PLAYBOOK ATLASPlaybook Atlas

Mining

AI in mining: explore 37 applications.

Support exploration, inspection and mine planning with traceable operational evidence.

Explore target review, equipment monitoring, dispatch and environmental observations for geoscience, engineering and mine operations teams.

Plan your first AI move See the 37 applications

Where the 37 applications sit

Explore the domains
  1. 13Safety and Compliance
  2. 10Extraction
  3. 7Exploration
  4. 7Market Intelligence and Forecasting
  5. 4Processing

01Why AI now

Why mining is moving on AI, in three figures.

Each figure links to its source.

  1. ICMM injury frequency rate: 2.59 in 2023

    ICMM reported 7,278 recordable injuries and a total recordable injury frequency rate of 2.59 per million hours worked in 2023.

    Source: ICMM Safety Performance Report

  2. AI could cut drilling costs by up to 60%

    The IEA says AI-based geological exploration could reduce drilling costs by up to 60% and increase discovery success rates as much as fourfold.

    Source: International Energy Agency

  3. U.S. mining: 221,000 retirements by 2029

    KPMG reports that about half of the U.S. mining workforce, approximately 221,000 workers, is expected to retire by 2029.

    Source: Society for Mining, Metallurgy & Exploration

How to evaluate a first project

Specify the site, asset and engineering decision. Check sensor quality and operating conditions against field observations, including missed hazards and false alerts. Evaluate recommendations under supervised conditions and retain the site’s established authority for equipment control, safety decisions and operational clearance.

02Capability map

Where mining puts AI to work, domain by domain.

Pick a domain to see its applications. Each one opens a full report.

Inside Safety and Compliance

Applications in Safety and Compliance

What the use cases ask AI to do

Share of the mining use cases, by the kind of work the AI does.

  1. Reasoning

    Analyzes, predicts and decides: scoring, forecasting, classifying.

    47%

  2. Generation

    Creates: text, images, code and other content.

    34%

  3. Agentic

    Acts: plans, uses tools and completes multi-step tasks.

    12%

  4. Perception

    Sees, hears and reads: documents, images, audio and video.

    8%

Under 1% each: optimization.

03Workflow ideas

Ways AI could change the work, in mining.

Atlas groups these applications by the changes they propose to a workflow. These preliminary classifications help you explore ideas; each application still needs a review of its sources and operating requirements.

Workflow categories in this catalog

Share of the 28 applications assigned a category.

How to evaluate an application

  1. Start with a bounded task

    Identify the inputs, the person responsible, and the decision or output the workflow must produce.

  2. Check the support for each method

    Look for source-backed details about the specific implementation, including its limits and human review.

  3. Measure the pilot

    Record the current baseline, agree on acceptance criteria, and test on representative cases before expanding.

Explore applications

04What gets built

The approaches mining uses most, and when to skip them.

Knowing when not to use one matters as much as knowing when to.

  1. 01 · 8 applications

    Time-Series

    Model and forecast time-ordered data to capture trends, seasonality, and temporal dependencies.

    Use it when

    • You need to forecast future values of a metric that is naturally ordered in time (e.g., demand, load, traffic, sensor readings).
    • The target variable exhibits temporal dependencies such as trend, seasonality, or autocorrelation that can be exploited.
    • Decisions depend on how a process evolves over time rather than on static snapshots (e.g., capacity planning, staffing, pricing).

    Skip it when

    • The data has no meaningful temporal order or the order is arbitrary (e.g., shuffled survey responses without timestamps).
    • You only need to predict static attributes or cross-sectional outcomes at a single point in time (e.g., churn at signup) without temporal context.
    • Historical data is extremely sparse, short, or irregular, making it impossible to learn reliable temporal patterns.
    Time-Series, in depth

  2. 02 · 6 applications

    Simulation-Optimization

    Simulation-Optimization combines computational simulation models with optimization algorithms to find optimal decisions under uncertainty and complex constraints. It runs many simulation scenarios to evaluate candidate solutions, using techniques like genetic algorithms, Bayesian optimization, or reinforcement learning.

    Simulation-Optimization, in depth

  3. 03 · 3 applications

    AutoML-Platform

    Managed platform for training and operating predictive models quickly.

    AutoML-Platform, in depth

05The applications

37 mining applications, each with a full report.

The widest first, by the number of use cases each covers. Every report shows what changed, how it works, who has done it and what can go wrong.

