Leveraging AI Capabilities for Innovating Brand Storytelling

by February 15, 2020 0 comments

AI

According to recent research by IDC, the total global spending on Artificial Intelligence (AI) systems will touch US$98 billion by 2023. Nearly 61% of marketers also say that AI is the most important aspect of their data strategy. This impact can be felt directly in the marketing communication of brands, helping them understand their key consumers while tailoring their offerings and messaging accordingly. There is a new intelligence in people’s midst; chatbots, recommendation engines, algorithms, language processing, etc., are just the tip of the iceberg. AI is helping brands create engaging stories and campaigns.

For example, in late July of 2019, JPMorgan Chase, the largest bank in the United States, picked an artificial intelligence (AI) algorithm over human beings to write a portion of its ad copy.

After experiments with synthetic storytelling brought a 450 percent lift in ad click-through rates (compared to 50 to 200% through other means), the bank inked a five-year deal with Persado to use its AI engine for direct-response emails and online display ads.

JPMorgan Chase Chief Marketing Officer Kristin Lemkau said in a statement, “Persado’s technology is incredibly promising. It rewrote copy and headlines that a marketer, using subjective judgment and their experience, likely wouldn’t have. And they worked. We think this is just the beginning.”

However, this is not the first time AI has been implemented for ideation and actual storytelling, and it certainly won’t be the last. Although AI arguably still has a long way to go before it can equal or exceed the human level, yet its algorithms can already automate more basic or repeatable tasks to accelerate creative processes.

Adobe CTO Abhay Parasnis told Forbes last spring, “There are a lot of practitioners who would rather not waste their time in drudgery doing repetitive tasks. AI can take those out of their lives and inspire them to focus on the more creative, storytelling, high-level activities they would rather spend time on.”

When it comes to marketing, AI undeniably contributes to creative storytelling by uncovering and aggregating structured and unstructured data from multiple channels and looking for patterns. With AI, creative teams can produce content in mere days, or even hours, that would otherwise take months, by eliminating the all-too-common grunt work bogging down design teams.

Various new AI-enabled tools and their features are automating previously tedious work processes so that almost anyone — whether they’re an experienced or novice creator — can get involved in motion design, animation, and special effects (whereas those fields were once reserved for individuals who knew how to code and animate and had some grounding in visual and design techniques). In the near future, AI will enable more professionals to jump into the game and rapidly create and circulate powerful, compelling, and memorable brand stories that matter.

Moreover, AI will enable computers to look, listen, and learn from what a designer is trying to do and make recommendations along the way. As designers assemble their creative stories, they’ll have options presented in their moments of need. In a sense, the designer will become a curator and the computer will serve as a creative assistant, proposing ideas. In that way, designers won’t have to hunt for the right brush, color, shape, or font based on their past activities and those of other designers. Machine-learning algorithms will help them zero in on the most likely options, saving time so their brains can stay in creative or strategic (rather than tactical) mode.

While that technology will invariably show up in tools like Creative Cloud, it may not be as apparent as it is today. In the future, some industry observers think AI will be invisible. It will be ambient. It will basically serve as a mostly silent assistant enabling its human counterparts to ideate, experiment, and create.

For data-driven design in the future, AI and machine learning will help designers become more contextually aware and serve up capabilities based on the task of the moment. As the technology progresses, design tools might enable users to change the style of an object from, say, modern classical to look like a Vincent van Gogh painting. Or an artist working with maple leaves may decide they’d look better as oak leaves and ask the program to make that adjustment. With AI and its ability to refer to and utilize mass treasure troves of data, almost anything will be possible.

It is expected that in the future, as AI becomes more integrated with design tools and is enhanced by capabilities like natural language processing (NLP), it may also be possible to simply utter a few commands and have elements of that creation change in seconds. These NLP-enabled assistants will be subtly integrated into applications, only serving up suggestions that make sense at the moment and facilitating — rather than obstructing — creative processes.

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