Digital modernization is shaped by numerous interacting variables, including how and why organizations make decisions, leadership preferences, technical considerations, and individual user behavior. System vulnerabilities can be introduced or worsen because of a single variable or a combination of factors. How organizations manage processes, systems, risks, and people play an integral role in preventing, identifying, and mitigating vulnerabilities. Understanding the relationship between organizational risk and technical complexity is essential as the US modernizes its nuclear, command, control, and communications (NC3) architecture. Networked and software-dependent components are vulnerable to cyber exploitation by adversaries. NC3 modernization represents a complex multi-layered cybersecurity challenge. As information security researcher Bruce Schneier noted in 1999, “complexity is the worst enemy of cybersecurity.” Moreover, no system can be completely “cyber secure.”

Organizational decision-making and leadership preferences play an integral role in how information technology solutions are implemented, from procurement to cybersecurity and everywhere in between. Modernizing the nuclear triad and the NC3 infrastructure relies on a small number of defense contractors to develop and deliver key technologies. Moving from an analog to a digital environment means third-party software will play an increasingly influential role in NC3 operations. Cybersecurity and risk management researcher Daniel Geer warned that organizations can become trapped by what he calls the “software monoculture,” meaning organizations assume significant risk when they depend on a narrow set of providers or a single provider for critical systems. Security flaws that originate in one part of an organization could spread to others using the same software, potentially cascading into widespread disruption and prolonged system downtime. Private companies, including defense contractors, could also be exploited first, providing a pathway for threat actors to attack government systems.

Several variables influence decision-making inside military organizations that can introduce system vulnerabilities. Nuclear scholar Scott Sagan notes that military organizations are rigid, approach issues through a military-centric lens, hold “parochial interests,” and engage in intense internal competition. The number of military services involved in NC3 modernization has produced disparate program management efforts and disjointed business requirements, which can introduce system vulnerabilities. Risk aversion “within the NC3 community” is another complicating factor, keeping some stakeholders entrenched in legacy systems they perceive to be more secure. Rather than confront modernization risks directly, leaders may make design trade-offs that jeopardize the security of NC3 upgrades and the development of future technologies. Furthermore, leaders with an inadequate understanding of organizational management, cybersecurity, and the cyber-nuclear nexus will undermine trust and contribute to poor decision-making across the enterprise.

The nuclear triad and supporting NC3 infrastructure involve human processes and technical systems working together to manage the inherent complexity. Organizational sociologist Charles Perrow argued that large organizations, like the military, do not fully understand the solutions they implement to manage complex systems. Perrow identified two structural criteria within complex systems that will eventually lead to accidents: interactive complexity and tight coupling. Interactive complexity involves interrelated systems whose interactions are not fully known. Tightly coupled systems operate under time-dependent requirements and have minimal margin for error. Accident or system exploitation through cyber operations can occur along three vectors: analog-to-digital modernization, ongoing maintenance of legacy analog and digital systems, and the design and implementation of future technologies. Cyber operations could target tightly coupled processes, potentially precipitating an accident within the NC3 architecture. Offensive operations could disrupt, degrade, or deny critical communication nodes and early warning capabilities. Threat actors may alter or destroy information systems and data used by NC3 stakeholders, including the President. The intersection between normal accidents theory and exploitable system vulnerabilities cannot be understated.

Stakeholders should consider the following options to manage organizational risk effectively. First, create a national center of excellence dedicated to advancing cyber-nuclear scholarship and skills training. Meeting the technical and policy challenges affecting NC3 systems and nuclear deterrence more broadly requires a highly specialized workforce. Cyber capabilities and risks will continue to evolve rapidly as the underlying global security situation becomes increasingly tenuous. Consolidating research and training under a single entity can streamline education delivery and talent acquisition pipelines. The center would be funded and staffed through a partnership among public, private, and military academic institutions, think tanks, and private-sector stakeholders. Second, establish an independent board of civilian experts to oversee US nuclear modernization efforts. A lack of organizational governance threatens the safety, security, and long-term viability of broader efforts to modernize the US nuclear enterprise. Establishing a group of experts independent of Congress and the Department of War (DOW) is essential to ensure accountability and manage organizational impediments. The board would issue reports to Congress and make them available to the public every six months. The board would interface directly with congressional, military, and private-sector stakeholders to remediate issues. It may be worthwhile appointing the authors of the 2023 Strategic Posture Commission report to this board, as they have the expertise to conduct a governance mandate.

Nuclear deterrence is a “zero‑failure mission.” Therefore, the systems that enable the US nuclear triad must be resilient to cyber threats. Organizational risk and technical complexity create exploitable system vulnerabilities; coupled with nuclear weapons, this is a dangerous combination. Failing to understand this complexity and address these challenges undermines the credibility of US nuclear deterrence strategy, including extended deterrence commitments. In an era of intensifying Great Power competition against two sophisticated cyber-capable nuclear peers, the United States must remain steadfast in confronting these challenges or risk potentially catastrophic consequences.

Nathan A. Heard is an independent researcher and doctoral student in the Defense and Strategic Studies Program at Missouri State University, focused on deterrence issues and emerging threats. He holds a master’s degree in defense and strategic studies and a graduate certificate in countering weapons of mass destruction from Missouri State. Heard is the author of the graduate thesis “A Novel Deterrence Strategy: Denial Through Space and Cyberspace” (2025) and the article “The Coming Crisis with North Korea” (2026). The views expressed are his own.

Managing Organizational Risk in Nuclear Command, Control, and Communications (NC3) Modernization 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.