Our food system is in the middle of a major transformation due to factors such as a growing population and climate change, while affordability has become more important than ever for people around the world.
Additionally, food ideologies are rapidly evolving, becoming more diverse and gaining traction for a larger part of the population.
As a global food company with products reaching billions of people around the world, we aim to work faster and more efficiently, while ensuring that our solutions are adapted to the local context and individual needs.
With food systems under pressure, we must find ways to manage tradeoffs between taste, nutrition, sustainability, and affordability.
This is where Artificial Intelligence (AI) and data science comes in.
They complement our R&D capabilities by helping us effectively handle these steadily increasing complexities, as well as improving the effectiveness and efficiency of our innovation process.
For example, tools such as chatbots can improve productivity and the innovation process by performing a variety of tasks, creating personalized content, and identifying solutions to complex problems.
At Nestlé, we identify digital opportunities across our global R&D organization to leverage AI, machine learning, data science and predictive analytics. This helps us connect the dots quicker, gain valuable insights and continue to deliver novel discoveries today and for generations to come.
Here are some key examples from across our global R&D organization:
Accelerating trend-based innovation
People’s needs and preferences are rapidly evolving, and this has led to novel trends and food ideologies, that are amplified by social media.
This, coupled with the use of connected devices and e-commerce, has resulted in an abundance of insights that we can leverage to drive innovation.
Today, the first generation of AI tools that gather social media insights based on advanced algorithms already exist to support innovators in identifying novel concepts.
We use AI to help us analyze information on trends, ingredients, flavors, and health benefits from social media, online publications, and other web sources.
Our innovators cluster the captured insights, which leads us to discover new ideas or trends that can be quickly translated into compelling product innovations.
For example, using these tools, we launched Nescafé Dalgona coffee mixes and Nesvita plant probiotic supplements for adults in China.
To accelerate our innovation process, we are piloting tools that help us create virtual product prototypes and quickly test them using virtual reality, including in the metaverse and Web3 spaces.
While creating and testing physical prototypes remains key, virtual capabilities help our product developers quickly see if they’ve hit the mark with a new product, saving time, effort, and materials.
For example, using virtual reality during the innovation process, we can test how consumers or retail customers interact with new concepts for coffee systems.
Beyond this, we also use AI in other key areas such as better predicting the sensory properties of exciting coffee innovations. Think of an ‘electronic tongue’ for coffee tasting!
Delivering personalized experiences and services
AI and virtual reality are increasingly becoming an integral part of consumer-facing experiences and services.
Soon vending and beverage machines will incorporate holographic operators that interact with people in multiple languages, while creating a personalized experience based on each individual’s taste preferences.
We already deliver personalized products and solutions for people and pets.
Using home test kits, consumers can share physiological data to receive recommendations for personalized nutritional supplements targeted to specific health conditions.
Together with the Crohn’s & Colitis Foundation, we developed a free web-based digital tool that makes preparing tasty and gut-friendly recipes easier than ever before.
Developed by our researchers who leveraged Nestlé’s expertise in digital health and nutritional science, the platform uses a machine-learning algorithm and nutrition data to generate personalized meal plans.
In petcare, we’re developing a holistic product ecosystem to help improve cat health by tracking changes in unique health and behavioral data patterns, while providing tailored recommendations to pet owners.
The ecosystem includes a Petivity Smart Litterbox where pet owners can track changes in urination, defecation, and weight patterns for indoor cats.
Using this data together with proprietary algorithms, the ecosystem can identify an increased risk of developing conditions such as kidney disease, urinary tract infections, and obesity.
Using a mobile app, our proprietary AI shares this information and provides expert advice to pet owners, including recommendations for veterinarian visits when relevant.
Leveraging historic clinical trial data for new discoveries
In the last 20 years, we’ve conducted over 300 clinical trials to support the health benefits of our products.
This has led to a wealth of clinical data. Today, through advanced data analytics, we’re further maximizing the return on investment from this data, by pulling together data from many different types of clinical studies, as well as recently published external studies.
By combining and comparing the data sets, we can discover new relationships between different physiological, behavioral and health indicators, and translate this information into novel nutritional solutions for specific populations.
Take, for example, our research on breastmilk. Here, our data scientists consolidated more than 2 million data points from 25 different clinical studies.
Using advanced data mining, we made important new discoveries that led to the development of an infant formula with human milk oligosaccharides (HMOs) tailored to the specific needs of C-section born babies.
Data science to support the transition to a regenerative food system
With around 30% of global greenhouse gas emissions that are linked to food and agriculture, and as we transition to a regenerative food system, we need to ensure food security.
Data-based precision farming and artificial intelligence can play a key role in facilitating this transformation.
Real-time monitoring of weather conditions as well as water and nutrient needs, for example, can reduce fertilizer use and optimize crop production.
Further development of satellite-based data systems, drones and field data can also be used to collect and better monitor regenerative practices on farms.
Our recently created Nestlé Institute of Agricultural Sciences is exploring the use of artificial intelligence and data science to accelerate the translation of agricultural science into solutions that enable farmers to improve the environmental footprint of ingredients we source.
One key area is the application of AI to classical plant breeding to, for example, help select and identify high-yielding, drought-and diseaseresistant coffee plant varieties.
AI and data science-driven innovation has transformative power. By embracing it, I believe that we’ll continue to deliver relevant and highly differentiated innovations, with agility, and faster than ever, while contributing to the positive transformation of food systems.
0In this process, of course, we must strive to ensure data protection and consumer confidentiality.
Finally, I want to stress that artificial intelligence or machine learning does not replace natural or human intelligence in Nestlé.
It’s about assisting our R&D teams in their work – enabling them to make informed decisions, data-based discoveries and manage difficult trade-offs in a complex innovation environment.