Is there a magic formula for brewing the perfect beer? If there is, then given the drink’s timeless popularity, whoever finds it is likely to be very successful. It’s a question that the world’s largest brewer is hoping to answer with the help of artificial intelligence (AI). 

AB InBev – producer of renowned brews including Budweiser, Stella Artois, and Corona – is building machine learning into key areas of its business, as it seeks to bring one of the world’s oldest industries into the digital age.

The company has invested in a raft of data-driven initiatives with the aim of improving everything from how it brews beer to how it manages its relationships with customers and markets its products to the public.

It began its steps towards digital transformation several years ago by establishing what it refers to as its Beer Garage – a Silicon Valley-based hub of innovation, where it researches, develops, and tests technology-driven solutions.

AB InBev’s global director of innovation, Andrew Green, spoke to me about the challenges involved with adding cutting-edge technology to the brew.

He tells me “The Beer Garage is our emerging technology office in Silicon Valley – as a company we’re super-committed to innovation, so placing people out here to be really in the forefront of what’s happening is very exciting for us. 

“It’s like we’re opening doors to the external ecosystem and inviting them in to collaborate and co-create with us.”

A key component of their Silicon Valley operations is the technology incubator, which is where several of the AI-powered initiatives currently being trialled or rolled out into production originated. But proximity to the larger tech companies of Mountain View, as well as being able to tap into the networks of the venture capitalists in the area, are all sources of opportunity and innovation.

Green explains, “We spend most of our time working with startups – early-stage companies as well as larger startups, and we learn a lot from working with them … it’s a really exciting way of working for us … these early-stage founders are super motivated and experts in their field, which is inspiring for us.”

The Beer Garage’s function is to sit between this startup ecosystem and the core AB InBev business, and discover ways that each can be of benefit to the other. These will generally be new concepts that can be quickly scaled up to the point where they can operate within one of its multinational operations.

How is AB InBev using AI right now?

Green talked me through three use cases across very different areas of the company’s business. The first is a system called SenseAI that uses machine learning to help brewers improve the quality and flavour of their products.

It involves using real-time analytics to measure data collected during the brewing process – from levels of CO2 used in the processes to the time dedicated to each different stage – to predict qualities of the end product.

Green says, “Supplying breweries is a big thing for us … so SenseAI was setting out to say, ‘we have all of this data, how can we utilise it to put the best product we possibly can into our consumers’ hands?”

Other data that is used includes results gathered from a grading process, where expert human beer tasters assess the taste of the algorithmically-informed brew.

At the moment this layer of human input is essential – no digital “tasting” system has yet been developed that is able to give as comprehensive and reliable assessment of the taste and quality of a finished beer, as an expert with a biological tongue and brain. But, “In the future, its totally possible we can put a more objective spin to that, as some of these things become more possible to do in a scalable way through technology, ” Green says.

A second use case involves using machine learning to build better and more sustainable relationships with customers – the distributors and outlets that sell its famous brands around the world.

Essentially it runs a risk analysis model meaning the company can more quickly assess customers to determine the amount of stock they will need and the amount of credit they can offer them.

“It’s a cool project that’s taken inspiration from the financial services and fintech that we see out here in Silicon Valley … we’re selling beer to retailers, but we’re also looking to help our retail partners and customers build their businesses too, ” Green says,

The ABCredit system lets the business identify the level of credit and payment terms that suit its relationship with an individual customer, by making more accurate individual assessments rather than having to use broader terms to consider the risks and opportunities.

Currently being piloted in Brazil, the company hopes the platform will eventually be rolled out globally – good news for beer fans who are more likely to find their favourite stores, restaurants, and bars well stocked when they drop by for a pint or two.

A third AI-driven initiative revolves around marketing and the increasingly popular concept of allowing machines to make creative decisions regarding the content of advertising and marketing materials.

Alehouse Creative allows advertising professionals across the country to feed in their creative briefs and receive real-time insights into how altering elements of their work could affect the impact it is likely to have.

It works by analysing the performance history of individual pieces of advertising material and imagery, to learn what works and what doesn’t when it comes to attracting customers through online marketing channels.

Green says, “At the touch of a button we’re able to create a new digital advert … when you think of all the work that goes into the manufacturing of different ads you see across platforms, including things like the required imagery and language, or putting the beer slightly to the left or the right might be the optimal way … we can now automate a lot of these processes which allows our creatives to spend their time doing creative stuff, rather than working on the hundredth iteration of a particular advert.”

This frees up creative staff to spend time looking for the most engaging imagery or telling the most compelling storey, bolstered by solid data on the impact it is likely to have when the advert is put to market.

AB InBev’s forays into artificial intelligence and technology-driven change are typical of those we’re seeing in market leaders across every industry. Their work highlights how smart, self-learning, and automated systems can be applied to any business problem to increase efficiency and improve the products they supply to their customers. 

