Three Different Artificial Intelligence Technologies
From within companies, many initiatives emerge that optimise different human-to-machine interactions by leveraging artificial intelligence technologies. Nonetheless, there is artificial intelligence and then there is artificial intelligence. Let us delve deeper into these technologies and how they increase customer value.Authors: Günther Lemmens, Jens Desmet & Sonja Noben
Robotic Process Automation
Robotic Process Automation (RPA) automates repetitive data entry or transfer actions by human workers with one or more application systems. These initiatives contribute to operational (often back-end/office) processes performance.
RPA completes necessary and critical activities at a lower cost, with higher and consistent quality, at all times of the day and night. They perform faster and are compliant with related rules and standards.
Between RPA and real AI, there is an intermediary step which is Machine Learning (ML). The difference between RPA and ML is that the former is rule-driven, while the latter is data-driven. Machine learning is both a part and a precursor of AI, as it already incorporates prescriptive analytics and runs decision-making engines.
However, this is not yet real AI since it relies on sets of mathematical rules. ML algorithms become iteratively more accurate in recognising patterns we train them on.
True Artificial Intelligence
The goal of all these intermediary developments is to create True AI software which mimics the human ability to decide, deduce logically, and act accordingly. These can understand what they are seeing, classify documents and pictures, identify patterns, create plans, solve problems, and interact with objects, systems, and humans.
One of the straightforward applications of true AI is natural language processing. It makes chatbots suitable replacements for humans in specific tasks, since bots can detect intent, understand requirements, and provide a personalised solution.
Compared to RPA, which would require a numerical input from the user (for Dutch press 1, for French press 2…), AI learns as it goes by observing and comes with different answers depending on the context and previous conversations.
Importance of knowing the differences
Knowing the differences between these levels of automation is essential. It helps to classify them but also to understand which is the best for a particular project.
For example, an AI chatbot interacts with a customer instead of a call-centre agent. In the background, a machine learning-powered recommendation engine finds the best matches for the customer’s needs. Meanwhile, an RPA tool makes the needed updates in the customer’s profile for further reference. DigitalScaler can help your organisation leverage these artificial intelligence practices to their fullest extent.