The latest news, trends, analysis, interviews and podcasts from the global food and beverage industry

The race to create sustainable, healthier and more exciting food has never been tougher – but artificial intelligence (AI) could be changing the game. From mapping taste and texture to predicting consumer preferences, AI is giving R&D teams supercharged creativity and efficiency. NotCo’s Alisia Heath reveals how tech-powered innovation is redefining what’s possible in the lab.

The food and beverage industry is under pressure to do more with less; create sustainable products, meet evolving consumer expectations and deliver innovation faster than ever. At the centre of this transformation is artificial intelligence (AI), which is helping R&D teams overcome long-standing bottlenecks and unlock faster, smarter product development to accelerate innovation and renovation.

Today’s food scientists are turning to AI to meet challenges around sustainability, supply chain agility, health and wellness and innovation efficiency. Companies like NotCo, with its Giuseppe AI program, are showing what’s possible when AI becomes a core part of the R&D process.

Meeting today’s R&D challenges

R&D teams face an unprecedented level of complexity. They must navigate:

• Sustainability: Growing pressure to reduce emissions, minimise waste and optimise resource usage.

  
  

• Supply chain interruptions: Global disruptions, from geopolitical conflict to climate change, impact ingredient availability and cost, requiring more flexible and adaptive formulations. Recent examples that have made headlines are cocoa, coffee and eggs, but there are many more that R&D teams are managing on a daily basis.

  
  

• Regulatory pressures and tariffs: Constantly evolving food labelling, nutritional standards and import/export policies demand agile, responsive development practices.

  
  

• Consumer preferences: Today's shoppers expect clean labels, reduced sugar and functional benefits, without compromising taste.

  
  

• Health and wellness: The rise of personalised nutrition is pushing food and beverage brands to develop products that support both physical and mental wellbeing.

  
  

• 'Fewer, bigger, better' innovations: To reduce risk, many companies are prioritising high-impact launches with clear consumer demand over incremental releases.

Together, these pressures are fuelling the need for faster and more agile innovation. That is where AI can be transformative.

How AI transforms formulation

AI platforms are redefining how R&D scientists and food developers improve product formulations by digitising and optimising the entire development process. Here's how:

Defining the target

It starts with a clear target; a product to match or surpass. This could be a dairy cheese, legacy snack or nostalgic treat. The target might focus on taste, texture, nutrition, cost, sustainability or all the above.

Mapping the target digitally

The AI model captures the product's profile, incorporating analytical data (like pH and viscosity), sensory attributes (such as creaminess or crunch) and consumer-relevant factors (like allergen status or clean label compliance). Food scientists identify key inputs and objectives, translating subjective attributes into structured, measurable data that the AI can use.

Exploring ingredient possibilities

AI systems scan ingredient databases, scientific literature and previous formulation outcomes to suggest viable combinations. This allows R&D teams to uncover unconventional ingredients and processes they might not have considered, helping eliminate bias and expand the innovation landscape.

Optimising and iterating

AI generates formulation candidates that are then evaluated for performance, using both analytical metrics (eg. rheology, colour, stability) and sensory evaluations (eg. descriptive analysis or qualitative consumer feedback). The insights feed into rapid iteration cycles, significantly accelerating time to formulation.

This process doesn't replace food scientists; it enhances their ability to move faster, test smarter and focus their time where it matters most.

Meeting and shaping consumer demand with AI

AI’s value doesn’t end with product formulation. It also helps R&D and marketing teams better understand what consumers want, accelerate time to market, and learn how to deliver it. With access to vast data sets like reviews and social media chatter, AI can:

• Model claims and preferences: Predict which claims ('no added sugar,' 'high protein') resonate with key demographics.

  
  

• Generate winning concepts: Develop product ideas based on emerging trends and historical performance.

  
  

• Reduce developer bias: Surface new formats or ingredients that might be overlooked through traditional development.

With the industry's shift toward fewer but more meaningful launches, AI gives R&D leaders greater confidence that they're investing in concepts with strong consumer pull.

Agile innovation in an age of economic constraint

The economic landscape is forcing every function, including R&D, to become more efficient and strategic. Volatile raw material pricing, inflation and labour costs all demand a smarter approach to innovation. AI helps R&D teams:

• Make earlier go/no-go decisions to improve ROI

• Predict the likelihood of success before entering costly development cycles

• Respond quickly to ingredient shortages or regulatory shifts via AI-powered reformulation.

In short, AI enables R&D teams to do more with less, without sacrificing creativity or quality.

Looking ahead: Where AI in food R&D is going

While still early in adoption, AI in food and beverage is evolving quickly. Future possibilities include:

• Closed-loop systems that combine AI and robotics for automated benchtop testing

• Real-time consumer co-creation tools using AI and AR/VR interfaces

• Precision fermentation and biotech integration guided by AI modelling

What's clear is that AI won't replace food scientists; it will empower them. It will remove trial and error guesswork, eliminate bottlenecks and free up time for deeper creativity and scientific exploration.

The next wave of food innovation will be led by teams that merge human expertise with digital intelligence. With AI as a partner, R&D is better equipped to deliver the sustainable, high-performing products today's market demands.