AI as a Creation Engine

AI is poised to have an increasing influence on the way companies create new content, paving the way for new forms of humanmachine collaboration.

AI is maturing at varying rates around the world, with some organisations using these technologies—including machine learning, deep learning, natural language processing, and computer vision— to support external and internal organisational capabilities. For media and entertainment companies and other content producers in particular, AI may also offer a startling range of possibilities for the creative process, enabling individuals and businesses to generate new content with minimised human input.

In a global analysis based on Deloitte’s most recent State of AI in the Enterprise survey, early adopters were asked to identify the primary benefits of implementing AI in their organisations. Respondents say using AI to enhance existing products and services is their most sought-after externally focused benefit, with 43% ranking it in their top three, while 31% prioritise using it to optimise external processes. The top internally focused benefit, meanwhile, is optimising business operations, with 41% placing it among their top three choices, followed by using AI to make better decisions, cited by 34% of respondents.

In the current wave of AI adoption, then, organisations seem largely focused on using the technologies to improve what they already have as opposed to creating something new. However, new applications are continually cropping up, indicating that AI implementations may be expanding beyond enhancement and optimisation. In the same survey, 28% of respondents indicate they want to use AI to create new products, while 27% want to use the technologies to pursue new marketplace opportunities.

Indeed, over the past few years, a growing number of attempts to advance AI’s capabilities have garnered public curiosity and media attention, and many such pursuits have been creatively inclined. For example, in 2016, IBM Watson created the first film trailer to be generated by AI by training on 100 existing horror movie trailers. In the art world, some organisations, including the Art and Artificial Intelligence Laboratory at Rutgers University in the US are exploring the use of AI algorithms to generate new artworks. AI is even being used to create music: OpenAI’s MuseNet is an AI-powered tool that can generate songs with multiple instruments and in various styles. This tool joins a growing number of music-generating services, startups, and artists leveraging AI in their work. AI has also been used in journalism, poetry, sports, video game development, culinary arts, and other creative pursuits.

These developments are certainly exciting, but before organisations can move AI content creation to the main stage, there are likely several challenges to address. First, for something to be truly creative in a business context, it should be both novel and useful. It is one thing to have an AI-powered system create something just because it can; it is another for that creation to be widely used and valued. Second, appreciation of content is subjective, relying on the preferences, emotions, and experiences of consumers; it is important that organisations using AI to generate content continue to make an emotional connection with their customers. Finally, there are intellectual property and content ownership questions pertaining to AI-generated content. Current regulations vary from country to country, and these frameworks will likely be tested in the future. ***

Media and entertainment companies and other content-intensive organisations currently using AI to enhance their existing operations are well served to consider experimenting with these burgeoning technologies to power new customer-facing creative pursuits. Risk management and technology security executives can work along side IT and marketing teams at these organisations to develop strategies for AI adoption and usage that break new ground in human-machine collaboration.