With the business world becoming congested with large volumes of buzz words, it can be easy for business leaders to switch off when trying to discuss artificial intelligence and machine learning etc.
However, there is now no denying that these technologies and advancements are changing the way businesses operate and grow.
Latest figures from the New Vantage Partners – Big Data and AI Executive Survey 2019, show 96% of top executives think that AI is the number one disruptive technology they were investing in, up from 68% two years previous. As it is now crucial that businesses look to incorporate such solutions, they must first gain a clear understanding of these solutions.
Demystifying artificial intelligence
We associate AI with data recognition, image recognition, text to speech, sentiment analysis, personalisation and see it as something very complex to implement.
In simple terms, AI can be defined as a set of tools that can be used to make computerised systems and processes behave in an intelligent and automated way. By imitating human thought patterns, AI has the ability to self-teach, solve problems and process large volumes of data. This means processes can be self-regulated by AI to enhance customer experience while continuing to improve the overall efficiency of the business processes.
Machine learning vs Deep learning
To understand the finer detail of AI, it is best to split it into two groups. The general AI is as mentioned before, the ability of machines to solve problems from a human perspective without the need for human intervention. Whereas artificial general intelligence has the cognitive abilities of AI and can understand the environment it is working with to then apply algorithms to process data and utilize various areas of knowledge.
A key area of AI is machine learning. This is the part of AI that has the ability to evaluate data, train itself and then make calculated decisions based on that data it has analysed. Using the algorithms installed, decisions are made based on the previous learnings and patterns that have already been tested. The key fact is that AI is focused on learning from a vast amount of data and then adapting to make those decisions.
In addition to this, there is deep learning. This is a more evolved form of machine learning that works by learning though its own data processing rather than through a data input. This means that the algorithms within deep learning decide for themselves to see if a prediction is accurate. In short, deep learning’s aim is to make situation-dependent decisions rather than rule-based ones.
AI is not out of reach
Once the power of AI is understood, it is wise to implement such solutions as early as possible. It is easy to do so and we recommend starting with a business use case by finding the highly repetitive tasks where people are involved and have an AI-based solution to accomplish those functions instead.
For example, use robots with AI to:
Update employee leave within your HR system
Use IBM’s Watson to perform comprehensive research for businesses, completing tasks such as comparing their competitors and producing detailed reports. Together with RPA it can be used to update internal data in marketing systems to provide surprisingly accurate predictions regarding the potential success of new products or services.
AI-enabled chatbots can provide intelligent answers to customers interacting with businesses. For example, an AI-enabled chatbot can take rule-based decisions on a complaint and with the help of RPA update back-end systems with the latest case information and also notify human complaint handlers of any exception
Get in contact with us at ABP and see how we can help your business with AI.