Historically, the most prolific creatives used varied strategies to generate their novel solutions. Generally, their processes took the same form; I've outlined this before, but in recap, idea generation consists of focusing incessantly on a single problem, forgetting about it in deep relaxation (often leading to an AHA! moment), then returning to the issue with a fresh perspective.
Creative Intelligence is an extension of that process; it is a concept innovated by Robert Sternberg in 1985 as part of his Triarchic Theory of Intelligence. In short, Creative Intelligence, also coined as Experiential Intelligence, involves intellectual flexibility and innovation in novel situations. This definition was reiterated by several marketers, such as Dr. Margaret J. King (The Center for Cultural Studies & Analysis), Zhen Tang (AI Law), and Jessica Bedenbaugh (Call It Moxie, Samaritan House), when asked "What is Creative Intelligence?"
Common themes from a couple dozen other answers include attuned intuition, transferring recently learned information to unique domains, and imaginative or innovative problem-solving (you can see all answers at the bottom of the article under sources). But above all, the most frequent response was that Creative Intelligence is an ability, a mindset, a potential to use information in a particular way.
That being said, there were some creative answers as well.
Jason Miczo of Good Vibe Designs said Creative Intelligence is to "be a continuous student of the world."
Chris Gadek of AdQuick said it's "a mixture of art and science."
David Morneau of inBeat called it a "combination of embracing uncertainty, being daring, and having adopted a 'test-and-learn' approach to problems."
Sidonie Smith, a Broadway Leading Lady, said "Creative Intelligence is just intelligence period. [It] doesn't need to be qualified."
While it may be true that Creative Intelligence is synonymous with all intelligence, for our purposes I'd like to distinguish it in a way that Chris and David hit on. Creative Intelligence is a mixture of art and science, an adoption of the 'test-and-learn' approach.
Today, science is our new religion. We turn to science to answer the big questions, collecting evidence to support our arguments. Through the scientific method, we humans have created beautiful structures, entire societies, and of course, artworks. Artists are now experimenters more than ever. They fail, fail, fail, and finally succeed, just to fail again a hundred times more. But the point is, the process of the artist is, at its core, the same as that of the scientists. There's background research, hypothesizing, experimenting, and analysis.
What's more, the combination of the processes results in even greater achievement. Consider what Google has made with their art experiments. Using AI, complex datasets, and a little free time, Googlers have built hundreds of digital art projects allowing users to experience art in brand new ways, as well as creating new data in the process. With a focus on what kind of people enjoy which type of experiences, Google can make more and more relevant art.
In the same way, Marpipe users build ads that get more and more relevant with each use, isolating groups of people by their willingness to view, click, sign up for, and purchase from different elements in varying ads. From those experiments, we gather information about the parts of an ad that are effective - the color, the model, the product, the facial expression, the tone of the copy. By viewing KPIs as votes, we can put together a picture of what works and what doesn't. That dataset, that information bank that includes details of words and images which are most likely to make someone engage with them, is what we would call creative data, or, more specifically, Creative Intelligence.
For an AI rendition of Creative Intelligence, check out GPT-3, OpenAIs ability to learn from any body of text and replicate works similar to it's training data set.