The viral popularity of ChatGPT, a language model chatbot, has thrown generative AI into the mainstream. The technology, developed by OpenAI, has captured the imagination of more than a million users. From asking for cocktail recipes to penning a love song, users have been experimenting with ChatGPT’s instant conversational responses.
However, it is the potential that generative AI has in business that has got investors excited. According to data from PitchBook, generative AI investment has increased by as much as 425% from 2020 to December 2022, reaching a total figure of $2.1bn last year – a particularly impressive feat considering a wider downturn in tech investment in 2022.
Many investors and analysts now predict a ChatGPT-inspired funding boom for generative AI companies. ChatGPT and other programmes like it have provided plenty of entertainment to users. But if generative AI is to truly revolutionise industries ranging from search to journalism to recruitment, there need to be real-world use cases for the technology to justify the hype.
UKTN has looked at some of the ways businesses are already using generative AI tools in their day-to-day.
Danny Waites, a data analyst at marketing agency Embryo Digital, told UKTN that ChatGPT has had a significant impact on his work. Waites said that the coding capabilities of OpenAI’s platform have been a great asset to his daily duties.
“I use python every single day in a wide variety of different use cases and I simply can’t remember the name of all the functions within certain libraries,” Waites told UKTN.
“For instance, if I get a task that requires me to web scrape, ChatGPT will be able to suggest some libraries that I might not have used and taken a longer approach to get the data.
“I’ve also used it to create Excel formulas, instead of testing one out piece by piece and taking 10 minutes to build one I can get the answer I need as long as I’m specific about the steps I need to take.”
He described the programme as a “better Google”, which responds with one “usually correct answer” as opposed to traditional search engines which present “hundreds of possible ones”.
Phelan Gowing-Mikellides, a business development manager at public relations firm Digital Trails, explained how certain copywriting tasks can be expedited greatly through generative AI.
“A journalist sent a request out for expert comment on the comms industry and predictions for the coming year,” Gowing-Mikellides told UKTN.
“I met the comment criteria set out in the request so I just copied the query into ChatGPT and got the AI to generate a response for me.” Gowing-Mikellides admitted the result needed to be “tweaked” to sound “a bit less robotic”, however, the final comment ended up getting “featured on a roundup of expert opinions”.
Since then, Howing-Mikellides has used a similar generative AI approach to pitch stories to journalists. Howing-Mikellides said the “response rate has been really good” and that it it “takes me no time at all to do so I can send like a hundred, hyper-personalised responses per day”.
Eilon Reshef, co-founder and chief product officer at revenue intelligence company Gong described how generative AI can be used by customer service and sales teams.
“Using generative AI, sales teams can sift through all historical customer interactions across mediums (e.g., web conference, phone, email, instant message) and then prompt it to draft the next response,” Reshef told UKTN.
“Imagine you’re a salesperson who needs to respond to a question by the customer. Based on AI’s understanding of the account history, imagine that it could guide you through crafting the perfect response.”
Reshef also described how generative AI can allow sales teams to develop refined sales pitches to prospective clients, which can save staff time, allowing for a greater number of calls to be made.
“Considering the average salesperson clocks nearly 100 interactions each day, the time savings would be significant,” Reshef added.