In just one year since the introduction of ChatGPT for generative artificial intelligence (AI), it has brought about major changes in the way we view work and complete daily tasks.
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Depending on who you believe, generative AI will either make us more efficient at work or put most of us out of work.
A key challenge for professionals and their businesses right now is to explore how generative AI can be used to increase productivity.
Six business leaders discuss how their organizations are beginning to explore and leverage generative AI, and offer six ways you can get involved.
1. Play with technology
Adam Warne, CIO of retailer River Island, said his organization has already begun to “leverage” GPT and is anxious to see if the technology is ready for customer-facing services before taking the next step in its exploration. I would like to make sure that there is.
“I think we’re probably in a similar situation as a lot of people,” he says. “We use it to generate ideas for content, such as blog posts, marketing posts, and product descriptions. But we’re not putting it into production.”
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Like other CIOs, Warne is cautious about using AI. Right now, he says, there needs to be a “human touch” between what generative AI is doing within the business and what customers are seeing on the outside.
However, he expects the level of automation to advance rapidly and advises all professionals to start considering generative AI.
“Given the speed at which it’s coming to market and evolving, I think it should be on everyone’s radar,” he says. “This is a way to go mainstream, but it will be production-ready very quickly.”
2. Use to increase efficiency
Brad Woodward, head of data at women’s lifestyle retailer Hush, believes generative AI tools can significantly improve the productivity of professionals of all kinds, especially IT developers. He says he is already looking into ways to do so.
“How we look at it, and how we train others to use it, is how we can do our jobs more efficiently.” he says.
“What’s really interesting about a tool like ChatGPT is how it can help you do things like write code or explore databases more efficiently.”
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Woodward cites an example from his own work life where he recently had to prototype a reporting model.
He didn’t want to use live data, so until recently he had to manually create sample data for his model. Instead, he turned to AI.
“I just said to ChatGPT, ‘Can you generate a bunch of database tables and some sample data for this model?'” 100 rows appeared, and I said, “I’d like some more. Is that so?” And we got 1,000 lines,” he says.
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“It was very easy. It might have taken an hour or two before. Now we can automate that task. We’re talking about generative AI within our team: How can we improve efficiency? Would you like to use this tool to improve your performance?
3. Take small steps
Lily Haake, head of technology and digital executive search at recruitment firm Harvey Nash, says the best starting point for professionals looking to explore generative AI is a knowledgeable partner on the other side of the enterprise firewall. It states that it is to search for.
“One of our clients was working with a third party,” she says. “At a certain scale, you don’t necessarily need to build that capability in-house; you can rely on a third party that has real expertise.” In fact, Haacke says smart professionals will probably and that they will choose to work with multiple external partners.
“It’s a good idea to seek out some third parties to ensure legal and ethical responses,” she says. “It really helps to have someone who has a helicopter perspective.”
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Companies that find strong partners can further develop their understanding of emerging technologies. With this kind of knowledge, it is possible to start exploring and, as Haake suggests, take “baby steps” to establish use cases for generative AI.
However, she also has a word of warning. Professionals who want to explore generative AI should make sure they have the information ready.
“You can’t automate and drive great AI initiatives unless you have the fundamentals of data management and governance in place,” says Haake. “If you’re not sure if you have quality data, that should be your starting point.”
4. Focus on business use cases
Prakash Rao, group head of supply chain projects at retail and services giant Landmark Group, says ChatGPT has great potential, but it’s important to focus on the business case. “Otherwise, it’s just jargon,” he says.
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Rao likens the rise of generative AI to innovations plotted in analyst Gartner’s Hype Cycle for Emerging Technologies. Every innovation has a peak of excitement, and people in IT and other industries see technology as a panacea.
Now, Rao says he expects a “trough of disillusionment,” where the hype around AI begins to plateau and then reaches a plateau where widespread acceptance, adoption, and use become commonplace. .
“Technology that can actually be applied to business has reached a level where every use case can come from this technology,” he says. “Going forward, we will see many useful business cases emerge and synergies in terms of the benefits of these technologies as well.”
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Rao said business departments across Landmark Group are considering ChatGPT, especially marketing and sales, where AI could provide new levels of customer service and interaction. “And of course, ChatGPT will also be evaluated in the supply chain,” he says. “But I haven’t seen any useful applications at this point.”
5. Explore enterprise-ready tools
Robyn Furby, technology implementation manager at insurance company NFU Mutual, says ChatGPT should be considered carefully, but is enthusiastic about the potential for enterprise-ready adaptation by Microsoft.
“We’re looking at it in the context of understanding what it means,” she says. “Naturally, as any financial services organization, we’re going to be cautious. And as a technology enthusiast, I’m interested in helping people use it securely. So our focus now is on how users can use it in a way that’s relevant today. ”
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Furby said the real power of ChatGPT is that it uses current language models, such as OpenAI’s GPT-4, to answer questions, provide information, and generate content.
“I think it’s going to be very interesting to see how it’s used,” she says. Microsoft’s AI Copilot began rolling out to devices running Windows 11 version 22H2 at the end of September. “In the meantime, we need to educate people about the differences between all these AI tools. What can external tools like ChatGPT and Bing be used for, and what can Copilot be used for? The education period is going to be an extensive process.”
6. Don’t forget to look into other areas of AI
888 Stephen Wild, engineering manager for observability and automation at William Hill, started dabbling with ChatGPT, as did the rest of his team, especially younger staff.
However, experimentation does not mean production. Wilde says experts need to be careful to ensure that generative AI brings significant benefits to their businesses. “I’m more worried at the moment,” he says, reflecting on the rapid pace of development. “The biggest problem I feel with the free version of ChatGPT is that it actually only works until 2021.”
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Like other digital leaders, Wilde believes the launch of enterprise-ready applications will be a turning point. “It would be interesting to see if Microsoft moves beyond Bing and starts incorporating technology into things like Teams. That’s probably the next big revolution in technology,” Wilde said.
He also says it’s important to recognize that the impact of AI is not limited to generative systems. For example, his organization uses New Relic’s automated application monitoring and observability platform.
“Machine learning is already very important to us. We use AI through New Relic and their alerting service. This reduces the number of alerts we have to attend to.” he says. “We also use this tool in the sense that we are constantly exploring our possibilities and checking for bots that try to freely promote us. The more bots we can find, the more You get better results.”