AI is changing the world, and businesses are scrambling to keep up. It’s been a never-ending game of Tetris – just when you think you have everything figured out – some new piece of the puzzle forces your business to rethink its whole strategy (cough, cough, ChatGPT). In the world of AI, something new is always happening because something new is always being discovered. And while the pace of innovation will eventually slow down, it will only be after AI has transformed every business in radical ways.
But just what is AI? Very very broadly speaking, AI isn’t necessarily “intelligent”, it’s just really good at finding patterns in data. And from this data, it either generates something new or provides insight into the patterns it’s found. This is why we classify AIs as either Generative or Analytical. Generative AIs, such as ChatGPT or DALL-E – produce new content in the form of text, images, articles, etc. These are the types of AIs that create a response to users and generate novel images. Analytical AIs, on the other hand, analyze and provide insights based on the data they are trained on. Think sentiment analysis. The AI is not creating new data, but rather it’s analyzing and extracting valuable insights from existing data.
But there’s another important distinction between AIs, and that is the type of data used to train the AI. AIs are trained off Generic Data or Custom Data.
When we refer to Generic Data, we are often talking about large datasets that are publicly accessible. To build a chatbot for instance - millions of text references like books, Wikipedia articles, and blog posts are fed into the chatbot. Broadly speaking, these text sources form a giant word cloud, that the AI then responds to users. The problem is, the AI is only as good as its data, and will take on the “personality” of its underlying data. That means if an AI model is trained on a dataset of children’s books, your AI will respond like a child! Or if the AI extracts data from negative social media discussions it is more likely to generate negative opinions in its output. Maybe that’s not an issue for every organization, but knowing that a chatbot responding to your customers, could have been trained on some less-than-savory or biased data, is something to be aware of.
So, what’s the alternative to Generic Data? Custom Data! Custom data is tailored to the needs of a particular individual or organization. Unlike generic data, custom data is often highly specific and includes data unique to the organization. This type of data can provide more detailed insights and help companies make informed decisions.
Why don’t all organizations use custom data if it’s so much better? It comes down to the work involved to prepare it. Creating a custom data set requires not only collecting this data across your organization, but also requires standardizing this data – which entails careful planning and data collection processes to ensure that the information is accurate and relevant. When used effectively, custom data can be the powerful tool in your AI arsenal to better analyze your customers and improve your overall operations. But only if you have the right data.
Now, you might be wondering, how can your organization get the correct data to build an Analytical AI? Well, if you’re in the CX industry, you most likely already have the data. The beauty of the CX industry (and why we build AIs for it), is that contact centers already have access to the data we need to train AI. Equally important is having data that can be trusted - meaning data that has been properly collected and validated. The more integrity, the more efficient the training. For example, customers who adhere to the COPC CX Standard, a data driven framework that provides guidelines and best practices for improving performance, have an advantage with their data because the standard generates best practice data. When our customers data is properly standardized, all we have to do is connect their data to our AI platform, and we can start predictive analysis It’s simple, you have the data and we have the benchmark to see how quickly we can start predictive analysis for your organization.
"CX operations generate enormous amounts of data that are essential to understand the Customer Experience. They also generate lots of useless data – those who get ahead in the AI race are the ones who can tell the difference.” - Rolf Adamson.
AI is changing the world before our eyes, and businesses will either thrive or be left behind in the face of it. Nexcom’s team of AI researchers and CX experts build Custom Analytical AIs for businesses trying to navigate the changing landscape.
Need help standardizing your data? or just curious about Analytical AIs? Schedule a call with our AI Data experts and learn more.
