That gap undermines American extended deterrence because Washington cannot reassure allies or deter aggressors without accounting for South Asia’s threat calculus. AI arms developments in this region stem from colonial legacies and mistrust of great power intentions, creating a volatile strategic environment.

India’s Governance Innovation in Defense AI

India’s governance model integrates civilian oversight with defense research and ensures ethical deployment of AI. The Responsible AI Certification Pilot evaluated algorithms for explainability before clearance. Its National Strategy for AI mandates ethical review boards for dual-use systems. Developers must document bias-mitigation measures and escalation pathways. Embedding accountability at design phase stabilizes deterrence signals by reducing inadvertent algorithmic behaviors.

The Evaluating Trustworthy AI (ETAI) Framework advances defense AI governance. It enforces five principles: reliability, security, transparency, fairness, privacy, and sets rigorous criteria for system assessment. Chief of Defense, Staff General Anil Chauhan, stressed resilience against adversarial attacks, highlighting the challenge of balancing effectiveness and safety. By mandating continuous validation against evolving threat scenarios, ETAI prevents mission creep and maintains operational integrity under stress.

India’s dual use by design philosophy embeds safeguards within prototypes from inception. This contrasts with reactive models that regulate AI after deployment. Civilian launch-authorization channels separate political intent from technical execution, ensuring decisions remain under human control and reinforcing credibility in crisis moments. Regular red-team exercises involving independent experts further validate system robustness and reduce risks of false positives in autonomous targeting.

Strengthening Extended Deterrence through Cooperation

US-India collaboration on AI verification can reinforce extended deterrence by aligning technical standards and testing protocols. The iCET fact sheet outlines secure information sharing and joint safety trials. Launched in January 2023, iCET has already enabled co-production of jet engines and transfer of advanced drone technologies. Building on this foundation, specialized working groups could develop common benchmarks for adversarial-resistance testing and automated anomaly detection.

A Center for Strategic and International Studies report recommends a trilateral verification cell blending American evaluation tools with India’s ethical reviews. Joint trials of autonomous air-defense algorithms would demonstrate interoperability and resolve. A shared “AI Red Flag” system would alert capitals to anomalous behaviors and reduce strategic surprise. Embedding cryptographically secure logging of decision path data ensures an immutable audit trail for post-event analysis and confidence building.

The INDUS-X initiative, launched during Prime Minister Narendra Modi’s 2023 US visit, integrates responsible AI principles into defense innovation. By aligning standards, both countries ensure AI systems enhance strategic stability rather than undermine it. Expanding INDUS-X to include scenario-based wargaming with allied partners can stress-test ethical frameworks and calibrate thresholds for human intervention under duress. This model can extend under the Quad framework, pressuring authoritarian regimes to adopt transparency measures.

Institutionalizing Global AI Arms Control

A formal arms control dialogue should adopt India’s baseline standards for ethical AI governance. The UNIDIR report calls for universal bias audits and incident-reporting obligations to prevent unintended escalation. Carnegie scholars propose a tiered certification process under a new protocol for autonomous systems within the Convention on Certain Conventional Weapons, requiring peer review of algorithms before deployment. Embedding such certification in national export-control regimes would create global incentives for adherence.

The UN General Assembly has established an Independent AI Scientific Panel and a Global Dialogue on AI Governance to issue annual assessments on risks and norms. This mechanism can evaluate military AI applications and recommend confidence-building measures. Procedural transparency would coexist with confidentiality requirements, balancing security with mutual reassurance. Regular joint workshops on risk-assessment methodologies can diffuse best practices and diffuse mistrust among major powers.

Regional Applications and Future Prospects

India’s responsible AI framework must inspire regional adoption and confidence-building measures. Pakistan and China should engage transparency initiatives to prevent dangerous asymmetries in AI capabilities. Proposed measures include joint research on AI safety, shared performance databases, and collaborative development of detection algorithms.

Successful tests of India’s hypersonic ET-LDHCM system, capable of Mach 8 and a 1,500-kilometer range, underscore the urgency of governance frameworks before fully autonomous weapons deploy. The Quad’s model of Indo-Pacific cooperation provides a template for multilateral norms on responsible AI in defense. Extending these norms to confidence-building measures such as pre-deployment notifications and automated backchannels can reduce the risk of inadvertent escalation.

