Improving Interactions with Unstructured Data

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Improving Interactions with Unstructured Data


The promise of a brighter, better tomorrow: that’s the driving factor behind technological advancements. And the promise of the OpenAI generative artificial intelligence, GPT, has a tidal wave of possibility attached to it. But with every breakthrough comes new risks and dangers.

For customer experience and service leaders, the capabilities that can be realized with this exciting technology are monumental. Organizations, regardless of size, can leverage this technology to humanize every interaction and interact with unstructured data like never before.

And while AI is nothing new, it has developed and become more accessible at light speed over the past year, causing a shift in the industry. This development has allowed us to rapidly rush the complexity and authenticity of AI across any medium. But is the recent hype surrounding large language models like ChatGPT from OpenAI all smoke, or is this here to stay?

Where Future Technologies Fall Down

First, let’s look at the pain points with traditional chatbots.

With pre-defined scripted journeys on a fixed set of inputs, chatbots are tailored to guide specific journeys with certain outputs. But as many customers experience, chatbots can quickly become too narrow and inflexible. They lack the human element, and people notice. There are hundreds of ways to ask questions, air a grievance, or respond to a prompt — but the bot, with human-designed journeys, is limited in its comprehension and versatility. Not to mention that it can take countless hours for development and deployment.

Then on the other side of the coin — there is generative AI and GPT.

The meteoric rise of GPT is a continuation of this technological advancement. This technology is a Natural Language Processing tool (NLP) driven by AI, drawing on Large Language Models (LLMs) to create unique human-like conversations. In other words, it is a complex learning algorithm trained on massive amounts of data surrounding how humans communicate. And unlike traditional chatbots, it can produce unique, personalized, and human-like phrases.

But with great rewards come risks. Generative AI has been known to be offensive and politically incorrect. In addition, it can produce irrelevant answers. Another concern is accuracy. When so much data is plugged in, there is a high probability of generating incorrect solutions with confidence. And while some view this technology as a universal CX solution, the reality is that without proper guidance, the CX output will be more generic and less helpful than the tools we have in the market currently. The future involves creating a system that harnesses the power of generative AI within a brand’s framework and is purpose-built for CX.

How New Technologies are Ushering in a New Era of CX

That’s where Enlighten Actions comes into play.



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