India's Military AI Roadmap: Trust, Enforcement, and Global South Leadership

AI in the military: India's path to ethical and strategic leadership

India has the right intent on military AI. The ETAI framework lays down reliability, safety, transparency, fairness, and privacy as first principles, and bodies like DAIC and DAIPA convene stakeholders around them.

The next move is execution. Principles must translate into enforceable rules, testable systems, and trained teams that can deploy AI with confidence under pressure.

From principles to execution

Look at how the US Department of Defense operationalized Responsible AI: clear principles, a single accountable office, and process guardrails embedded in acquisition and command.

That model shows how to close the last mile-align policy, procurement, and people so that systems are tested, traceable, and controllable. See the DoD's approach to Responsible AI for reference: DoD CDAO.

Close the enforcement gap

India should create a statutory Defence AI Regulatory Authority with the mandate and teeth to ensure compliance across services and vendors. Oversight cannot be advisory; it must be auditable and enforceable.

• Certify: Approve models and systems before fielding; require risk and ethics impact assessments for every procurement.
• Investigate: Conduct incident reviews, mandate corrective actions, and publish lessons learned (with appropriate classification).
• Enforce: Issue binding directives, suspend deployments, and penalize non-compliance across the supply chain.

Two non-negotiables: traceability in every deployed system (from data to decision) and human override at every level of command, with fail-safe defaults when confidence drops or comms degrade.

Build stress-testing and data infrastructure

Adapt AIRAWAT into a defence-grade testbed that can simulate contested, noisy, and adversarial environments. Models must be evaluated under sensor spoofing, electronic warfare, data drift, and degraded GPS-before they ever see a live mission.

• Scenario libraries for high-stress operations: urban, mountain, maritime, and multi-domain coordination.
• Red-team pipelines to probe model brittleness, spoofing susceptibility, and escalation risks.
• Continuous monitoring: telemetry, rollback mechanisms, and post-deployment model health checks.

Invest in people, not just models

Capability fails without adoption. Train commanders, operators, acquisition leaders, lawyers, and engineers on model limits, bias, human factors, rules of engagement with AI, and override discipline.

Executives can accelerate this with role-based learning plans and certification paths. For structured upskilling across functions, explore curated options: AI Courses by Job.

Template leadership for the Global South

Many countries want defence AI but lack governance capacity. India can lead by publishing modular toolkits: ETAI-aligned checklists, data standards, assessment rubrics, and training modules that ministries can adopt and adapt.

Use platforms like the Defence India Startup Challenge to engage startups and MSMEs, pair them with test ranges, and export governance playbooks alongside technologies.

Shape inclusive global norms

At the UN GGE, G20, and BRICS, India can champion pragmatic standards for feasible accountability, human control, and equitable access-standards that resource-constrained states can meet.

Priority topics: shared testing protocols, incident reporting taxonomies, and assurance marks for AI systems. Reference forum: UN GGE under the CCW.

12-month action plan for decision-makers

• Stand up an interim Defence AI Regulatory Authority; define certification gates for all AI procurements.
• Mandate traceability, override policies, and escalation protocols in every requirement document and vendor contract.
• Launch AIRAWAT-Def: a secure simulation and red-teaming platform with mission profiles and adversarial test suites.
• Require ethics and risk impact assessments for fielding decisions; tie approvals to test coverage and fail-safe design.
• Institute role-based training for commanders, operators, and acquisition teams; track certification completion.
• Set incident reporting SLAs, root-cause templates, and model rollback procedures across services.
• Run joint exercises focused on AI-human teaming, override drills, and comms-denied operations.
• Publish an exportable "AI Assurance Kit" for partner nations; pilot with two Global South defence ministries.

Success metrics that matter

• Certification throughput time and compliance rate across programs.
• Test coverage across adversarial scenarios and environmental conditions.
• Override engagement time and proportion of safe-fail transitions.
• Post-deployment drift detection time and incident frequency per flight/hour/patrol.
• Training completion rates and results from red-team exercises.

Why this approach wins

Trustworthy systems reduce operational risk, shorten decision cycles, and improve deterrence. Enforceable governance accelerates procurement by setting clear ground rules for industry.

Most importantly, it gives India an exportable standard: a practical, human-in-command blueprint that partners can adopt. That is how leadership scales across the Global South.