applications for the last 18 months in the most important technical conferences in Europe,” the Mondra spokesperson said.
“Nowadays, it’s not just the technology being mature, but also the implementation patterns and – most importantly – the infrastructure to use it in a responsible way,” added the spokesperson. This triggered Mondra to experiment with how to build an intelligent assistant. It wanted a tool equipped with Life Cycle Assessment (LCA) analysis knowledge, which the food industry could use to help them towards net zero without forgetting or forgoing data privacy.
The Sherpa tool allows users to chat with their data, explore it and analyse it. However, the tool is not trained on client data. “We never send our clients’ private datasets to an AI model for training purposes,” said the spokesperson. Instead, Sherpa is based on a principle called “grounding”. It’s been designed to know the Mondra platform and how to use its services to dynamically query the dataset and interpret the results. “When it does so, it has the same data visibility as the user.”
AI tools, like Sherpa, have the capability to analyse complex datasets on product ingredients and emissions. Through Sherpa, Mondra can use the most technologically advanced models —including the newest GPT-o1, capable of reasoning—to run analysis and what-if scenario modelling, report generation and charts.
AI may be able to support and enhance traceability efforts ahead of the EUDR. Mondra uses AI within its hyper-modelling automated LCA technology, which is used to generate the 33,500 footprints of its models daily. It also lends critical ability when working with imperfect and incomplete data. The result is LCAs and full Digital Twins of every product’s unique supply chain.
Mondra is actively working on several traceability use cases including commodity sourcing, EUDR and water risk that lean into those Digital Twins as the skeletal framework to layer upon these new datasets.
Ensuring real impact rather than greenwashing is critical to making a tangible difference in sustainability actions like decarbonisation. “AI makes sustainability accessible, meaning more people are engaged and able to bring innovative thinking to the space,” said Mondra’s spokesperson.
AI enables faster and more thorough analysis, cutting the cycle time from idea to proven concept. “From there, AI enables faster scenario modelling to take the concept to action real change, reducing eco-impact and risk, all controlled to protect or improve commercial performance.”
