How artificial intelligence is transforming India's fight against one of the world's longest-running insurgencies
Picture this: It's 3 AM in the dense forests of Chhattisgarh. A drone hovers silently above the canopy. Its infrared sensors detect heat signatures moving below. Within seconds, an AI algorithm processes the data, cross-references movement patterns, and alerts security forces 50 kilometers away.
This isn't science fiction. This is happening right now in India's fight against one of the world's longest-running insurgencies.
The big question everyone's asking: Can artificial intelligence finally end what bullets and boots couldn't accomplish in over five decades?
I've spent months analyzing the data, studying the numbers, and researching the latest developments. What I found will surprise you.
Let me start with a number that'll shock you.
But here's where it gets interesting.
Civilian deaths from Naxal-Maoist violence increased by 27% in 2024 compared to 2023, even as security forces launched their most aggressive operations yet.
Yet, something remarkable is happening:
That's a 65% drop in incidents over 10 years.
What changed? Technology.
For decades, India's anti-Naxal strategy was pretty straightforward:
The results? Mixed at best.
Security forces often arrived at attack sites hours after Naxalites had disappeared back into the jungle. Intelligence networks got compromised. Manual surveillance couldn't possibly cover India's massive 96,000 square kilometers of Naxal-affected territory.
Something had to change. And it did.
India is just starting to use AI for national defense. But the early results in counter-insurgency operations are already impressive.
Here's what's actually happening on the ground:
Get this: The CRPF has deployed 51 satellite trackers for real-time tracking of troops in Naxal operations. They've requested 808 additional trackers from the Union Home Ministry.
That's a 1,586% increase in tracking capability.
Each tracker uses GPS, GSM, and satellite communication to provide:
AI algorithms can now do things that would take human analysts weeks to figure out:
Detect unusual forest activity, track infrastructure changes, monitor supply routes
Analyze intercepted communications for threat assessment and operational intelligence
Predict likely ambush locations based on historical data and terrain analysis
Identify and track supply route patterns used by insurgent groups
The government has established over 320 security camps and 68 night-landing helipads in Naxal-affected states.
But here's the key difference: It's not just about quantity anymore. It's about smart placement.
AI models analyze:
This isn't guesswork anymore. It's data-driven strategy.
Modern anti-Naxal operations use a sophisticated tech ecosystem that would make Silicon Valley proud:
In May 2024, security forces eliminated 31 Naxalites in what was called India's biggest-ever anti-Naxal operation. This wasn't just about superior firepower.
The operation used:
The result? Zero casualties among security forces – unprecedented in operations of this scale.
Let me show you the hard data from recent years. These numbers tell a compelling story:
| Metric | Before AI (2010-2014) | After AI (2020-2024) | Improvement |
|---|---|---|---|
| Annual Incidents | 1,080 (2014) | 374 (2024) | 65% reduction |
| Security Force Casualties | 312 per year | 187 per year | 40% reduction |
| Affected Districts | 106 districts | 46 districts | 57% reduction |
| States Affected | 10 states | 7 states | 30% reduction |
These aren't just statistics. Each number represents lives saved, families protected, and communities liberated.
But here's where the story gets complicated.
As security forces become more effective, Naxalites have adapted their tactics. They're targeting civilians they suspect of being informants.
The troubling paradox: Civilian deaths increased 27% in 2024 – the highest spike in recent years.
Better technology is making operations more successful, but it's also making the conflict more brutal for innocent people caught in between.
AI systems make decisions based on patterns and probabilities. But what happens when the algorithm gets it wrong?
Consider these real challenges:
The Evaluating Trustworthy Artificial Intelligence (ETAI) Framework and Guidelines for the Indian Armed Forces were launched by the Chief of Defence Staff in November 2024 – acknowledging these very concerns.
The technology isn't just changing how security forces fight. It's transforming how they think about counter-insurgency entirely.
AI systems now analyze much more than just military targets:
Track economic conditions in affected areas to identify poverty-driven recruitment
Monitor access patterns to essential services and identify underserved communities
Analyze employment data and population movements to predict unrest
Identify areas where development programs could prevent radicalization
This helps authorities address root causes, not just symptoms.
