The role of AI in creative industries
Artificial Intelligence (AI) has fast grown to prominence in recent years across the technology sector. Accenture expects the innovation to double the annual economic growth rates of 12 of the largest developed countries by 2035. It’s potential has in some sectors been overhyped, but in my view, it is set to play a crucial role in creative disciplines.
To the uninitiated, AI is most commonly associated with robotics and complex digital analytics platforms. Creative disciplines are not usually the first things that come to mind when most think of AI. However, in my view, the technology’s rise has been paved in the creative sector by that of data-driven marketing and business intelligence.
The use of data-driven marketing and business intelligence has widely become the norm across a multitude of industries, sectors. The role data plays particularly in marketing has evolved from that of a supporting role to a driver of intelligent decision making and targeting.
A core challenge with introducing AI into creative disciplines is that like any technology, it lacks emotion; as a result, creatives for whom invoking and understanding emotion is a core part of their role, are likely to be skeptical. Empathy is a distinctly human character trait and essential to producing good work that engages markets. However, we are not talking about a creative designer being replaced by a robot, simply aided by AI-driven automation technology.
Understandably, the experiences we’ve seen in industries such as manufacturing from the growth in automation has made the said word a somewhat loaded term. The transformational impact technology has made across the board has meant whenever anything is introduced that alters or lowers human input or simply automates something new, concern around jobs is leveled. That being said, intelligent robots and AI solutions are their most helpful when used to support human processes rather than take them over – a key point for creatives to note.
Arguably AI has to date had a bad reputation in some areas. We saw just recently at Facebook the complexities involved in applying this technology. Facebook’s own AI robots were shut down because their iterative mutual communications led to what some called a ‘secret language’ – cuing Frankenstein and Alien vs. Predator memes to appear from the more hysterical usual suspects across the internet.
For marketers though, it is in prevention technologies where AI is currently adding the greatest value. Ad-fraud detection, for example, is already a space using AI to guarantee ad-spend is delivering its desired outcomes. AI helps systems to automatically learn and predict occurrences of fraud, enabling brands to act appropriately to reduce its impact. The same technology is also being widely applied in search marketing and programmatic advertising as a means to detect opportunities and provide insight into positioning.
Google, in particular, has carried out many experiments with AI, showing off its computers ability to caption images. The technology giant has even experimented with creativity by encouraging its computers to dream of unusual ideas such as animals in clouds. Of course, fully fledged automated design is a long way off, however Google’s attempts highlight the potential value AI could provide to creatives – an ability to suggest ideas and support design and ideas development process.
Automating parts of creative work can enable teams to dedicate more time to more complex and time heavy tasks, dramatically improving process management and staff resourcing as a result. In recent months we’ve seen AI used widely as a means to suggest new ideas and develop simple work such as basic ad templates that would typically be seen as menial content curation by expert design teams. IBM Watson has shown how sentiment can be measured from email subject lines and plotted against open rates. Introducing an element of automation into the production of the most basic ads such as those that are continually updated or require little editing, can help brands and agencies to avoid deskilling teams, and maintain their focus on delivering more complex work.
Can AI make a real difference to the creative process?
AI isn’t completely new thought to creative and marketing disciplines. We’ve seen it used in predictive marketing for a number of years now. The technology can be particularly valuable in evaluating and identifying opportunities and messages. Predictive marketers use complex data engines to better target communications based on knowledge and predictions on customer behaviour patterns.
Applying this technology and level of insight to creative designers, in particular, should, therefore, be a relative no-brainer. Being able to recognise and react to patterns in data such as items like click-through rate, and connecting these to ideas that work can provide significant value to creative processes. Particularly in an environment where we’re seeing creative budgets squeezed, being able to provide a traceable and clear data-based reason for work and spend can provide significant value to design processes.
In short, the future role of AI in creative is not to do too much creative work at all, but to provide the guidance and intelligence required to deliver the best possible results and make people better at their jobs. The work that experts will refer to as simple and mundane in any industry is often likely to see AI take over and automate.
Future technology transformation is largely about upskilling and enabling rather than taking jobs. The wide introduction of AI must be viewed in all industries as an opportunity to grow and upskill existing staff. With that in mind, in creativity AI should improve and dramatically aid creativity rather than make it robotic as critics might suggest.
AI has the potential to make a real difference to creative processes. Ultimately the more easily brands and agencies can identify value, the more likely creative ideas and design will achieve their desired results. From perfecting ads right the way through to improving targeting, I’m keen to see greater integration of AI into process management across advertising, marketing and associated industries. According to research by Accenture, Chief Marketing Officers are the most likely C-Suite member to be fired when things go wrong, making it even more critical that their departments and areas of influence are able to fully demonstrate value.
Robert Berkeley, President of Express KCS
(Note: This article was initially published in ITProPortal.)
Main Image Credit: PHOTOCREO Michal Bednarek / Shutterstock