drones – Air Marshal's Perspective

September 4, 2026

847: DETERRENCE IN THE AUTONOMOUS WARFARE SCENARIO

Article published in the Sep 26 edition of “News Analytics” magazine

The character of warfare evolves alongside technological innovation. Today, another transformative revolution is reshaping global security. The integration of artificial intelligence (AI), autonomous weapons systems, and human-machine teaming into military operations is underway.

Deterrence has traditionally depended on a human adversary believing that the costs of aggression will outweigh its expected benefits. Nuclear weapons made this logic especially powerful by creating the prospect of unacceptable retaliation.

Autonomous warfare, however, is altering the speed, visibility and psychology of military competition. Artificial intelligence-enabled systems can detect, classify, track and engage targets with limited human intervention. In contrast, autonomous drones, loitering munitions, cyber tools, underwater vehicles and defensive systems may operate across several domains simultaneously. The central question is whether autonomous systems will replace conventional or nuclear deterrence or alter its dynamics.

The Transformative Effects on Deterrence

At the core of this transformation is the integration of AI across the full spectrum of military functions, including intelligence, surveillance, and reconnaissance (ISR), targeting, command and control, logistics, and, increasingly, the application of force. Autonomous platforms (ranging from loitering munitions and drone swarms to AI-enabled decision-support systems) operate with varying degrees of independence once activated. Human-machine teaming seeks to combine the strengths of both.

Autonomous systems are particularly suited to denial because they can support persistent sensing, distributed defence, and rapid disruption. Unmanned aerial vehicles can monitor approaches to military installations; autonomous underwater systems can observe maritime activity; ground robots can support border surveillance; and AI-enabled command systems can fuse information from multiple sensors. A networked force may complicate an adversary’s effort to achieve surprise, suppress defences or destroy high-value targets.

Autonomy can enhance capability by allowing military systems to process enormous quantities of data and act faster than human operators. An AI-enabled surveillance network may identify changes in an adversary’s deployment patterns before traditional intelligence systems do. Autonomous platforms can then maintain continuous patrols, coordinate with one another and respond to selected threats without waiting for detailed instructions. Such capabilities may strengthen deterrence by denial.

The importance of denial will increase as military forces become more dispersed. Instead of protecting a small number of vulnerable platforms, states may deploy large numbers of mobile, concealed and networked systems. An adversary would then face a difficult targeting problem: destroying some autonomous platforms would not necessarily turn off the entire force. This resilience can reduce the attractiveness of a first strike.

Autonomy can influence credibility. A state with resilient, dispersed, and relatively inexpensive autonomous systems may be able to respond to aggression even after suffering damage to its command centres, air bases, or naval facilities. Swarms and unmanned systems can generate operational effects without exposing large numbers of personnel to danger. This may make retaliation more politically acceptable and therefore more credible.

Autonomy can also impose operational costs. Defensive systems may use algorithms to detect incoming missiles, drones or aircraft and recommend or initiate responses. If these systems are reliable and their employment conditions are clearly defined, they can reduce the prospect that an adversary will achieve a quick victory. The strategic message becomes: aggression will encounter a persistent, adaptive and difficult-to-suppress defence.

Escalation Dynamics

The most serious challenge is compressed decision time. Autonomous systems can identify and respond to threats faster than human institutions can verify information, consult political leaders or establish whether an incident was deliberate. In a crisis, this may generate a “use-or-lose” mentality. Commanders may fear that delaying action will allow an adversary’s autonomous systems to destroy their own sensors, communications or retaliatory forces.

Machine-speed operations can therefore create pressure for pre-delegation. Political and military leaders may authorise automated responses in advance because human approval would be too slow. Yet pre-delegation carries significant risks. An algorithm may misinterpret a civilian aircraft, a training exercise or a cyber intrusion as an attack. A technical malfunction could trigger a chain of responses that neither side intended.

Autonomous warfare also creates the possibility of machine-to-machine interaction. One state’s defensive algorithm may classify the activation of another state’s autonomous system as hostile. The second state may then respond automatically, producing reciprocal escalation. Unlike human decision-makers, algorithms do not possess political intuition, historical memory or an inherent preference for restraint. They optimise according to programmed objectives and available data. If the data are incomplete or manipulated, the resulting decision may be technically rational but strategically disastrous.

Strategic Stability

Autonomous warfare will have its most consequential impact on strategic stability when it interacts with nuclear forces. AI-enabled systems may improve early warning, intelligence analysis and the protection of nuclear assets. They could help identify suspicious activity and strengthen command-and-control resilience. In this respect, autonomy may reduce uncertainty and support more informed decisions.