Machine learning models process social media sentiment, community feedback, and local grievances to identify areas where development programs might prevent radicalization.
It's moving from "search and destroy" to "predict and prevent."
India's AI-powered counter-insurgency approach is being watched globally. Countries dealing with similar challenges – from Colombia to the Philippines – are studying these methods.
But India's advantages are unique:
China has invested heavily in AI for internal security, spending an estimated $7.8 billion on surveillance technology in 2023.
India's approach is different – focused on specific conflict zones rather than population-wide monitoring.
This matters because it affects public support and democratic legitimacy of operations.
Despite technological advances, fundamental problems remain:
Political Complexity: AI can't resolve underlying grievances about land rights, tribal autonomy, or economic exploitation that fuel the insurgency.
Terrain Limitations: Dense forests, mountainous regions, and remote villages still provide natural advantages to insurgents that technology struggles to overcome.
Adaptation Speed: Naxalites adapt tactics faster than security forces can deploy new technologies. They've learned to avoid mobile phones, use coded messages, and exploit technology gaps.
Resource Constraints: Advanced AI systems require significant investment. Not all affected states have equal access to cutting-edge technology.
Several emerging technologies could reshape the conflict:
Multiple drones working together to patrol larger areas, share intelligence, and coordinate responses without human intervention.
Systems that analyze historical data, weather patterns, seasonal trends, and local events to predict when and where attacks are most likely.
Unbreakable communication networks that prevent insurgents from intercepting security force communications.
AI processing capabilities that work without internet connectivity, crucial for operations in isolated regions.
As we move through 2025, India's AI-powered approach to counter-insurgency is showing measurable results.
Incidents are down. Security force casualties have decreased. Affected territory has shrunk significantly.
But victory isn't just about statistics.
It's about creating conditions where former insurgents choose development over violence, where tribal communities see the state as protector rather than oppressor, and where technology serves human dignity.
After analyzing the numbers, patterns, and real-world outcomes, several insights emerge:
Technology doesn't replace soldiers and police officers – it makes them more effective. The 40% reduction in security force casualties proves this.
Proactive, AI-driven intelligence is far more effective than reactive operations. The shift from 1,080 incidents in 2014 to 374 in 2024 demonstrates this clearly.
Despite the recent increase in civilian casualties, overall violence has decreased significantly. Better targeting means fewer random encounters.
India's investment in AI for defence is still small – just 1.5% of global AI spending goes to this sector domestically. But early results justify scaling up.
Success comes from connecting multiple technologies – drones, satellites, analytics, and communications – not from any single tool.
The question isn't whether AI can end India's Naxal insurgency entirely – conflicts rooted in decades of grievance rarely have purely technological solutions.
The real question is whether AI can create space for political solutions by making violence less attractive and development more visible.
From my analysis of the data, the early evidence suggests it can. The numbers are encouraging:
But the ultimate test isn't in algorithms or statistics.
It's in the lives of people who no longer fear walking forest paths at night, children who can attend schools without security escorts, and communities where prosperity replaces propaganda.
That's a future worth coding for.
Current AI systems achieve 70-85% accuracy in predicting high-risk areas and potential attack locations. However, human oversight remains crucial for all operational decisions to minimize false positives and protect civilian lives.
India currently spends approximately 1.5% of its defense budget on AI technologies. The government has announced plans to increase this to 5% by 2030, focusing on indigenous AI development and integration.
Insurgent groups have adapted by avoiding digital communications, using natural cover more effectively, changing movement patterns frequently, and exploiting technology gaps in remote areas. This ongoing adaptation cycle drives continuous technological evolution.
The Indian Armed Forces launched the ETAI (Evaluating Trustworthy Artificial Intelligence) Framework in November 2024, which mandates human oversight, transparency requirements, bias testing, and civilian protection protocols for all AI deployments.
Yes, AI is increasingly used for development-focused intelligence – analyzing economic indicators, education access, healthcare availability, and employment patterns to identify areas where targeted development programs could prevent radicalization.
India's approach focuses on targeted, zone-specific deployment rather than population-wide surveillance (like China). Countries such as Colombia, the Philippines, and Nigeria are studying India's model for their own counter-insurgency efforts.