Essential rules of adopting AI in mining and metals
Watch this webinar to learn:
- A simple definition of AI and the benefits of adopting it into your operations.
- AI maturity model.
- The anatomy of a successful AI project.
- Real-world examples and success stories.
Mining and metals companies contend with an unpredictable market and volatile commodities pricing. In response, these companies must increase tonnage while reducing cost, and they are often pressed with making important decisions in uncertain circumstances. They seek out artificial intelligence (AI)-driven technologies in pursuit of more stable results in their operations to improve quality, increase tonnage throughput and even achieve autonomous operations. But first, they must lay down the proper data foundation to take advantage of the many benefits that AI can offer.
Increasing output while reducing production costs is every company’s dream. However, achieving that dream requires optimised assets, processes, and optimising strategies without compromising team member safety. Now, many companies are looking for new ways to improve efficiency and overall production by embarking on a digital transformation journey. Digital transformation enables key stakeholders to turn operational data into quantifiable business results.
Unfortunately, many companies are struggling getting value out of such initiatives. They are not taking a structured approach on new deployments, focusing on implementing new AI technologies without first having the right operational data foundation in place and making sure their people are properly empowered.