The opposite is also possible. AI-enabled surveillance and autonomous strike systems could threaten mobile missiles, submarines, command centres and communications networks. If one state believes that its nuclear deterrent is becoming vulnerable, it may adopt more aggressive readiness postures or delegate greater authority to military commanders. The combination of improved detection, persistent tracking and rapid attack could generate fears of a disarming first strike.

This danger is not limited to actual technical capability. Perception also does matter. A state may respond to what it believes an adversary can do, even if the adversary’s systems are not as effective as assumed. Strategic competition could consequently become unstable through exaggerated assessments of AI-enabled counterforce capabilities. The combination of advanced intelligence, strike systems and missile defence may challenge the traditional assumption that retaliation remains assured after a first strike.

Autonomous systems may also blur the boundary between conventional and nuclear operations. An attack on dual-use command-and-control infrastructure by conventional autonomous weapons could be interpreted as preparation for a nuclear attack. If a state cannot distinguish between an anti-conventional operation and an anti-nuclear operation, it may escalate rapidly. Maintaining clear separation between nuclear and conventional assets, preserving human decision authority and establishing crisis communication channels will therefore become increasingly important.

Implications for India and Regional Security

For India, autonomous warfare is directly relevant to a security environment characterised by contested borders, maritime competition, terrorism, cyber threats, and the possibility of simultaneous pressure from multiple directions. Autonomous systems can enhance surveillance along difficult terrain, improve maritime domain awareness and support the protection of critical infrastructure. They can also strengthen deterrence by denial by making surprise incursions, drone attacks and limited aggression more difficult to execute successfully.

However, technology alone cannot provide deterrence. India would require an integrated architecture combining sensors, secure communications, electronic warfare, cyber resilience, air defence, space-based support and trained human operators. Autonomous platforms must remain connected to a wider command-and-control system that can function even when communications are degraded, or networks are attacked.

Concluding Thoughts

The transition to algorithm-assisted autonomous warfare will not change the basic concept of strategic deterrence. It will mandate a more controlled version of it. One that accounts for machine-speed decision cycles and distributed, ambiguous chains of responsibility. It will also have to cater for an adversary whose calculations are also based on software architectures. Autonomy will create an additional layer of deterrence, one based on persistent surveillance, rapid response, distributed force structures, denial of objectives and the ability to impose costs at machine speed.

As autonomous capabilities continue to grow, policymakers will have the important task of adapting and finding balance during this transition. In autonomous warfare, deterrence will depend not just on cutting-edge technologies but also on ensuring these systems operate within clear, transparent guidelines, robust command structures, well-rounded legal frameworks, and internationally accepted norms. The goal isn’t to slow technological progress, but to ensure that humans, who are ultimately responsible for warfare, still have the power to choose peace.

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Information and data included in the blog are for educational & non-commercial purposes only and have been carefully adapted, excerpted, or edited from reliable and accurate sources. All copyrighted material belongs to the respective owners and is provided only for wider dissemination.

References: –

Institute for Defence Studies and Analyses. (2019). Artificial intelligence and national security: Indian perspectives. Manohar Parrikar Institute for Defence Studies and Analyses.

Rajaraman, V. (2014). Robot soldiers: Artificial intelligence and the future of warfare. Resonance, 19(11), 1037–1048.

Horowitz, M. C. (2016). The ethics & morality of robotic warfare: Assessing the debate over autonomous weapons. Political Science Quarterly, 131(2), 331–351.

Boulanin, V., Saalman, L., Topychkanov, P., Su, F., & Peldán Carlsson, M. (2020). Artificial intelligence, strategic stability and nuclear risk. Stockholm International Peace Research Institute.

Su, F., Wan, W., Saalman, L., & Chernavskikh, V. (2025). Pragmatic approaches to governance at the artificial intelligence–nuclear nexus. Stockholm International Peace Research Institute.

Boulanin, V., Saalman, L., Topychkanov, P., Su, F., & Peldán Carlsson, M. (2020). Artificial intelligence, strategic stability and nuclear risk. Stockholm International Peace Research Institute.

Johnson, J. (2020). Artificial intelligence, drone swarming and deterrence. Journal of Strategic Studies, 43(5), 1–24.
Horowitz, M. C. (2019). When speed kills: Lethal autonomous weapons, deterrence, and stability. Journal of Strategic Studies, 42(5), 764–788.

September 1, 2026

844: AIR DOMINANCE IN A DRONE AGE

Article published in the Sep 26 edition of “Life of Soldier” Magazine

Air power is entering a period of structural transformation. For decades, air superiority was largely defined by advanced fighter aircraft’s ability to defeat enemy aircraft, suppress air defences, and provide freedom of action to other elements of the joint force. The emergence of inexpensive unmanned aerial systems (UAS), autonomous technologies, artificial intelligence (AI), electronic warfare and increasingly networked sensors is challenging that model.

