Artificial intelligence (AI) and machine learning (ML) have huge potential to drive a new generation of creative brand experiences. They are at the forefront of a powerful shift that will bring brands closer to consumer expectations, passions and emotions. Assistive and smart technologies are catching up and we’re already facing a new world of possibilities.

AI and ML can be applied in many ways. The use of machine learning to power business decisions and product recommendations is becoming widespread. We experience it when we buy on Amazon, watch television on Netflix, hail an Uber or tag friends on Facebook. There are more creative experiments out there such as “The Next Rembrandt app”, “machine music composition” and “TV show script generation” that use ML to create new art (with mixed results). While AI is poised to transform our industries and technologies, just like electricity did in the mid-twentieth century, AI has the potential to change art, creativity and the way brands and agencies create the next generation of experiences.

It’s easy to hear all the buzz and think of AI and ML as new or recent developments, but they have a long history. AI has been researched since the dawn of computing but in the past few years it has become more powerful, flexible and accessible. This is down to heavy investment from companies like Intel, Google, Apple and Facebook, leading to faster, cheaper hardware with better algorithms.

The key to a successful machine-assisted experience is data. Converting big data into useful data is a difficult challenge. This is where agencies and brands have a huge opportunity. Netflix has been successful in making sense of consumer data, to the point that it now knows which shows and casts will become hits, before they have even been filmed.

One big issue is that most of the data being captured isn’t smart. Often, it doesn’t reflect consumer interests and takes a lot of analysis (and sometimes plain guesswork) to come up with insights that drive strategy and creativity. Traditional web and mobile analytics don’t work as expected in a hyper-connected world. Demographics, page views, page clicks and hashtags are falling short in their exposure of true consumer learnings. Lifestyle, sentiment and engagement are the key elements to go after. Spotify has done this in innovative ways, marrying user habits like playlist creation with crowd-sourced behaviours to create personalised playlist suggestions.

Brands want to understand how people feel about their services, products and content. So far, though, it seems we only have a partial view of consumers, not the full picture we aspire to. This is exactly where a new wave of interfaces will move the industry forward, away from a straight broadcast out with frivolous two-way interactions towards a more natural dialogue between brands and people.

With the rise of new interfaces and interactions such as 1:1 messaging, voice-enabled services and natural language processing, we have a chance to reach a deeper understanding of consumers. Combine this with the constant growth of connected devices, and the opportunity to capture smart data from consumer interactions becomes huge.

Data is the fuel of AI. According to Internet Live Stats, there are roughly 3.5 billion people with access to the internet, generating exponential amounts of data. And IDC believes we ll be creating 44 zettabytes of data worldwide by 2020. This data will become increasingly smarter, thanks to two main factors. First, more connected devices means we’ll need a more holistic view of consumer lifestyles. And second, the rise of messaging and conversational platforms such as WeChat, Line, Slack and Facebook will provide a stream of dialogue-based data. This will result in a new wave of smart data, empowering our industry to understand people on a whole new level.

AI lets us understand complex interactions such as voice, text dialogues, pictures and videos in a more personalised way. Now we can classify interactions from consumers, and smart solutions can understand what a person is saying. When we recognise the intention and the sentiment of a human interaction, we can react to it accordingly. Is that person happy or frustrated about the service? Was the content delightful or bland? This is the kind of qualitative understanding that we can’t get through page views or clicks. Jay Zasa, also of R/GA, wrote a great piece, recently, about the challenge of creating meaningful bots and conversational services.

Most importantly, machines can learn much quicker than humans. They constantly develop and improve over time, testing response, intent and sentiment to enhance the service on offer. They can solve the scalability problem, which has blocked truly personalised services for so long. Why would you go to a website and waste time searching for something if you could have a smart, machine-assisted personal service giving you what you need at the right time and place, on the right device or channel? After all, the ultimate goal is to create the simplest, most meaningful experience for consumers.

Machines are not about to take over the world and lead the creative sphere, but if we want to create better, simpler, more personal experiences, it’s clear that AI technology must play a chief role in the research and design of brand experiences. AI could become the ultimate creative tool for brands and agencies, helping them build richer experiences with lasting value.

There’s a unique element of creativity in all of us that machines are unlikely to replicate (at least for the time being). However, the landscape is moving towards a smarter, hyper-connected, ongoing dialogue between people and brands. Things are evolving fast and our industry can’t afford to hesitate. We need to use cognitive technology in new ways to boldly break the mould, creating experiences that aren’t one-off executions. Instead, they’ll be constantly improving and growing the brand-consumer relationship.

Anthony Baker is tech director at R/GA London

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