  1. Mineral Discovery and Processing Optimization HubThis AI solution uses machine learning, computer vision, and advanced geostatistics to identify high-potential mineral deposits, characterize ore bodies, and optimize mineral processing and energy use across mining operations. By integrating geological, geochemical, geophysical, and plant data, these tools improve targeting accuracy, increase recovery rates, and reduce waste and energy consumption. The result is higher exploration success, more efficient operations, and lower overall cost per ton mined and processed.Silo → Int16 use cases
  2. Mining Hazard Intelligence HubAI Mining Hazard Intelligence continuously analyzes sensor feeds, video, control system logs, and worker wearables to detect hazards, predict incidents, and flag unsafe conditions across mining operations. It unifies risk monitoring from pit to plant, supporting real-time alerts, safer work practices, and proactive policy decisions. This reduces accidents and downtime while improving regulatory compliance and productivity in high-risk mining environments.React → Pred14 use cases
  3. Mining AI Benchmarking SuiteThis AI solution aggregates global data on automation, digitalization, and AI adoption in mining to benchmark companies against industry leaders. It delivers market intelligence, ESG and operational performance comparisons, and adoption roadmaps so mining firms can prioritize investments, de‑risk technology choices, and accelerate ROI from smart mining initiatives.Expert → AI13 use cases
  4. Geochemical Prospecting and Core Scanning SuiteThis AI solution applies advanced machine learning to geochemical, geostatistical, and core-scanning data to detect anomalies, model mineral systems, and prioritize high‑potential exploration targets. By automating mineral targeting, resource characterization, and tailings classification, it reduces exploration risk, shortens discovery cycles, and improves capital allocation across greenfield and brownfield projects.Expert → AI12 use cases
  5. AI Mining Loading AutomationSuite of AI systems that automate and optimize loading operations across open-pit and underground mines, from shovels and loaders to autonomous haul trucks and cargo drones. These tools use real-time data to improve loading accuracy, reduce cycle times, and cut fuel and energy use while enhancing safety in high‑risk zones. The result is higher throughput, lower operating costs, and more predictable, resilient mining operations.Labor → Demand11 use cases
  6. Mining AI Safety GuardrailsMining AI Safety Governance is a suite of tools that designs, monitors, and enforces safety protocols for AI and autonomous systems in mining operations. It unifies risk scanning, guardrails for LLMs, and log-based risk inference to detect unsafe behaviors early and standardize safe responses. This reduces the likelihood of accidents, compliance breaches, and downtime as AI use expands across mines.React → Pred7 use cases
All 37 applications, A to Z

Work with us

The catalog shows what is possible. A sprint decides what you should fund.

Reading every report still leaves the hardest question open: which move is worth funding first, here, given your constraints. That is the sprint: two weeks, fixed scope, and a candid answer either way.

Book a 30-minute callHow the sprint works

Two weeks Fixed scope A candid fit-or-no-fit answer

  1. 01

    Three ranked opportunities

    A decision-ready shortlist scored against value, feasibility, evidence, risk, and time to proof.

  2. 02

    One pilot-ready workflow

    A bounded operating design with actors, handoffs, data needs, controls, and success measures.

  3. 03

    A defensible 90-day plan

    Build-versus-buy guidance, ROI assumptions, risk treatment, sequencing, and executive decisions.

06Rules & standards

Rules and standards to check, with their scope and sources.

Selected US and EU references for these workflows. Applicability depends on jurisdiction, organization, data and intended use. The planning notes are Atlas editorial guidance; they are not official implementation-time estimates or an exhaustive list of obligations.

  1. MSHA surface mobile equipment safety programs

    Law or regulation

    United States · covered mine operators and surface mobile equipment

    Applicable rules require written safety programs addressing hazards, maintenance, technology evaluation and training. Evaluating a new safety technology is different from mandatory adoption of an AI system.

    MSHA: Surface Mobile Equipment Safety Program

    Source checked

    Project planning note

    Integrate the proposed alert or equipment change into the mine’s hazard, maintenance and training program.

  2. NIST Secure Software Development Framework

    Voluntary framework

    United States framework · usable internationally

    The SSDF recommends secure development, software protection and vulnerability-response practices. It is guidance rather than a universal law; procurement or contract terms may incorporate specific requirements.

    NIST: Secure Software Development Framework

    Source checked

    Project planning note

    Use a documented software-change process for operational tools, including recovery and vulnerability handling.

Your next step

Find your first move in mining.

Ask the workspace which move fits your company. Add your size, systems and constraints, and it works from these 37 applications to a plan your team can act on.

Plan your first AI move

Rather talk it through? Book a 30-minute call