The transformation is not simply about drone proliferation. It is about the emergence of a different architecture for warfare in which crewed and uncrewed platforms, sensors, weapons, communications networks and decision-support systems operate as an interconnected combat ecosystem.

Recent conflicts have demonstrated the operational value of relatively inexpensive drones for intelligence, surveillance and reconnaissance, targeting, precision attack, battle-damage assessment and battlefield communications. At the same time, the increasing use of drones in massed attacks has exposed the economic and operational limitations of traditional air-defence concepts.

For air forces, the strategic challenge is therefore two-sided. They must develop the means to exploit unmanned systems. At the same time, they have to protect their own forces and infrastructure from increasingly capable autonomous and semi-autonomous threats.

Autonomous Combat Ecosystem

The traditional air forces were organised around platforms. Fighter aircraft, bombers, airborne early-warning aircraft, tankers and transport aircraft each performed specialised missions. Their effectiveness depended heavily on their individual capabilities and the quality of the personnel operating them.

The drone age is accelerating a shift toward network-centric and distributed operations. A future combat aircraft may simultaneously function as a sensor, command node, communications relay and weapons platform. An uncrewed aircraft operating ahead of it may extend its sensor coverage. Another one may perform electronic warfare. A third may act as a decoy, while a fourth carries weapons. Ground-based radars and space-based sensors can contribute additional information to the same operational picture.

The objective is not necessarily to replace expensive crewed aircraft with drones. Rather, it is to create a force mix in which high-end platforms are supported and amplified by larger numbers of lower-cost autonomous or remotely operated systems. Such an approach could increase the number of sensors, weapons and potential targets available to a commander without proportionally increasing the number of pilots placed at risk.

Future Air Superiority Models

The future air-superiority model is likely to consist of several overlapping components rather than a single dominant capability.

The Manned-Unmanned Team. Advanced crewed aircraft will increasingly function as command-and-control nodes for uncrewed systems. Instead of sending a pilot into every high-risk environment, commanders can distribute risk among a mixture of platforms. This would allow expensive crewed aircraft to remain focused on missions requiring human judgement while autonomous systems provide additional mass.

Distributed Air Power. Future air forces will need to operate despite attacks on bases, runways and communications infrastructure. Dispersal, mobility and rapid reconstitution will therefore become increasingly important. The relevant question will not simply be whether an air force can generate sorties under ideal conditions. It will be whether it can continue generating combat power after its infrastructure has been attacked.

Persistent Sensing. Small unmanned platforms can provide persistent surveillance at relatively low cost. When integrated with ground, maritime, space and airborne sensors, they can contribute to a continuous picture of the battlespace. This creates a paradox for conventional military operations: greater visibility can improve targeting, but it also makes concealment increasingly difficult. Camouflage, deception, emissions control and mobility will therefore become more important, even as sensor technology improves.

Information and Electronic Superiority. Air superiority increasingly depends on the ability to sense, communicate and coordinate. An aircraft with excellent aerodynamic performance that cannot maintain communications or trust its sensor information may be comparatively less effective. Electronic warfare will therefore become an integral component of air combat rather than a specialist supporting function. The battle for the electromagnetic spectrum will increasingly accompany the battle for physical airspace.

Air Defence Against Swarms

Drone swarms represent one of the most difficult challenges for contemporary air defence because they combine low cost, numbers, flexibility and uncertainty. A conventional air-defence architecture may be highly effective against a limited number of sophisticated threats yet struggle economically when confronted by large numbers of inexpensive UAS. The problem is fundamentally one of cost-benefit comparison.

This makes layered defence essential. The first requirement is detection. Traditional radar must increasingly operate alongside electro-optical, infrared, acoustic and other sensing technologies. The objective is to build a multi-sensor picture that can identify small, slow-moving objects.

The second requirement is automated classification. A large raid can generate more tracks than human operators can efficiently evaluate. AI-assisted systems may therefore become essential for filtering sensor data and prioritising potential threats.

The third requirement is a response mechanism. Different threats require different responses. Expensive interceptors may be used against high-value, sophisticated targets. Low-cost defensive systems can address simpler threats.

Electronic warfare provides another layer. Other technologies, including directed-energy systems, may eventually augment the defensive options where operational conditions permit.

The key principle is that air defence against swarms cannot depend upon a single weapon. It must be an integrated system of sensors, command networks, electronic warfare and multiple classes of interceptors.

Adaptation Trends

Air forces worldwide are fundamentally redesigning how they conceive, plan, and execute air operations. Air forces are increasingly adapting their force structures around three major developments: distributed operations, manned-unmanned teaming and rapid technological adaptation.

