Potential Risks of Incorporating GenAI in Productivity Apps

Potential Risks of Incorporating GenAI in Productivity Apps

We’re in the “iPhone moment” for generative ⁣AI, with ⁢every company rushing ​to figure out its strategy for dealing with this disruptive technology.

According​ to a⁢ KPMG survey ‍conducted ⁣this June, 97% of US executives at large companies expect their organizations to⁢ be impacted ⁣highly by generative AI⁤ in the next‌ 12 to 18 months, and 93% believe it will provide value to their‍ business. Some 35% of companies have already⁣ started to deploy AI ⁢tools and solutions, while⁢ 83% ⁣say that⁢ they ‌will increase⁣ their generative AI investments by at least‍ 50% in the next⁣ six to twelve months.

Companies have been⁢ using machine learning and AI for⁢ years now, said Kalyan ‍Veeramachaneni, principal ​research scientist at MIT’s Laboratory for Information and Decision Systems, which is working on developing custom generative models ⁢to use for tabular data. What’s different now, he said, is that generative AI tools are ⁤accessible‌ to people who are not ⁣data scientists.

“It opens new doors,” he said. “This ⁢will enhance the ⁤productivity of a lot of ⁣people.”

According to a recent study by analyst firm Valoir, 40% of the average workday can be automated with AI, with⁤ the highest ​potential for automation‍ in⁤ IT, followed by finance, operations, customer service, ​and sales.

It can take years for enterprises to build their own generative AI‌ models and‌ integrate them into their workflows, but one area where generative AI can make an immediate and dramatic business impact is when it’s embedded into ⁣popular⁢ productivity ⁤apps. According ‍to David McCurdy,‍ chief enterprise architect and CTO at ​Insight, a Tempe-based solutions integrator, 99% of companies that adopt generative AI ‍will start by using genAI tools embedded ⁢into core business apps built by someone else.

Microsoft 365, ‌Google Workspace, Adobe Photoshop, Slack, and Grammarly are among​ the many popular productivity software ⁤tools⁣ that now offer a generative AI component. (Some⁤ are still in ⁣private beta‍ testing.) Employees ⁤already know ​and use⁢ these tools every day, ‍so ⁢when the vendors add generative AI features, it immediately makes the ‌new technology widely accessible.

In fact, according to a recent study conducted by⁢ Forrester on ⁤behalf⁣ of Grammarly, 70%​ of employees are already using generative⁣ AI for some or all of their writing — but 80% of them are doing this at companies that haven’t‍ officially implemented it​ yet.

Embedding AIs ⁢like OpenAI’s ChatGPT into productivity apps ⁤is​ one ⁢quick way for vendors to add generative AIs to their platforms. Grammarly, for instance, added‌ genAI capabilities to its writing assistance platform⁣ in March, using OpenAI’s GPT⁤ 3.5 ⁣in a private Azure cloud ⁤environment. But⁢ soon vendors will ⁣be able to build their own‍ custom models ‌as ‍well.

It doesn’t take millions of⁣ dollars and billions of training ⁢data records to train a large language ⁣model (LLM), the foundation‌ for‌ a genAI chatbot, if a company ⁣starts with a pre-trained…

2023-09-05 19:24:02
Original ‍from www.computerworld.com rnrn

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