The year 2022 saw the graduation of generative AI into a full-fledged creative force after years in which artificial intelligence-generated entertainment was renowned primarily for its humorous absurdity—only infrequently wandering towards unsettling realism.

Anyone can easily make lifelike pictures with a straightforward language prompt thanks to a variety of realistic image generators, including OpenAI's Dall-E 2 research group's creation. In the meantime, OpenAI's ChatGPT gave its cutting-edge text generation system a conversational interface. 

Users can now tell a machine what to write by simply telling it what to, and within seconds, they will receive a detailed and well-written passage—even if the facts aren't always accurate. These new systems have already spurred extensive experimentation among brands, agencies, burgeoning startups, and creative tool integrations. 

They were trained on datasets that total hundreds of millions of images and pages of text, respectively. According to analysts, brand marketers and agencies will begin to seriously consider how this type of synthetic material may be used to boost human creativity and fulfil business objectives in 2023. 

Marketers will also have to deal with a plethora of new hazards brought on by this proliferation, such as issues over authenticating the legitimacy of content and machine copyright infringements. The most significant technical change he has recorded in the last five to ten years, according to Mark Curtis, head of innovation at Accenture Song and author of the company's annual tech trends report, is probably the rise of generative AI.

Beyond testing this out, agencies ought to be figuring out what it means for their operations right away, according to Curtis. It is a tool that people use to either jump-start their creative thought, develop something from the ground up and then continuously modify it, or move more swiftly. … While it does drastically change the economics of most of what we do in creative, it is not a panacea.

 ChatGPT was launched in the latter part of this year by OpenAI, the Microsoft-funded research facility that has been driving the development of the generative AI models that serve as the technology's foundation in recent years.

The new programme enhances the GPT-3 large language model, one of the group's earlier large language models, by making the tool more conversational. Users can now instruct ChatGPT what to write using simple text directives rather than inputting the first few words of a piece and having the tool finish it. 

In terms of emulating the grammar and style of a certain sort of writing, the results are frequently startlingly accurate. Similar to GPT-3, ChatGPT can be used for a variety of purposes, such as copy testing for digital ads, building realistic chatbots for customer care, and improving contextual search tools. Parts of these capabilities rely on the ability to reduce some of the machine's unpredictable behaviour and errors, which have been an ongoing issue at least since the 2019 release of GPT-2.

 However, a number of businesses and programmers are already trying to increase its sensitivity to the substance of the output or to create tools that get around its flaws. According to Zach Kula, group strategy director at BBDO, the sector should consider this tool's potential to revolutionise the work of creatives rather than focusing on how it can replace humans.