The use of artificial intelligence (AI) in the creative industries is growing at an unprecedented rate. It’s already telling us what to watch on Netflix, what to listen to on Spotify, what to order on Uber Eats and what to buy on Amazon.
But it’s potential to influence our lives goes way beyond recommendations on a streaming service, app or website. It’s now being used to push the boundaries of what we previously thought possible in fashion, art, music, film, and gaming as leaders in the creative industries pivot away from the traditional confines of human thought to embrace AI, automation and machine learning.
All about the image
The creative industries are often thought of as being ‘cool’. They’re forward-thinking, progressive and inspiring. They’re seen as having their own cultures and identities, which successful brands have forged over many years and will fight to protect, while job roles are commonly characterized by their emphasis on innovation, creativity, and vision.
It would be easy to assume, therefore, that AI, automation, and data has no place in such an unpredictable, trend-driven market. But the creative industries have been central to technological advancement for centuries. From television, photography and fashion to advertising, computer games and music, those working in the creative industries have the power to inspire people with their inventions – and AI has the power to make it happen smarter.
With the latest tools at an employee’s fingertips, and the right data being used, brands are now creating machines capable of understanding content as well as humans. They can accurately predict a customer’s buying habits, determine their product preferences, and help develop ideas into fully-fledged campaigns. And they can do it quicker, more efficiently and with less margin for error.
So, what’s the catch?
Machine versus human: Who wore it better?
The technology already exists, but the challenge centres on how it is used.
How can AI – a tool that thrives on numbers and algorithms – learn to reflect your brand’s creative tone and image? How can it learn to tell a customer what two clothing products match? Or album to listen to next?
Getting it right hinges on your data, and how this is used to deliver two key things – hyper-personalized customer experience and augmented employee intelligence.
That’s according to Anca Marola, who is the Chief Data Officer of the Louis Vuitton Moet Hennessey (LVMH) Group. She delivered a fascinating keynote address on data transformation in the creative industries at GDS’ recent Data and Analytics Summit, which was attended by hundreds of thought-leaders from across Europe, the US and other parts of the world.
She said the integration of AI has accelerated over the past few years, but so too has the customer’s resilience to targeted messages or advertisements. With creative industries in mind, Anca said the onus is on brands focus on the quality of their communication – not the quantity.
“We are faced with an attention crisis,” she told attendees.
“As consumers, we feel it every day – there are mind-blowing statistics that show there are more than 300 billion emails being sent every day when there are maybe only five billion people with internet access.”
“We’re being bombarded every day with a lot of advertising and communications and there’s some statistics that say we see up to 10,000 advertisements per day per person.”
“The consumer has developed a sort of blindness so it’s absolutely crucial – not just preferrable – that we replace quantity with quality.”
“And that quality can come from data and AI – by talking less and instead talking at a better time.”
LVMH Group in numbers:
- 6 divisions, covering fashion, wines and spirits, beauty, watches and jewellery, selective retailing and hotels and press
- 75 houses
- €64bn revenue in 2021
Trends, taste and yellow socks
Key to all of this is an understand that AI cannot simply be used to replicate previous trends or past behaviour. For Anca and her colleagues at LVMH, it’s about stimulating something new and creating styles of the future.
“How can the merchandizers, the people we consider having the taste, work with a machine to teach taste to a machine?” She asked.
“It’s about giving feedback to the algorithm, something that evolves with the taste of our merchandizers. I think it’s also important to have that big picture recommendation. For example, at LVMH, we want to have that full look that is a consistent and tasteful match as a whole – each product must go together. You don’t want to mix yellow socks with crocodile or panther print!”
“It’s also about the journey. When we’re first starting, it’s easy to do the targeting, personalization scenarios but as we get more sophisticated, we must take that helicopter view to prioritize that full journey of a customer.”
An element of surprise is also important, to keep customers on their toes.
“We get feedback from our customers in our consumer studies that tell us oh, everything is so automated nowadays, it doesn’t leave me space to be spontaneous. That’s because they get the pre-emptive contact at the right time, but it doesn’t leave any space for them to just drop into the store unannounced.”
“It’s important to leave that space in our strategies, but it’s also important from an AI perspective. How do you incentivize the AI to not just optimize for the short-term but also optimize for that longer-term engagement?”
“Focus on surprise engagement and not just sales because long-term, that’s what builds our brand’s relationships and consumer delight.”
AI techniques, from machine learning to pattern recognition, have already proved effective in various industries. Healthcare, finance, and retail are just a few that are already reaping the benefits of advanced cognition capabilities – while the creative industries continue to explore and experiment with the possibilities.
It may never replace the human soul of creativity – and nor should it – but AI can certainly serve as a smart, efficient, and inspirational assistant.
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