{"id":59402,"date":"2026-02-22T10:06:46","date_gmt":"2026-02-22T07:06:46","guid":{"rendered":"https:\/\/geoconversation.org\/news\/artificial-intelligence-in-mining-how-to-stop-just-observing-and-start-managing\/"},"modified":"2026-02-22T10:06:46","modified_gmt":"2026-02-22T07:06:46","slug":"artificial-intelligence-in-mining-how-to-stop-just-observing-and-start-managing","status":"publish","type":"news","link":"https:\/\/geoconversation.org\/en\/news\/artificial-intelligence-in-mining-how-to-stop-just-observing-and-start-managing\/","title":{"rendered":"Artificial Intelligence in Mining: How to Stop Just Observing and Start Managing"},"content":{"rendered":"\n

At the largest African conference, Mining Indaba 2026, experts discussed the shortage of equipment or raw materials. The main topic was something else: why, with an abundance of digital systems and sensors, production in quarries is still unstable. OES company, developing AI solutions for mining<\/a>, presented her view of the problem and a way to solve it.<\/p>\n\n\n

Modern quarries are crammed with sensors. There is a lot of data, performance indicators are calculated automatically. But as soon as there is a deviation from the plan, chaos begins. Dispatchers and shift supervisors are drowning in correspondence and calls, trying to figure out what to do first. Priorities are blurred, responsibility is blurred, reactions are late. Management turns into manual fire extinguishing.<\/p>\n\n\n

OES proposes to build a live control loop in real time. Their platform based on artificial intelligence<\/a> does not show beautiful graphs after the fact, but helps make decisions here and now.<\/p>\n\n\n

Each role in production has its own interface. The dispatcher sees which deviation requires immediate intervention, who to connect and what can be postponed. The shift manager receives information about who is assigned tasks, whether reaction standards are being met, and where the process is stuck. Management sees systemic problems: repeated failures, low discipline and lack of resources, which they previously learned about after the fact.<\/p>\n\n\n

Equipment operators receive directives directly to their terminals. They don’t have to wait for the dispatcher to shout on the radio or send a message. The system itself sets the task and controls execution.<\/p>\n\n\n

At the exhibition, OES representatives interacted with dozens of operators and contractors working with coal, gold, copper, diamonds and other minerals. The picture is the same everywhere. Digitalization has already reached the industry, but it has not added real controllability.<\/p>\n\n\n

The main result of participation in Mining Indaba is the understanding that the market is ripe. African companies no longer ask Why do they need artificial intelligence?<\/a>. They want to know how to implement it and when to get results. Demand has shifted from abstract talk to practical solutions that work quickly and do not require years of IT reforms.<\/p>\n\n\n

For OES, this is a signal for active international expansion. The window of opportunity is open, and the company intends to offer the market a tool that turns the chaos of data into a clear rhythm of production.<\/p>\n\n\n

Source: @nagora_coalanalytics<\/p>\n","protected":false},"excerpt":{"rendered":"

At the largest African conference, Mining Indaba 2026, experts discussed the shortage of equipment or raw materials. The main topic was something else: why, with an abundance of digital systems and sensors, production in quarries is still unstable. OES company, developing AI solutions for mining , presented her view of<\/p>\n","protected":false},"author":12,"featured_media":45802,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_seopress_robots_primary_cat":"","_seopress_titles_title":"Artificial Intelligence in Mining: How to Stop Just Observing and Start Managing","_seopress_titles_desc":"At Mining Indaba we discussed why digitalization does not save us from failures. Find out how an AI platform can help you manage your shift in real time.","_seopress_robots_index":"","_seopress_analysis_target_kw":"","footnotes":""},"categories":[11],"tags":[319,321],"class_list":["post-59402","news","type-news","status-publish","has-post-thumbnail","category-it","tag-avtomatizacziya-i-robotizacziya","tag-iskusstvennyj-intellekt-v-geologii"],"acf":[],"pbg_featured_image_src":{"full":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii.webp",1404,772,false],"thumbnail":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii-150x82.webp",150,82,true],"medium":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii-300x165.webp",300,165,true],"medium_large":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii-768x422.webp",768,422,true],"large":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii-1024x563.webp",1024,563,true],"1536x1536":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii.webp",1404,772,false],"2048x2048":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii.webp",1404,772,false],"bricks_large_16x9":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii-1200x675.webp",1200,675,true],"bricks_large":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii-1200x660.webp",1200,660,true],"bricks_large_square":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii-1200x772.webp",1200,772,true],"bricks_medium":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii-600x330.webp",600,330,true],"bricks_medium_square":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/02\/platforma-ii-600x600.webp",600,600,true]},"pbg_author_info":{"display_name":"Yulia Frolova","author_link":"https:\/\/geoconversation.org\/en\/author\/giulia-nikolaevna\/","author_img":false},"pbg_comment_info":" No Comments","pbg_excerpt":"At the largest African conference, Mining Indaba 2026, experts discussed the shortage of equipment or raw materials. The main topic was something else: why, with an abundance of digital systems and sensors, production in quarries is still unstable. OES company, developing AI solutions for mining , presented her view of","_links":{"self":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/news\/59402","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/news"}],"about":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/types\/news"}],"author":[{"embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/comments?post=59402"}],"version-history":[{"count":0,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/news\/59402\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/media\/45802"}],"wp:attachment":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/media?parent=59402"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/categories?post=59402"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/tags?post=59402"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}