How does AI improve decision-making and processes?
AI is increasingly infiltrating our lives, both professionally and personally, something we’ve all witnessed and noted in the media. Some of us have even used it in our careers and personal lives. The challenge with AI lies in training the model one uses, and this requires data. The more data there is and the more diverse it is, all while maintaining quality, the higher quality we can expect from the AI tool.
More and more companies are integrating AI into their operations, from image recognition to automating data-driven decisions. The major challenge is having quality data in large quantities to make the AI model as capable as possible. Data collection is time-consuming, which means it usually takes some time to get a well-functioning AI model to perform effectively. This is where synthetic data comes in. With the right tools, one can cost-effectively generate vast amounts of synthetic quality data, allowing for quicker training, testing, and deployment of an AI model for automated processes. This creates significant business value for customers, as they can realize their investment returns faster and further develop their processes.
