Generative AI, when and how should we use it?

4 minute read

Stin Mattu Product Marketing Manager for Contact Center Products

Generative AI is well and truly the hot topic in the tech world right now, Tech giants like Google, Microsoft and Amazon are accelerating their development since ChatGPT became the fastest adopted innovation for the average user.

Much debate has followed, especially since some of the models have returned questionable content. Fans of Generative AI and evolving tech will take these with a pinch of salt while others will think of worst-case scenarios amplified in part, by the stories we have seen in the world of entertainment. No one wants the fictional company Cyberdyne Systems develop Skynet which led to the creation of Terminators or have to employ Will Smith to fend off rogue Robots, let alone to live in the Matrix as batteries for the machines (which pill was it again?).

Use cases for Generative AI.

Whilst there are some legitimate concerns about the rapid rate at which new AI products are emerging and, in some cases, the questionable use cases they serve, there is value in getting assistance from AI. The question shouldn’t be can AI do everything, it should be, how can AI help me to do what I need to get done?

From a customer service perspective, customers being able to interact with a company 24/7, 365 and get answers when they need them is a dream come true. To get to that stage, a lot of work has to be done to ensure that the information that is shared is correct and that the machine has been trained correctly to respond to the diverse ways in which humans interact. It is very important to remember that no one knows customers better than your agents, they should always have an input into developing the solution, they are real subject matter experts after all.

In a recent TED talk by one of the co-founders of Open AI, Greg Brockman shared some interesting use cases where GPT-4 could provide useful information to help drive decisions that may be overlooked by the human mind. The caveat would be that the information should always serve as a guide from which further research could be done to find the best course of action.

This is not dissimilar to the way we work today by gathering information from all our available data sources and experts to make informed choices on how to proceed with what the goal is. The difference is, the time and effort we have to put in to do this impacts available resources and drives up cost.

Adopting a 80/20 model to use of AI.

80/20 can many things in the business world, for AI we can adopt it as a simple formula, use AI to do 80 percent of the groundwork, allowing the remaining 20 percent to be done by a human who can utilize 100 percent of their effort towards their remaining tasks. This is not a new concept in itself; machinery was the innovation in the industrial age that realised the same concept.

Here at Upland, we are taking this approach with how to improve efficiency in knowledge management with the Upland AI Knowledge Assistant. The first step in realizing this to help authors with fast tracked knowledge creation in RightAnswers. The concept is simple, allow authors to have options on how the knowledge is created, either by using GPT to start the content creation process with dedicated commands or to input content that can be optimized to match a particular brand style or improve customer readability.

Taking this approach still gives humans control on what is created and shared but in less time. All of the efficiency with minimal risk. The fact that an author now has the mental capacity to concentrate on the remaining tasks with less strain means they can be more productive and be freed up to work on other important issues with a clearer head. Employee satisfaction is now becoming a more recognised factor in leading to better customer outcomes, we strongly support this.

I’m certain this will not be the only AI use case that we will continue to develop for knowledge management use in RightAnswers, Panviva or BA Insight. It is a solid foundation on which we will build more customer focused innovations in creation, optimization, and delivery of knowledge.

The future is now and if you want to know more about Upland AI Knowledge Assistant and how it can help free up your staff to focus on customer needs, feel free to reach out to the team for a demo.

Hasta la vista for now (admit it, you just said that in Arnie’s voice😉)

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