Generative AI and ChatGPT: How the Tech Could Overhaul the Consumer Goods Industry and Red Flags to Look For
Before launching into use cases, it’s important to identify that generative AI, while not abruptly new, has recently seen a surge in adoption as companies feel confident enough in the tech’s ability to release it for widespread use. But its foundation is wholly different from general AI in functionality, and models vary widely from each other.
“Technologies like neural nets have been around for decades,” says Harmon. “Many companies developed technology like ChatGPT a while ago, but didn't release it because it wasn't ready for a broad audience.”
The tech continues to evolve at a rapid pace, he says — largely due to healthy VC investment and an increasing amount of computing power which can enable new AI capabilities.
The global generative AI market size accounted for $7.9 billion in 2021 and is projected to occupy a market size of $110.8 billion by 2030, according to Acumen Research and Consulting, a global provider of market intelligence. And total private funding in China alone was estimated at $17.21 billion in 2021.
Generative AI Applications
Despite being so new to the industry, CGT predicts long-term benefits. In fact, we foresee generative AI playing a forward role in the consumer goods jobs of the future, particularly in the areas of upskilling. According to a recent Gartner blog post, generative AI will likely be used “to replace, recalibrate, and redefine some of the activities and tasks included in various jobs.”
Among its capabilities, said Gartner, are summarizing text, classifying content, answering questions, and translating and converting language (including programming languages).
Using these abilities as a guide, it’s safe to presume the technology can impact areas of business like marketing and e-commerce in order to provide more targeted marketing, elevated customer support, and increased personalization efforts to boost loyalty.
The top potential use cases for the consumer goods space, says Mukherjee, are “generating novel, diverse, and personalized copy content, audio, video, and images at speed and scale; and saving time and cost for audiences in different languages spread across other geographical boundaries.”