Looking ahead to the United Nations General Assembly meeting on AI governance in September 2024, American policymakers can leverage India’s experience. Joint verification exercises and an ethical audit regime will establish global norms for military AI. Integrating lessons from ETAI and iCET into the assembly’s resolutions can produce enforceable standards that bind both democratic and authoritarian states. This approach will reaffirm American extended deterrence and help prevent destabilizing AI-driven arms races worldwide.

By demonstrating that ethical AI development strengthens rather than weakens deterrence credibility, India’s model provides both technical solutions and normative frameworks for managing the military applications of artificial intelligence. Sustained international cooperation on these principles is pivotal for securing strategic stability in a rapidly evolving technological landscape.

Vaibhav Chhimpa is a researcher who previously worked with the Department of Science & Technology (DST), India. Views expressed are the Author’s own.

The Artificial Intelligence (AI) Arms Race in South Asia was originally published on Global Security Review.

Agentic AI quickly became a buzzword in the technology industry, drawing the attention of innovators, corporations, and policymakers alike. By combining machine learning, natural language processing, and real-time analytics, agentic AI systems can interpret nuanced data and execute multi-step tasks previously thought to require human intervention. This capability unlocks immense potential across industries, from healthcare and finance to manufacturing and customer service.

However, the rise of this transformative technology is accompanied by profound challenges. The potential for significant job displacement is actual and imminent. Roles that involve repetitive or analytical tasks could be rendered obsolete, leaving swathes of the workforce vulnerable. This shift is sparking resistance from employees and unions concerned about job security and the ethical implications of AI in the workplace.

In the workplace, agentic AI is already making waves. Businesses leverage these systems to automate complex workflows, enhance productivity, and reduce operational costs. For instance, AI agents are being deployed to streamline supply chains, personalize customer interactions, and even assist in groundbreaking research, such as drug discovery and financial forecasting. As organizations increasingly adopt this technology, the workplace transforms, promising greater efficiency and innovation.

However, the rise of agentic AI is not without challenges. Concerns about job displacement, ethical considerations, and security risks have fueled resistance from employees, unions, and policymakers. Trust in AI decision-making and transparency in its operations remain critical issues that must be addressed for widespread acceptance. Moreover, questions about accountability and regulatory oversight are at the forefront of discussions as the line between human and machine decision-making becomes increasingly blurred.

As this trend continues to gain momentum, agentic AI promises to become a cornerstone of the future economy. Its ability to think, learn, and act autonomously offers unprecedented opportunities to reshape industries and redefine the relationship between humans and technology. With careful implementation and robust ethical guidelines, agentic AI could usher in a new era of collaboration between intelligent systems and human ingenuity, setting the stage for innovations yet to be imagined. 

Basics of Agentic AI

Agentic AI represents a significant advancement in artificial intelligence, characterized by its autonomy in decision-making and action execution without direct human intervention. Unlike traditional AI systems that rely on predefined rules, agentic AI adapts to dynamic environments, processes vast data, and formulates strategies to achieve specific objectives. This autonomy enables agentic AI to handle complex, multi-step problems across various industries.

Integrating agentic AI into the workplace transforms business operations by automating intricate tasks and enhancing efficiency. Companies like ServiceNow are embedding agentic AI into their enterprise software to act as control towers for AI-driven business transformations, facilitating seamless system cooperation. Additionally, organizations such as Johnson & Johnson and Moody’s are deploying AI agents for tasks ranging from drug discovery to financial analysis, demonstrating the versatility and impact of Agentic AI in various sectors.

Potential Benefits

Autonomy and adaptability are critical as agentic AI systems operate independently, making decisions and adapting to changing inputs to achieve specific goals without human oversight. Enhanced productivity is vital because agentic AI automates complex tasks, allowing employees to focus on strategic initiatives, thereby increasing overall productivity.

Agentic AI aids industry applications when it is utilized across various industries, including healthcare, manufacturing, and retail, to optimize processes and improve efficiency.

Emerging Concerns

 While promising enhanced productivity and operational efficiency, the integration of agentic AI in the workplace faces significant resistance from various groups due to various concerns. These objections stem from ethical, economic, and cultural implications. Worker advocacy organizations and unions express concern about the potential for large-scale job displacement.

Agentic AI, with its capacity to perform complex, multi-step tasks autonomously, threatens roles that rely on repetitive or analytical tasks, such as data analysis, customer service, and logistics coordination. These groups argue that businesses may prioritize short-term cost savings over employee welfare, exacerbating unemployment and wage stagnation.

