Scratching the surface of AI

In 2018, the software spending per company in the mining sector in the UK was just US$162 000, but this is forecast to rise to US$227 000 in the next two years. So, why are mining companies turning towards new software to improve their operations?

The mining industry produces a vast amount of data every single day, with data points being generated from sensors capturing data from vibrations in the ground and monitoring instruments that are helping to develop safer drill and blasting procedures. However, accessing all this siloed data is a resource intensive and time consuming task. Advances in artificial intelligence (AI) technologies are essential to unlocking insight from this unstructured data, helping organisations to realise efficiencies in raw material extraction, transportation and analysis, in the face of growing pressure to meet the global demand for critical raw materials.

For larger mining companies, the challenge of manoeuvring the digital ecosystems being used by teams around the globe is driving the demand for improved knowledge management. On top of this, the mining process itself is complex and draws upon many different pieces of equipment, technologies and sciences, while also involving an array of contractors and subcontractors, who are all communicating across different channels, such as: video calls, emails, instant messenger, and webchats. With so many different moving parts, being able to access all the business-critical decisions, which are stored in different repositories across the company, becomes increasingly difficult.

The potential business risk this presents is exacerbated by the diverse computing systems that are often used by mining firms, which, when accompanied by poor software integration, have the potential to miss the vital information required to produce essential documentation, such as tenders, reports and evaluations, in order to comply with industry regulation.

Conserving labour resources

While mining companies need to hire people to make sense of their unstructured data, statistics show that the industry found it hard to fill data-related vacancies during the start of 2022: the jobs that were advertised during this period had been online for an average of 15 days before being taken offline. This is an increase from an average of 13 days in 2021, signalling that the required skillset for these specialist roles has become harder to find in the past year. This is where knowledge management software underpinned by AI can offer real advantages thanks to its ability to break down data siloes and process information quickly and with extreme accuracy, thus enhancing resource productivity.

New cloud-based software solutions, such as those offered by iKVA, can instantly be implemented and integrated with existing workflow systems to relieve the strain on resourcing issues. iKVA’s technology – which harnesses AI, Advanced Machine Learning, and vector mapping technology – enables mining organisations to leverage unstructured data from multiple sources to reduce wasted time and improve profitability. This avoids sourcing highly-specialised employees, as well as costly upgrades to the legacy systems, which are still frequently used by mining organisations.

Documentation made simpler

Producing complex documents, such as sustainability reports, permit requests and licensing agreements, takes considerable time and labour. However, access to the accurate information they contain is vital for limiting business risk, and AI technology can be effectively leveraged to ensure that documentation is consistently aligned to the organisation’s existing internal standards and strategies.

iKVA’s software for engineers helps with this challenge; the tool proactively and intelligently suggests company information that is relevant to the document that the worker is creating, in real-time. Seamless integration into the user’s workflow eliminates the need to stop working to search for, and discover, information. Since AI can use entire multi-page documents, such as commercial contracts, as a search query, as opposed to just a few keywords, the results that come back are considerably more accurate and relevant. With this knowledge, engineers can refer to relevant customer details, or use critical information from similar approved documents, saving them time and reducing business risk.

Conclusion

As the mining sector faces increasing pressure to meet the demand for raw materials, the industry is only just beginning to scratch the surface of the benefits to be gained from the data-led insight that AI technology can provide. When firms begin to embrace AI, they will benefit from improved operational efficiencies and margins, better decision making, and valuable business insight to remain competitive in an evolving, post-pandemic landscape.

Author bio

Professor Jon Crowcroft is a founder of iKVA, a Professor at the University of Cambridge Computer Laboratory, and the Chair of Programmes at the Alan Turing Institute.

Read the article online at: https://www.globalminingreview.com/mining/08072022/scratching-the-surface-of-ai/