Mining operations team deploying Physical AI through controlled implementation waves, progressing from supervised use cases to domain-level autonomy and cross-domain orchestration while monitoring safety, performance, and operational continuity.

Talks that move

Implementing the Agentic IROC

Deploying Physical AI in controlled waves so the operation builds trust, demonstrates value, and advances toward cross-domain orchestration without compromising safety or continuity.

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Autonomy is not a go-live date.

WHY THIS "AGENTIC IROC IMPLEMENTATION" CHALLENGE?

Agentic solutions can prove value in pilots and still fail to change operations. Scaling requires reliable data, safe authority, workforce adoption, integration, ownership, and governance with progress measured by evidence rather than the calendar alone.

Key benefits

Scale authority at the speed of trust

The implementation model advances decision by decision and domain by domain, increasing autonomy only when performance, readiness, safety, and value support it.

Build around decisions, not technology waveS

Scale the operating model by critical decision and domain.

Let evidence unlock more autonomy

Increase authority only when trust and performance justify it.

Keep the business case in the loop

Track realized value through every implementation wave.

Treat overrides as learning signals

Improve through exceptions, outcomes, playbooks, and policy reviews.

How NTT DATA helps

01

Put ownership around autonomy

Mobilize an autonomous operations office with executive mandate, product ownership, governance, safety authority, architecture custody, value tracking, and change leadership.

Mining operations team overseeing an active mine where people, haulage, processing, and operational systems progressively work together as the organization advances toward greater autonomous coordination.

02

Build the production foundation

Establish the agent platform, integrations, semantic context, observability, AgentOps, cybersecurity, AI safety, simulation, and support model.

Mining engineers and operators working together in the field to validate the first supervised autonomous capabilities before expanding their operational authority.

03

Commission the first decisions safely

Use offline validation, simulation, shadow mode, supervised recommendation, bounded action, and rollback-tested release.

Mining operations specialists coordinating mine, processing, maintenance, and logistics activities as autonomous capabilities expand across multiple operational domains.

04

Expand only where evidence supports it

Grow domain agents and master orchestration as operating maturity increases.

Experienced mining professionals overseeing a mature operation where higher levels of autonomy operate selectively under continuous human governance and operational oversight.

05

Make adoption part of the system

We don’t treat implementation as a technical handover. We operate, learn, retrain people, review value, and expand autonomy decision by decision.

Mining leaders and operations specialists reviewing operational performance together to determine whether autonomous capabilities are delivering sufficient safety, trust, and business value to justify further expansion

Mining operations professionals overlooking an active open-pit mine where increasingly autonomous operations are introduced progressively under continued human supervision.

Proven impact

Controlled progression. Earned trust. Autonomy that grows with evidence.

Results that matter

Implementation maturity builds across defined horizons rather than a single production cutover.

Establish H1 readiness

Platform foundation, change plan, supervised copilots, selective local agents, baseline overrides, and safety validation.

Accelerate through H2

Domain agents at scale, selected master orchestration, learning loops, and faster replanning.

Sustain at H3

Selective higher autonomy, continuous governance, skills retention, ESG integration, and replication.

Measure value and trust continuously

Override rate, mean time to replan, safety exceptions, target-autonomy attainment, and realized value versus business case.

Scale autonomy only as fast as evidence and trust allow.

Build a controlled path from first decisions to sustained orchestration.

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