Demystifying Artificial Intelligence, what is AI?
Artificial Intelligence (AI) has become a buzzword in recent years, mentioned by many but rarely understood. What exactly is AI? And how does it work? In this blog series, we’ll explore the fascinating world of AI, shedding light on its fundamental principles and mechanisms.
Artificial Intelligence (AI) often seems like a mystical concept, shrouded in a veil of complex algorithms and machine learning models. However, the reality is far less intimidating. AI is more accessible than most people think. It is not about creating super-intelligent machines but about harnessing the patterns within data to make informed decisions, optimize processes, and gain a competitive edge. This blog post aims to demystify AI and inspire you to explore its potential in your business.
What is AI?
AI is a broad field that includes various methods, technologies, and techniques. It involves creating systems or software that can perform tasks typically requiring human intelligence such as problem-solving, learning, reasoning, understanding language, recognizing patterns, or making decisions. In simpler terms:
“AI is a way to use hidden patterns within data to make informed decisions.”
The Role of Analytics
Analytics plays a pivotal role in AI, offering different levels of insight and capabilities.
These levels can be defined as descriptive, predictive, and prescriptive analytics. Without these key principles, it’s unlikely you’ll be able to create intelligent systems.
So, what does analytics mean? It involves asking and answering four essential questions:
- What happened?
- Why did it happen?
- What is going to happen?
- How do we make it happen?
Descriptive Analytics
At the foundational stage sits Descriptive analytics. It involves gathering, organizing, and summarizing historical data. It aims to provide a clear picture of past events, patterns, trends and answers the questions: ‘What happened?’ ‘And why did it happen?’ With these answers we transform findings into a clear story, removing ambiguity and uncertainty for decision-makers.
Predictive analytics
At the next stage of AI, we find Predictive analytics. Utilizing Predictive analytics means going a step further, leveraging historical data to make predictions about (future) events or trends. It simulates and extrapolates potential outcomes, based on patterns found in the data using statistical and machine learning models. It aims to answer the question: ‘what is going to happen?’ By anticipating future scenarios, predictive analytics allows us to make informed decisions and redirect our strategy where possible before things go south.
Prescriptive analytics
We find Prescriptive analytics at the final step of AI. Recommending actions or strategies to achieve desired outcomes or avoid undesirable ones. It combines data analysis, prediction modelling, optimization, and simulation techniques to establish what-if scenarios. Prescriptive analytics suggest the best course of action based on (business) objectives and constraints. With it answering the questions: ‘how to make it happen?’ ‘What should we do to achieve our goals?’
Conclusion
AI and analytics are not mystical concepts. They are practical tools that can be used to drive data-driven transitions, challenge the status quo, and inspire what is possible. AI is a broad and evolving field of computer science that aims to create systems and machines capable of performing tasks that typically require human intelligence. Analytics plays a crucial role in building these capabilities, with each type of analytics playing a distinct role. Descriptive analytics explains what has happened in the past, predictive analytics offers future insights, and prescriptive analytics recommends the best actions to achieve desired outcomes. These levels of analytics enables you to create intelligent systems that can learn and improve.
