Rowena Saquin

AI is transforming the way we work, and business outcomes across industries. In many industries like Finance, e-Commerce, Marketing, Transportation, Telecommunications, etc., artificial intelligence and machine learning have been successfully integrated into operations to optimize processes, enhance efficiency, and reduce operational costs to improve business results. The application of AI on industrial applications, on the other hand, has traditionally lagged behind. While there are some successes in very specific sectors like manufacturing, the broader implementation in process plants, energy, and other utilities is very limited compared to other industries. While the potentials of AI has been demonstrated in many industries, there are challenges inherent to industrial applications. Firstly, data security and availability are key hurdles. Industrial settings often involve sensitive data and are often siloed as a result. Collecting data to develop accurate AI models, therefore, becomes a formidable task. Secondly, the domain knowledge is very limited. There are very few people who can verify the accuracy of results of AI models. And lastly, there is a need for upskilling the workforce to harness AI effectively in industrial applications. Despite these challenges, AI continues to promise remarkable benefits that improve safety, productivity, and resiliency. As the industry continue to adapt, overcoming these obstacles will be crucial to realizing the full potential of AI in the industrial sector.