BTR: AI Reshapes Intelligence Analysis as Great Power Competition Intensifies

Cormac Meiners, i2 Group

SILVER SPRING, MD, UNITED STATES, August 7, 2025 /EINPresswire.com/ -- The global focus in national security is pivoting away from counterterrorism and toward great power competition with adversaries such as China and Russia, driving significant change in the tools and techniques used in intelligence analysis. This is all occurring as artificial intelligence (AI), once viewed as a speculative enhancement to traditional tradecraft, has evolved into a critical factor for how U.S. intelligence professionals collect, process, and act on massive volumes of data.

In a recent executive vidcast for journalists, Cormac Meiners, U.S. Federal Lead at i2 Group – a provider of intelligence analysis software that helps organizations detect threats and visualize complex data relationships – discussed how the intelligence community is retooling itself for this new era.

“AI is not just augmenting the intelligence cycle,” said Meiners. “It’s redefining the pace and precision with which agencies can respond to threats in real time.”

From Counterterrorism to Strategic Competition

The U.S. intelligence community, Meiners noted, has spent two decades refining techniques for tracking terrorist networks. These methods relied heavily on human expertise, manual link analysis, and long-cycle decision-making. But as state-sponsored cyber-espionage, economic warfare, and disinformation campaigns rise in prominence, the scope and complexity of threats have evolved.

“We’re not just looking at rogue actors with limited capabilities,” said Meiners. “We’re now dealing with nation-states executing sophisticated, multi-domain strategies that play out over years and involve multiple vectors — cyber, economic, informational, and even environmental.”

This shift demands new methods for correlating vast troves of structured and unstructured data — from open-source intelligence (OSINT) and intercepted signals to social media and financial transactions.

AI-Driven Correlation: Speed, Scale, and Context

According to Meiners, AI enables intelligence professionals to filter signal from noise and uncover connections that might remain obscured in massive data environments.

“An analyst might spend days sifting through reports to identify patterns manually. AI cuts that down to minutes — often with greater precision and reliability,” he said.

Modern tools leverage machine learning, natural language processing, and advanced identity resolution to detect relationships between people, places, organizations, and events. This accelerates the intelligence cycle and creates opportunities for proactive — rather than reactive — decision-making.

“Today, it’s about achieving decision advantage,” said Meiners. “How fast can you go from data to insight to action? Increasingly, AI is defining the answer to this question.”

Human-AI Collaboration, Not Replacement

Despite the surge in automation, Meiners was quick to stress that AI will not replace the human analyst. Instead, it functions as a force multiplier.

“The best outcomes happen when humans and machines work together,” he said. “The analyst brings intuition, cultural knowledge, and mission context — AI brings speed, scalability, and pattern recognition.”

This human-in-the-loop model ensures that AI-generated outputs are vetted, contextualized, and operationalized appropriately. In high-stakes environments like defense and intelligence, this collaborative approach is essential to maintaining trust and accountability.

Visual Link Analysis Still Matters

While AI is bringing new capabilities to the table, foundational methods like visual link analysis remain indispensable.

“Visual link analysis is still at the heart of what we do,” said Meiners. “It’s how analysts see the forest and the trees — identifying not only the connections, but the context and consequences behind them.”

Platforms like i2 Analyst’s Notebook now integrate AI-assisted features that automatically surface anomalies, clusters, and key influencers in networks. These tools help analysts build hypotheses and test scenarios with greater speed and clarity.

The Role of Multi-Source Data Fusion

One of the most promising areas of advancement is multi-source data fusion — the ability to integrate disparate data sets into a unified situational view.

“Gone are the days when analysts could work within silos,” said Meiners. “We’re talking about streaming sensor data, satellite imagery, chat logs, financial records, and more — all in one place, all at once.”

AI enables this fusion by providing mechanisms for normalization, tagging, and relevance scoring across heterogeneous sources. This, Meiners argued, is what allows agencies to move from situational awareness to true situational understanding.

Governance and Ethics in AI-Driven Intelligence

While Meiners acknowledged that there are important ethical and governance challenges that come with deploying AI in intelligence environments, the intelligence community is coming to grips with how to address them.

“Transparency, auditability, and bias mitigation are all critical issues,” he said. “Especially when you’re making decisions that could have life-or-death consequences, or when the implications touch civil liberties.”

That is why it is important to build governance frameworks that prioritize auditability, transparency, and ethical alignment.

“These features are increasingly being mandated by policymakers and demanded by oversight bodies, and are therefore present in solutions like i2 Analyst’s Notebook,” he said.

Continuous Innovation Amidst Geopolitical Complexity

Meiners expects the pace of innovation in the intelligence space to continue accelerating as adversaries become more technologically sophisticated.

“We’re in an arms race of information and insight,” he said. “And the winners will be those who can out-think and out-decide the opposition — not just outgun them.”

To that end, i2 Group is investing in scalable, modular AI solutions that can be deployed across diverse mission environments — from battlefield edge deployments to national-level analysis centers.

“We need tools that work at scale, in real time, and under pressure,” said Meiners. “That’s where the future is headed.”

The implications of this transformation are not limited to the defense sector. As private-sector firms — from financial institutions to critical infrastructure operators — grapple with cyber threats and geopolitical risk, many are looking to intelligence-grade tools to harden their own analytic capabilities.

“Think of insider threats, supply chain monitoring, or global risk assessment,” said Meiners. “These are use cases where the line between national security and commercial security is blurring.”

According to Gartner, more than 60% of large enterprises will adopt AI-enhanced threat intelligence platforms by 2027 as part of their cybersecurity resilience strategies.

As global tensions rise and threat vectors multiply, the role of AI in intelligence analysis is becoming foundational. Leaders like Cormac Meiners and organizations like i2 Group are at the forefront of this evolution — championing tools that empower analysts to make faster, smarter, and more ethical decisions in an increasingly dangerous world.

“The mission hasn’t changed,” said Meiners. “It’s still about protecting people, assets, and values. What’s changing is how we do it — and AI is a big part of that transformation.”

Click Here to read the full Q&A based on this Interview.

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