ChatGPT has dominated the tech news cycle since it was released in November, and it will certainly not be the last as tech companies are feverishly working to release new solutions with new generative AI capabilities designed to help enterprises work more efficiently and intelligently.
Microsoft and Google, two the biggest players in enterprise computing, are leading the charge in bringing generative AI to the workplace with Bing and Bard, respectively. However, many other tech firms are integrating OpenAI’s GPT-4 and other language models into their solutions to provide an intelligent assistant to augment their human users’ skills.
With these tools and use cases rapidly expanding, IT leaders should begin thinking about potential use cases and developing a plan to bring generative AI to their workplace, according to two Gartner analysts during a virtual press briefing on AI from the analyst firm’s Data & Analytics Summit this week in Orlando, Fla.
Generative AI is coming for the enterprise
According to Frances Karamouzis, the group chief of research for IT leaders and GTP, and a distinguished vice president analyst at Gartner, AI already exists in a wide range of enterprise tools either in the user interface or in the functionality, so enterprise IT leaders should not shy away from adopting new generative AI tools.
While there are data privacy and security risks, as well as ethical considerations, Karamouzis says enterprises simply cannot afford to be behind the curve on AI.
“The biggest risk is standing still,” Karamouzis says.
ChatGPT beat out the largest social media platforms and other popular consumer apps for reaching 1 million users first, achieving the feat in just five days. And, the chatbot is widely available and easy to use on OpenAI’s website, making it accessible to the masses.
Microsoft and Google are following similar footsteps, with Microsoft making their OpenAI-powered Bing Chat available in a preview, and Google beginning to do the same with Bard. The big tech firms are poised to compete with one another in AI for the foreseeable future, and others will inevitably follow.
That is leading Gartner to predict that by 2026, 100 million workers will have what the firm calls a “robo-colleague,” a synthetic virtual assistant designed to help make users more productive and efficient. Rather than replacing jobs, Karamouzis says there will instead be an evolution where workers use these AI tools to augment their decision-making.
“Will they replace jobs? No, but I think there will be incredible tools that will help recalibrate and redefine how we do work,” Karamouzis says.
The concerns with adopting generative AI in the enterprise
With this pace of innovation and an equal amount of intrigue from organizations and users, the vendor landscape has shifted to focus on AI and finding ways to bring the technology to customers.
Now, the question becomes how enterprises and IT leaders put the technology to good use. However, Karamouzis says that may be easier said than done, predicting that less over the next two years, less than 15% of enterprises are doing to derive meaningful value from it generative AI.
One of those roadblocks may be the ethical, legal and regulatory concerns over the use of these advanced AI models, says Svetlana Sicular, a vice president analyst at Gartner focused on data and AI.
Many regulations exist that govern the use of data, but Sicular anticipates much more red tape around the use of data in AI models. In fact, many such regulations are already in draft form, and regulators everywhere are well aware of these new AI capabilities.
Around ethics, there are serious concerns around plagiarism and essentially, if ChatGPT should be an author or not. Whether or not organizations should disclose that content was created by generative AI is a big question.
Other concerns around data security may be less obvious, but represent an area where enterprise IT leaders may want to approach with great caution, Sicular says.
“If you go directly to the link to ChatGPT, your data is their data,” the AI researcher and analyst says. “Their training their model on your data, and people don’t realize it.”
With enterprises intrigued about the possible use cases of these advanced AI tools, they should think carefully about creating guidelines. However, what keeps Sicular thinking positively about the adoption of generative AI is that these concerns are being raised at the forefront of its emergence rather than after adoption is already widespread.
Sicular compares this to the emergence of social media, for which IT leaders and enterprises were not totally prepared.
“The alarms for AI were raised earlier in the cycle than for social media, which gives me hope that we will do the right thing,” Sicular says.
Enterprise adoption of generative AI and ChatGPT
As with any other emerging or trending technology, enterprises should remain open to the possible use cases and do their due diligence on how best to deploy generative AI models and intelligent virtual assistants.
Sicular suggests simply letting technology leaders explore its capabilities and use cases, but doing so safely and securely.
Coding has emerged as a popular early use case of generative AI, with programmers using these tools to generate code that is then quality checked by human experts. The human control of these programs, Sicular says, is key.
Microsoft has adopted the term “copilot” for its OpenAI integrations across its products, and that is a framing that bodes well for the industry, Sicular says.
“I like the name copilot. It reflects that you’re in charge,” Sicular says. “You’re asking someone trusted to help your or take on some of your tasks and give you the result of those tasks.”
Sicular also recommends that organizations have an open discussion about the possible use cases, encouraging users to share their experiences and allow use cases to grow organically based on that success.
“That’s where use cases will surface,” Sicular says. “It will take time for the enterprise to find those use cases, but if you allow people to experiment, you will see some interesting ideas that will make enterprises competitive or help them do certain things in a new way.”
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