When the concept artist and illustrator RJ Palmer first witnessed the fine-tuned photorealism of compositions produced by the AI image generator Dall-E 2, his feeling was one of unease. The tool, released by the AI research company OpenAI, showed a marked improvement on 2021's Dall-E, and was quickly followed by rivals such as Stable Diffusion and Midjourney. Type in any surreal prompt, from Kermit the frog in the style of Edvard Munch, to Gollum from The Lord of the Rings feasting on a slice of watermelon, and these tools will return a startlingly accurate depiction moments later. Cosmopolitan trumpeted the world's first AI-generated magazine cover, and technology investors fell over themselves to wave in the new era of "generative AI". The image-generation capabilities have already spread to video, with the release of Google's Imagen Video and Meta's Make-A-Video.

For so many of us, artificial intelligence (AI) is a completely intangible thing – often drawing us in towards the realm of science fiction. In a professional sense, it is hard to see yet filters into our everyday lives. For us marketers, its lack of visibility can leave us struggling to fully get to grips with what is means for our business decisions. So, when I saw that the Barbican Centre in London had curated an exhibition on artificial intelligence, AI: more than human, I was keen to go along and immerse myself in the experience. In spite of the fact it isn't specifically about AI in the workplace, I thought, whilst getting up close and personal with its history as well as some of the latest technology, there might be transferrable ideas and concepts that would inspire and give me a better grasp of what it offers.

Science and art intermingle as artist Anna Ridler's work displays digital tulips and drawings made by specially modified algorithms in the Robert L. Ringel Gallery in Stewart Center. Ridler's art collects data and generates data sets to create unique narratives, according to information displayed in the gallery. One side of the gallery displays blooming digital tulips created through artificial intelligence. For one of her pieces, she created "Bloemenveiling," a website to auction her digital tulips. Reflecting the Tulip Mania of 17-century Holland, Ridler's auction serves as a digital representation of the interaction between humans, technology and economic markets.

Artificial intelligence is spreading through our lives. As it moves from new feeds to productivity tools, the boundary between what is human-made and machine-made is becoming almost invisible, resulting in vast shifts in how we perceive and interact with the world. AI has surprised us with how it can move, see and hear, but also, with what it can create. Once thought of as a solely human trait, creativity is now a debated topic. Or is a thought process constrained by what us humans define it as? In 2016, Google DeepMind's AlphaGo system trounced the world's reigning champion, Lee Sedol at Go – an ancient Chinese game – by using its creative intelligence to devise a winning strategy.

Reaching a fever-pitch in the 1630s, "tulipmania" -- a Dutch Golden Age obsession with the rare and exotic flowers responsible, supposedly, for driving overzealous buyers to financial ruin -- has long been considered the first economic bubble. The tulip craze served as a convenient analogy for stories of our desire to monetize the natural world and our tendency towards speculative absurdity. While the extent of this botanical craze has been vastly exaggerated in books, blockbuster movies, and principles in economics, the idea that flowers might control markets continues to captivate social scientists as well as artists. In her latest work, London-based artist Anna Ridler brings this historic phenomenon into the future, using AI to produce thousands of invented "impossible" tulips, slowly developing the features that early modern collectors considered valuable -- their unpredictable stripes and stipples -- along with the price of bitcoin. Ridler's video installation, "Mosaic Virus," is named for the plant virus that creates the strange variations in color that catapulted the price of some tulips far beyond others for 17th century collectors.

Now and then, a painter like Claude Monet or Pablo Picasso comes along and turns the art world on its head. They invent new aesthetic styles, forging movements such as impressionism or abstract expressionism. But could the next big shake-up be the work of a machine? An artificial intelligence has been developed that produces images in unconventional styles – and much of its output has already been given the thumbs up by members of the public. The idea is to make art that is "novel, but not too novel", says Marian Mazzone, an art historian at the College of Charleston in South Carolina who worked on the system.

A woman appears to walk down a hallway, then melts into a moonlit sky. A face appears in the dark, contorts into shapes. The animation is based on a 1929 film version of Edgar Allen Poe's story, but its inky and strange visuals are the result of something altogether more modern: machine learning. Each moment of Ridler's film has been generated by artificial intelligence. The artist took stills from the first four minutes of the 1929 movie, then drew them with ink on paper.

Machine learning already plays a big part in your everyday life, and its role is only going to grow. Google searches and muttered requests to Amazon's Alexa may tap into a veiled world of clever algorithms, but these techniques teeter on something much larger: a world of self-developing artificial intelligence. Deep learning, and the neural networks that do the thinking, is becoming an integral seam to digital technology. By extension, artificial intelligence is having a growing effect on our experience of the world and, as an artist, it is a material that can't be ignored. That at least is the thinking of Anna Ridler, who is building a name for herself with works that hoist machine-learning techniques and bring them into the gallery.

In the art AI, one of these roles is played by a generator network, which creates images. The other is played by a discriminator network, which was trained on 81,500 paintings to tell the difference between images we would class as artworks and those we wouldn't – such as a photo or diagram, say. "You want to have something really creative and striking – but at the same time not go too far and make something that isn't aesthetically pleasing," says team member Ahmed Elgammal at Rutgers University. Once the AI had produced a series of images, members of the public were asked to judge them alongside paintings by people in an online survey, without knowing which were the AI's work.