Each year there seems to be a tech trend for enterprises to follow and these trends usually underpin sessions at the various conferences. Over the years we’ve seen the trend move from omnichannel, digital transformation, to customer experience…This year has firmly been entrenched in the world of Artificial Intelligence (AI) and Machine Learning (ML).
But, it’s no longer about the theory and the nice-to-haves. The trend is about how we use AI and ML to improve processes, provide a better customer experience, support digital transformation initiatives and drive omnichannel communications.
AI encompasses and fuels every trend we’ve seen in the last few years and will certainly drive the growth in many other areas over the coming years.
This year’s Document Strategy Forum (DSF) was firmly focused on sharing insights around AI and ML and what we need to be thinking about when it comes to incorporating AI into document and Customer Communication Management (CCM) processes.
Here are a few of the topics highlighted at the conference around AI and ML in general and some discussion around how they can be used in CCM:
AI vs Machine Learning
Stewart Rogers (@TheRealSJR), the keynote speaker at DSF and AI guru explains that Machine Learning is about finding patterns in data, while AI is about altering those patterns to meet a goal.
ML is a subset of AI and it’s about learning through repeated patterns, where AI is about developing a system to mimic human responses. Depending on the task at hand, machine learning can be better suited than AI and vice versa.
Machine Learning is great for content creation, when deciding which content is best suited to each customer, based on data on hand – such as past behavior, demographics, psychographics and location. While AI is a far better fit for predicting user behavior and using content based on that prediction to prompt the user’s next action.
Understanding the goals and needs in the organization is of utmost importance in applying the correct AI and ML strategy.
It’s all about the data
Without data, none of this is possible. A clear message at the conference was that companies need to adopt a strategy for the data available and the potential uses.
Data is essential for AI to function and to ensure the best possible customer experience. The best way to bring unstructured data that sits in siloes together, is through machine learning.
Stewart quite rightly pointed out however that AI is a mirror to our own views and so, we need to ensure not to include biases in data. Junk in, junk out (which includes biases) – AI can’t fix that, it just highlights it.
Another factor to consider are your documents and ensuring your organization has a strategy, if they are to apply AI to customer documents.
Documents should be treated the same way as data,when it comes to applying standards for use in AI processes.
So, what does this all mean?
Using data to drive AI and Machine Learning, organizations are able to improve the customer experience by personalizing interactions, as well as products and services to meet the needs of the customer.
It’s all about the data and leveraging what you have, to make future choices, processes and the customer experience better than before.