Is there a magic formula for brewing the perfect beer? If there is, then given the drink’s timeless popularity, whoever finds it is likely to be very successful. It’s a question that the world’s largest brewer is hoping to answer with the help of artificial intelligence (AI). 

AB InBev – producer of renowned brews including Budweiser, Stella Artois, and Corona – is building machine learning into key areas of its business, as it seeks to bring one of the world’s oldest industries into the digital age.

The company has invested in a raft of data-driven initiatives with the aim of improving everything from how it brews beer to how it manages its relationships with customers and markets its products to the public.

It began its steps towards digital transformation several years ago by establishing what it refers to as its Beer Garage – a Silicon Valley-based hub of innovation, where it researches, develops, and tests technology-driven solutions.

AB InBev’s global director of innovation, Andrew Green, spoke to me about the challenges involved with adding cutting-edge technology to the brew.

He tells me “The Beer Garage is our emerging technology office in Silicon Valley – as a company we’re super-committed to innovation, so placing people out here to be really in the forefront of what’s happening is very exciting for us. 

“It’s like we’re opening doors to the external ecosystem and inviting them in to collaborate and co-create with us.”

A key component of their Silicon Valley operations is the technology incubator, which is where several of the AI-powered initiatives currently being trialled or rolled out into production originated. But proximity to the larger tech companies of Mountain View, as well as being able to tap into the networks of the venture capitalists in the area, are all sources of opportunity and innovation.

Green explains, “We spend most of our time working with startups – early-stage companies as well as larger startups, and we learn a lot from working with them … it’s a really exciting way of working for us … these early-stage founders are super motivated and experts in their field, which is inspiring for us.”

The Beer Garage’s function is to sit between this startup ecosystem and the core AB InBev business, and discover ways that each can be of benefit to the other. These will generally be new concepts that can be quickly scaled up to the point where they can operate within one of its multinational operations.

How is AB InBev using AI right now?

Green talked me through three use cases across very different areas of the company’s business. The first is a system called SenseAI that uses machine learning to help brewers improve the quality and flavour of their products.

It involves using real-time analytics to measure data collected during the brewing process – from levels of CO2 used in the processes to the time dedicated to each different stage – to predict qualities of the end product.

Green says, “Supplying breweries is a big thing for us … so SenseAI was setting out to say, ‘we have all of this data, how can we utilise it to put the best product we possibly can into our consumers’ hands?”

Other data that is used includes results gathered from a grading process, where expert human beer tasters assess the taste of the algorithmically-informed brew.

At the moment this layer of human input is essential – no digital “tasting” system has yet been developed that is able to give as comprehensive and reliable assessment of the taste and quality of a finished beer, as an expert with a biological tongue and brain. But, “In the future, its totally possible we can put a more objective spin to that, as some of these things become more possible to do in a scalable way through technology, ” Green says.

A second use case involves using machine learning to build better and more sustainable relationships with customers – the distributors and outlets that sell its famous brands around the world.

Essentially it runs a risk analysis model meaning the company can more quickly assess customers to determine the amount of stock they will need and the amount of credit they can offer them.

“It’s a cool project that’s taken inspiration from the financial services and fintech that we see out here in Silicon Valley … we’re selling beer to retailers, but we’re also looking to help our retail partners and customers build their businesses too, ” Green says,

The ABCredit system lets the business identify the level of credit and payment terms that suit its relationship with an individual customer, by making more accurate individual assessments rather than having to use broader terms to consider the risks and opportunities.

Currently being piloted in Brazil, the company hopes the platform will eventually be rolled out globally – good news for beer fans who are more likely to find their favourite stores, restaurants, and bars well stocked when they drop by for a pint or two.

A third AI-driven initiative revolves around marketing and the increasingly popular concept of allowing machines to make creative decisions regarding the content of advertising and marketing materials.

Alehouse Creative allows advertising professionals across the country to feed in their creative briefs and receive real-time insights into how altering elements of their work could affect the impact it is likely to have.

It works by analysing the performance history of individual pieces of advertising material and imagery, to learn what works and what doesn’t when it comes to attracting customers through online marketing channels.

Green says, “At the touch of a button we’re able to create a new digital advert … when you think of all the work that goes into the manufacturing of different ads you see across platforms, including things like the required imagery and language, or putting the beer slightly to the left or the right might be the optimal way … we can now automate a lot of these processes which allows our creatives to spend their time doing creative stuff, rather than working on the hundredth iteration of a particular advert.”

This frees up creative staff to spend time looking for the most engaging imagery or telling the most compelling storey, bolstered by solid data on the impact it is likely to have when the advert is put to market.

AB InBev’s forays into artificial intelligence and technology-driven change are typical of those we’re seeing in market leaders across every industry. Their work highlights how smart, self-learning, and automated systems can be applied to any business problem to increase efficiency and improve the products they supply to their customers.