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Agentic Artificial Intelligence: The Emerging Force Reshaping Automation and Decision-Making

Agentic artificial intelligence (AI), characterized by self-directed systems capable of planning, reasoning, and self-correcting, is an emerging development with the potential to fundamentally alter multiple industries over the next decade. This shift moves beyond traditional, rule-based automation toward autonomous systems that can adapt dynamically in complex environments. Current signals indicate that agentic AI could disrupt strategic intelligence, military defense, critical infrastructure management, and beyond, raising new operational and governance challenges for businesses and governments.

What’s Changing?

Recent developments illustrate a growing focus on AI systems that exhibit agency—defined by autonomous goal-setting, decision-making, and continuous learning capabilities, often described as “agentic AI” (Automation Magazine, 2025). Unlike conventional AI tools that perform narrowly defined tasks within pre-set rules, agentic AI systems could dynamically assess changing situations, formulate multi-step plans, and self-adjust, significantly expanding AI’s scope and effectiveness.

This evolution aligns with breakthroughs such as “infinite, perfect memory” AI systems predicted to unlock new intelligence capabilities (Yahoo Finance, 2025). Moreover, the increasing integration of AI into national defense—exemplified by Northrop Grumman’s AiON counter-drone platform which autonomously engages drone swarms reducing human workload by 98% (Drone Warfare, 2025)—demonstrates agentic AI’s potential to manage complex, simultaneous sensors and effectors in real time with minimal human intervention.

Nation-states like China and the US have designated agentic AI and associated autonomous capabilities as core technologies for the next decade (Firstpost, 2025). China’s “AI Plus” initiative plans widespread adoption across multiple sectors by 2027, deepening AI integration beyond conventional application (TV BRICS, 2025). The technology is anticipated to accelerate transformations not just in defense, but also in energy—such as AI-enabled utility-scale fusion power plants planned for 2026 aiming to power AI workloads sustainably (Just Security, 2025).

In tandem, regulatory frameworks and safety laws targeting AI use underscore recognition of its increased agency and decision-making autonomy. For instance, New York’s comprehensive AI safety law and California’s strategic AI council reflect accelerating efforts to govern AI systems capable of autonomous reasoning and decision-making (Alisa Mustafa Newsletter, 2025). These policies may foreshadow global moves to address risks inherent in agentic AI’s sophistication, particularly regarding ethical and accountability concerns.

Cybersecurity also confronts new challenges with agentic AI. Attackers employing AI-driven reconnaissance and exploitation tools significantly enhance the pace and complexity of cyber assaults (99ten, 2025). This escalation may force agencies to adopt AI-driven defenses capable of automated, adaptive threat mitigation, thus heightening demand for agentic systems in both offense and defense cybersecurity applications (BlackArrow Cyber, 2025; FedTech Magazine, 2025).

Finally, the business landscape hints at agentic AI’s disruptive potential outside defense and cybersecurity. Banking, procurement, and consulting services increasingly leverage AI to improve decision-making quality and operational efficiency (Finextra, 2025; Procurement Magazine, 2026; Hotbot.com, 2025). The shift toward agentic AI could elevate these industries from automated task execution to autonomous strategic decision systems that uncover hidden risks and opportunities in real time.

Why Is This Important?

Agentic AI’s evolution introduces a qualitative leap in automation, promising efficiency gains and operational agility across sectors. Its ability to self-correct and plan autonomously could reduce costly human errors, increase system resilience, and drive innovation in complex, dynamic environments.

In defense, agentic AI could redefine battlefield dynamics by enabling autonomous autonomous platforms to coordinate in real time, manage multi-domain operations, and reduce operator burdens (Drone Warfare, 2025). Such capabilities might shift military advantage towards actors that can deploy agentic AI more effectively while raising geopolitical risks of miscalculation and unanticipated escalation.

In critical infrastructure, agentic AI may optimize energy distribution, data center operations, and smart grid management—examples include AI-powered fusion energy projects which could generate sustainable power tailored to AI’s own growth demands (Just Security, 2025). This may transform energy-intensive sectors enabling them to meet rising computational demands with greater efficiency and fewer environmental impacts.

From a policy perspective, agentic AI raises novel regulatory and ethical questions about trust, transparency, and liability for autonomous decisions. Governing bodies face pressure to craft frameworks that balance innovation incentives with safeguards against errors, misuse, and unintended consequences (Alisa Mustafa Newsletter, 2025).

Cybersecurity considerations are paramount. The potential for agentic AI to power adaptive cyberattacks and advanced defenses triggers a new form of “arms race” where the sophistication of autonomous offensive and defensive capabilities could escalate rapidly (BlackArrow Cyber, 2025; 99ten, 2025). Organizations must prepare for security landscapes dominated by AI-driven adversaries and defenders.

Finally, the broadening reach of agentic AI into commercial sectors—banking, procurement, consulting—suggests emerging disruptions in how decisions are made across organizations. Automated systems capable of self-governance might challenge traditional roles and demand workforce reskilling, with impacts on employment and organizational design (Finextra, 2025; Procurement Magazine, 2026).

Implications

Radical agents of change like agentic AI demand proactive adaptation strategies from all stakeholders:

  • Businesses should monitor the maturity of agentic AI applications relevant to their sectors, invest in data infrastructure upgrades, and explore pilot programs to integrate autonomous decision systems while balancing human oversight requirements.
  • Governments must design anticipatory regulatory frameworks that accommodate agentic AI’s autonomous functions, mandate transparency standards, and develop mechanisms for accountability in complex AI-enabled decisions.
  • Defense agencies will need to assess operational doctrines incorporating agentic AI-driven platforms, devising strategies to mitigate escalation risks while leveraging AI’s force multiplication capabilities.
  • Cybersecurity professionals must gear up for a future defined by AI vs AI engagements, adopting agentic AI-based defenses and fostering international collaboration to preempt harmful autonomous cyber conflicts.
  • Workforces should prepare for AI-augmented roles requiring new skills in managing, auditing, and collaborating with autonomous systems, while organizations address possible labor displacement through retraining.

Understanding agentic AI’s trajectory today may give stakeholders a crucial window to influence its design principles, governance, and equitable adoption, thereby enhancing win-win outcomes rather than a zero-sum race.

Questions

  • Which industries are most likely to benefit first from agentic AI applications, and which may face disruption risks?
  • How can regulatory bodies balance innovation encouragement with safeguarding transparency and accountability in agentic AI decision-making?
  • What governance models could ensure ethical deployment of autonomous AI systems in high-stakes areas like defense and infrastructure?
  • What strategies should organizations adopt to integrate agentic AI while preserving human oversight and preventing overreliance?
  • How might international cooperation evolve to manage the heightened cyber threat landscape driven by autonomous offensive and defensive systems?
  • What workforce development initiatives are necessary to prepare employees for collaboration with agentic AI systems?

Keywords

Agentic AI; Autonomous Systems; Artificial Intelligence Regulation; Cybersecurity Automation; AI Governance; AI in Defense; AI in Energy; Workforce Reskilling

Bibliography

Briefing Created: 27/12/2025

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