How Artificial Intelligence could change branded content

October 16th, 2017

There is a huge debate in the media at the moment about the implications of Artificial Intelligence (AI), Machine Learning and robots and whether their widespread use in the industry will destroy or create human jobs.

The optimists argue that technological change always does consign some occupations to history, but ushers in new ones too.

The pessimists believe that this time the pace of change will be so quick that there won’t be enough time for new roles to be created. It really is a case of time will tell.

What though of the media? Newspaper companies have been experimenting with Artificial Intelligence for several years years now. Simultaneously the big platforms like Google have been looking at how to generate interest in its AI innovations.

So what does this mean for journalists, and more broadly content creators who work with brands. Are their days numbered? I was recently at the FIPP Congress where a panel attempted to answer those questions.

Creating commoditised content

There may come a day when AI powered bots can successfully create think pieces reflecting the views of ‘composite commentators’ that might even reflect the personal biases of the reader, but not for now. Most of the innovation is using bots to create content in data heavy areas like sport or finance news. As Francesco Marconi, Manager strategy and development, Associated Press explained humans set up templates and the content (names of company figures and potentially standardised quotes from individuals), is then inserted by the bot in the appropriate places.

As Francesco argued the role of the bot is not to replace journalists, but rather to free up their time so they can focus on more creative work. As well as obviously creating scale for the media company.

“With automated content we can open new markets and better serve our client publishers with new forms of content. These are often in areas that we previously found difficult to scale. Automation of earnings reports, for example. We went from doing 300 companies to over 4000 stories, and were able to free up 20% of journalists’ time.”

Media companies aren’t just using AI to automatically create word based stories either – AI can also be harnessed for video content. Once again humans set up a template and then AI can be used to select appropriate words and images.

AI in social media

The opportunity for brands to use AI right now is in the lower rungs of content production with commoditised content that they can put out via social media. Bots might not just create the content too. They may also optimise the content to go out at different times, as well as power how an automatic message responder – whether they be one to one or one to many via comments – interacts with users.

In fact community management is clearly an area that social platforms are investing heavily in. At FIPP Alice Zimmermann – Global Product Partnerships, Google spoke of a project that does just that.

“We use AI to help technology to enhance media and make our professional lives and jobs easier. An example is Project Jigsaw which uses machine learning in different ways to protect freedom of speech online. We need to be able to participate in media in discussion boards etc without being subjected trolling and online abuse. We now have AI that can gauge the toxic impact the comments could have on a discussion, and thereby encourage a healthier culture in our media.”

As Francesco Marconi outlined, Associated Press has found another use AI – powering research into social media to isolate trends. “We also use augmentation to discover hidden insights. We used AI to analyse tweeted replies to Trump’s social media posts. By analysing the public discourse we were able to identify some key terms. We could see partisan bias when people are replying to tweets.”

For brands having this level of intelligent analysis of social media will be invaluable and it will play a core role in what is arguably going to be AI’s key role in branded content creation in the next few years – personalisation.

Essentially AI systems learn about individuals from what they read and how they respond to content, then deliver content that is most relevant to them. The way this has rolled out so far is often a mixture of encouraging readers to offer information – ticking boxes as to what they are interested in – and then using AI so spot their usage trends and fill the gaps. A classic example of how this works is the BBC’s MyBBC innovation. This is a receptacle of an individual’s data which is both implicitly and explicitly collected. In other words the individual makes choices to personalise the content but they are tracked too. They then serve recomendations on what is of interest to make the service more relevant. They can then use that data to create stories that are most relevant for individuals.

This quite clearly has huge potential for brands to meet the demands of their customers with appropriate content which may deepen brand relationships, or in the B2B sphere might move them a notch or two along the sales pipeline.

I think we are heading towards the tipping point with AI and brands. At the present time AI seems like an expensive investment (though Google for one is very keen to licence out its AI technology) and there’s evidence that not all brands are convinced of its merits. Next year though could see all that change as the cost of integrating AI systems falls and brands become more serious about personalising content.

Commissioned by The CMA

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