Employees in affected industries, such as manufacturing, finance, and retail, fear job insecurity and skill redundancy. Their resistance stems from the perception that companies are deploying AI solutions without clear plans for retraining or upskilling displaced workers. Furthermore, employees often express discomfort working alongside autonomous systems due to a lack of trust and transparency in AI decision-making.

Civil rights groups and ethics committees raise alarm bells over the potential misuse of Agentic AI in surveillance, decision-making, and predictive analytics. Concerns center on the lack of accountability for autonomous decisions, biases in AI algorithms, and the possibility of violating individual privacy rights. These groups argue that deploying AI without clear ethical guidelines undermines trust and could harm marginalized communities disproportionately.

Many managers view agentic AI as threatening their authority and decision-making roles. With AI systems taking on responsibilities like resource allocation and strategic planning, resistance arises from concerns about diminished relevance and influence in organizational hierarchies.

C-Suite Leadership and Industry Best Practices

 Executives, particularly C-suite leadership, often resist large-scale AI adoption due to high implementation costs, cybersecurity risks, and the challenges of integrating AI into legacy systems. They also face pressure to ensure ethical compliance, which slows decision-making processes and creates resistance to adopting agentic AI systems.

As agentic AI reshapes the corporate landscape, C-suite leaders face a dual imperative: embracing this transformative technology, driving innovation, and remaining attractive to top talent while supporting existing employees. Forward-thinking executives recognize that successfully navigating this shift requires technical adoption and a strategic focus on building a resilient and inclusive workplace culture.

C-suite leaders emphasize reskilling and upskilling programs to keep talent coming. By investing in continuous learning initiatives, leaders can empower employees to thrive alongside agentic AI, positioning their companies as industry leaders prioritizing professional growth. Additionally, fostering partnerships with academic institutions and specialized training providers enables businesses to cultivate a pipeline of skilled professionals eager to work with cutting-edge technologies.

Equally important is addressing employee concerns about job security and ethical AI deployment. Transparent communication about how agentic AI is integrated and its benefits to the organization and workforce helps build trust.

C-suite leaders should also protect their organizations by establishing best practices for ethical AI use, including governance frameworks, data privacy safeguards, and inclusive decision-making processes. These measures mitigate risks and position companies as responsible innovators, enhancing their reputation among employees, customers, and investors.

 Ethics and Governance

 In the broader policy perspective, regulatory authorities resist rapid adoption due to insufficient legislation governing AI ethics, accountability, and security. Policymakers advocate for stricter oversight and clearer governance frameworks to mitigate autonomy and data security risks.

While this innovation has much to be praised, consumer resistance stems from a lack of understanding and trust in agentic AI systems. Concerns about transparency in AI-driven decisions—such as pricing models, recommendations, or dispute resolutions—lead to skepticism about businesses that fully rely on such systems.

 Tech Companies Eye Financial Windfall from Agentic AI

 Tech giants are racing to position themselves at the forefront of the agentic AI revolution, recognizing its immense potential to drive financial growth. Companies like Google, Microsoft, and Amazon invest heavily in research and development to create advanced AI agents capable of autonomous decision-making. These firms view agentic AI as a transformative technology that can enhance their existing platforms, open new revenue streams, and cement their dominance in the AI landscape. For instance, enterprise solutions powered by agentic AI are being marketed as tools to revolutionize industries by automating complex tasks, optimizing workflows, and delivering unprecedented efficiency.

Start-ups and established firms compete to attract venture capital funding, focusing on niche applications such as healthcare diagnostics, financial analytics, and personalized customer experiences. These targeted deployments promise significant cost savings for businesses, making them attractive investments. Additionally, tech companies are integrating agentic AI into cloud computing services, offering businesses scalable, AI-powered solutions that can be tailored to diverse needs.

In short, Agentic AI is coming. It will shape industry, government, and the military, and preparing for that future is critical.

Mr. Greg Sharpe is a Fellow and the director of Communications and Marketing for the National Institute for Deterrence Studies and the Managing Design Editor for the Global Security Review. He has 25+ years in marketing and communications with a focus on digital communications, organizational and institutional change, and analysis.  Greg has over 35 years of military, federal civilian, and defense contractor experience in the fields of database development, digital marketing & analytics, and organizational outreach and engagement, technology use case exploration and assessment.

Navigating the New Frontier: Agentic AI’s Promise and Challenges was originally published on Global Security Review.