Leaders, managers, and teams must understand AI and its business implications to stay competitive in today’s ever-evolving global economy. This blog post discusses AI technology and its effects on businesses.
AI machine learning is when computers can learn and get better at tasks by looking at examples.
Supervised learning is when the computer is given labelled examples to learn from.
When I first researched this, it did not make sense. I’ve used this example to help you visualise this:
Let’s say the CEO of a company wants the managers to learn how to identify and handle customer complaints effectively. The CEO may provide the managers with a set of customer complaints along with the recommended solutions. This is an example of supervised learning, where the CEO is the “leader” and the managers are the “learners.”
The CEO provides the “training data,” or examples of how to handle customer complaints, and the managers use this information to learn and improve their skills. The managers can use this knowledge to handle similar complaints in the future, and the CEO can monitor their progress and provide feedback as needed. Through this process, the managers can learn from the experience of the CEO and become better at handling customer complaints.
Unsupervised learning is when the computer learns on its own without being given labelled examples.
To help you visualise this, and how AI technology could help a company identify customer pain points:
Let’s say the CEO of a company wants to identify customer pain points without any prior knowledge of what those points might be. This is an example of unsupervised learning, where there is no pre-labelled training data. In this case, the CEO might analyse a large dataset of customer complaints and use unsupervised learning programmes to identify patterns and clusters of similar complaints.
The computer programmes can group similar complaints together and help the CEO understand what the common pain points are. Once the pain points are identified, the CEO can work with the managers to come up with solutions to address those pain points.
The computer programmes can also be used to monitor customer feedback in real-time, so the company can quickly identify new pain points as they arise and respond to them in a timely manner. Through this process, the company can improve customer satisfaction and loyalty.
AI machine learning can change many industries, like healthcare, finance, and retail.
For example, it can help doctors predict patient outcomes, help investors make better decisions, and give shoppers a more personalised shopping experience.
Deep learning is a way that computers learn by looking at examples. Yes, ok, how can I explain this?
You may remember learning at school how to recognise different animals by looking at pictures of them in a book. So, imagine a computer looking at lots of pictures of animals.
Instead of just memorising the pictures, it uses them to figure out how to tell one animal from another.
Deep learning has been responsible for some of the most significant breakthroughs in AI, including computer vision, speech recognition, and natural language processing. Deep learning computer programmes can be used to do many different things, like classifying images, recognising speech, and translating languages.
Natural language processing
This sounds scary, right? I’m sure we are all sick of ‘holding on the line’ to get customer service… chat-bots to the rescue!
Natural Language Processing (NLP) can help businesses make this process quicker and easier for their customers.
NLP technology allows computers to understand and communicate with humans using everyday language. This means that instead of waiting on the phone for a person to help, businesses can create chatbots and virtual assistants that can help customers right away.
These digital assistants can answer questions, schedule appointments, and solve problems—all in real-time. They can even provide personalised service 24/7. This technology can save businesses time and money while also making their customers happier.
Stephen Spielberg territory lol!
Robotics is a field of AI that focuses on the design and development of robots, which are machines that can perform tasks that typically require human intelligence. Robotics has the potential to transform various industries, including manufacturing, healthcare, and transportation.
For example, robots can be used in manufacturing to improve production efficiency and quality control, in healthcare to assist with patient care and surgery, and in transportation to improve delivery times and reduce costs.
AI and Industry 4.0
Industrial revolutions have defined human history, from harnessing the power of water and steam in the first to electrifying production processes in the second, and introducing computing across many industries in the third.
I can’t believe I’m living in the 4th industrial revolution!
Industry 4.0 is the fourth industrial revolution, characterised by the integration of advanced technologies, such as artificial intelligence (AI), the Internet of Things (IoT), and robotics, into the manufacturing process. Industry 4.0 has the potential to transform manufacturing by improving production efficiency, reducing costs, and enabling the production of customised products at scale.
For businesses, adopting Industry 4.0 technologies, such as AI, can provide a competitive advantage by enabling them to produce higher-quality products faster and more efficiently.
AI and business transformation
AI has the potential to transform businesses in a number of ways, from improving the customer experience to automating tasks and improving decision-making.
For example, AI can be used to personalise the customer experience by using machine learning programmes to analyse customer data and provide personalised recommendations. AI can also be used to automate tasks such as data entry and customer service, freeing up employees to focus on higher-value activities – yeah!
Moreover, AI can be used to improve decision-making by providing businesses with insights and recommendations based on large amounts of data. For example, machine learning programmes can be used to analyse market trends, predict customer behaviour, and identify new business opportunities.
However, with AI’s potential benefits come potential challenges. Businesses need to be aware of the ethical and social implications of AI, such as privacy, bias, and job displacement, and ensure that AI systems are developed and deployed in a responsible and transparent manner.
The key takeaways
AI technology has the potential to transform businesses in a number of ways, from improving the customer experience to automating tasks and improving decision-making.
However, it is important for leaders, managers, and teams to understand the different types of AI technology and their potential impact on business to ensure that AI is integrated into their organisations in a way that benefits both the business and society as a whole.
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