TALKING
‘‘ business
Charlene Smith, Sales Director, Insight Consulting
The hype surrounding AI being leveraged in businesses has reached fever pitch, to the point where many businesses are panicking about AI implementation. They fear being left behind, worrying that their competitors already have a competitive advantage. We have encountered many businesses that want AI but do not know what they want it for, if they can report to the board that the business has invested in AI. In many cases, AI becomes a box-ticking exercise.
This is unfortunate, because when understood as the transformative technology that it is, AI can become a powerful enabler across a business. This means that businesses must first take a step back and, to use a strong human analogy, breathe and ask why.
Too many businesses rush to implement AI without understanding why they are doing it. Unless there is a clear why, the how becomes futile. Of course, the fear of being technologically obsolete means everyone should absolutely be having the discussion but it should never lead to hasty, panicked decisions. Collaborating with an expert partner, strategic implementation of any technology, especially AI, trumps panic-driven adoption.
Machine learning is how computers are taught to learn from data without needing to be explicitly programmed for each single task. The computers can find patterns and then make predictions or decisions based on the data.
Deep learning is an advanced type of machine learning that uses artificial neural networks with many layers, hence the word deep. These networks can learn complex patterns from vast amounts of data, often used for functions such as image and speech recognition.
Another word you will hear a lot is algorithm. An algorithm is best described as step-by-step instructions that a computer follows to solve problems or complete tasks. Training data is the specific set of data used to train an AI model. An AI model is the brain of an AI system.
It is the result of training an algorithm on data. The model is then used to make predictions or decisions on new, previously unseen data. One will regularly encounter the word inference, which is the process of using a trained AI model to make predictions or decisions on new data.
Artificial Intelligence means computers think and act in ways that seem intelligent. This can range from simple calculations to complex problem-solving – at scale. It all starts with data. The better the quality and relevance of the data, the better the AI solution, as it depends on the data.
Understood this way, it becomes apparent that AI is a problem-solving, efficiency-enhancing tool. Tool being the operative word. It is not a magical solution. And so, in the rush to implement AI, businesses must ask: What problems do I need to solve, what efficiencies do I need to gain and how can I deploy this tool to address these? www. intelligentcio. com INTELLIGENTCIO AFRICA
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