5 AI Capabilities Every Business Leader Should Know About
Artificial intelligence is already here, and most of us use it in some way every day - often without realising it. It offers a completely new set of tools for solving a wide range of problems, and while the details can be left to the engineers, it’s important for decision makers to understand the basic capabilities of AI.
While there are countless technologies that use AI, I’ve identified five key AI capabilities that you may want to consider developing in your business.
1. Natural Language Processing
While there are some high profile examples of NLP, like Siri and Google Translate, the true potential in NLP for businesses is in automatic processing of written and spoken language.
Examples include: understanding how people are talking about your brand online, prioritising sales efforts based on recorded conversations, and chatbots that interact with customers.
2. Supervised Learning - Regression
AI is especially useful for finding patterns and trends in historic demand in order to predict the future based on seasonal trends, time of day and other internal or external factors.
Examples include: predicting hospital patient numbers, predicting energy prices, predicting container port workload.
3. Supervised Learning - Classification
AI is able to process massive and complex data sources in order to answer questions about what something is, or isn’t.
Examples include: is this account fraudulent? Is this person likely to buy my product? Does this video show someone shoplifting? Is this machine likely to fail soon and should be serviced?
4. Reinforcement Learning
This technology is essentially trial and error learning. An intelligent computer learns by making decisions in a simulated or real environment in order to achieve a goal or optimal behaviour.
Examples include: What route should I take to optimise garbage collection routes? Where should I send ambulances in a city so that response time is minimised? How should I allocate my digital marketing budget amongst different channels?
5. Unsupervised Learning
This technology refers to the ability for AI to analyse data and find correlations and clusters which might not be immediately obvious.
Examples include: What menu items tend to sell well together? What are the customer profiles for my product/service?
Most AI applications fit into one or more of the categories above. At Piccard, we specialise in developing user-focused, carefully designed software experiences on top of state-of-the-art AI technology. If you’re interested in finding out how we might be able to help your organisation, please get in touch.