Distributed operations seek to reduce dependence on a small number of vulnerable air bases and command nodes. A concentrated air force may possess extremely capable aircraft but still face operational paralysis if its runways, fuel infrastructure, command centres or communications nodes are disabled. Aircraft, sensors, logistics and command functions need to be dispersed across a wider geographical area. This complicates an adversary’s targeting problem and increases the force’s resilience. The concept is particularly relevant in an era of long-range precision weapons.

Manned-unmanned teaming is another trend. A future fighter may coordinate multiple uncrewed systems rather than operating alone. These platforms could undertake sensing, communications, electronic warfare, decoy and other missions while keeping human decision-makers at an appropriate level of control. This approach effectively increases the combat mass available to each crewed platform.

The third transformation is the increasing importance of software and data. Aircraft increasingly depend on digital mission systems, secure communications, electronic warfare databases and AI-enabled decision support. The ability to update these capabilities rapidly can become a strategic advantage.

This creates a different procurement philosophy. Rather than treating an aircraft as a fixed capability acquired for several decades, air forces increasingly need platforms that can accept frequent software, sensor and weapons upgrades.

Analytical Perspective

Extent of Autonomy. Autonomy is likely to be a defining feature of future air warfare, but it should not be confused with the complete removal of humans from the kill chain. The more consequential development is the creation of autonomous combat ecosystems in which machines perform increasingly complex supporting tasks while humans retain command authority over critical decisions. AI can process enormous quantities of sensor data, identify patterns, prioritise potential threats and provide recommendations to operators. Autonomous systems can maintain formations, navigate contested environments, coordinate movement and respond to changing conditions within pre-established parameters. The military advantage comes from speed. Modern battlespaces can generate more information than human operators can absorb. A system that can process multiple sensor feeds simultaneously may identify an emerging threat far faster than a human-centred process.

New Vulnerabilities. Autonomy also creates new vulnerabilities. A sophisticated autonomous system depends upon software, communications, navigation and data. These dependencies create opportunities for cyber-attack, electronic warfare and deception. An adversary may attempt to corrupt the information an autonomous system relies on rather than physically destroying the platform. The future contest will therefore involve not only physical survivability but also algorithmic and informational survivability. Military organisations will need confidence that autonomous systems can continue operating when communications are degraded, GPS or other navigation services are disrupted, and sensor information becomes incomplete or contradictory. The most resilient systems may therefore be those that can operate with degraded connectivity while retaining clear human-defined constraints and mission objectives.

The Industrial Scalability. The drone age is making industrial capacity a key part of military power. A traditional air force measures strength through the number and sophistication of aircraft in its inventory (Quantity and Quality). Future conflicts would require scalability: the ability to rapidly manufacture autonomous systems, replenish losses, update software, produce sensors, and maintain secure communications. Modular design, commercial technology, software-defined systems and rapid manufacturing could allow air forces to shorten development cycles.

The Continuing Role of the Fighter. The rise of drones should not be interpreted as the end of the fighter aircraft. High-performance crewed aircraft continue to provide capabilities that autonomous systems cannot easily replicate across every mission. Human judgement, flexibility, situational awareness and the ability to respond to unexpected circumstances remain important. The change is that the fighter may no longer operate as an isolated platform, but as part of a networked ecosystem. Integrating the fighter into a wider ecosystem would make it more valuable, not less relevant.

Concluding Thoughts

This transformation highlights several important aspects.

Mass is once again a strategic necessity; even though high-end capability matters, affordable mass can impose excessive operational and economic costs on the opponent.

Resilience is as important as performance. Networks, bases and command systems must be capable of absorbing disruption.

Software and data are becoming combat capabilities rather than merely supporting functions.

Neutralising the swarm’s ability to coordinate is more important than physically destroying every individual drone.

Air defence must evolve from a capability to merely intercept platforms to disrupting the networked operating systems.

Human-machine integration will define command and control. The objective should not be unrestricted autonomy but the intelligent allocation of tasks between humans and machines.

Bottom Line

The future of air dominance will consequently be determined less by individual platforms and more by the ability to integrate manned aircraft, autonomous systems, sensors, networks, electronic warfare and air defence into a resilient force.

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References: –

Dhakate S, “Synergistic applications of autonomous UCAVs, swarm robotics and cloud computing in future air warfare”, Journal of Defence Studies, 17(4), (2023).

Khosla, A. “Wings of dominance: The future of air warfare. Air Marshal’s Perspective”. (2026, June 26).

Upadhyay, A. “Counter UAS technologies for India: A prognosis”. Journal of Defence Studies, 16(4). (2022).

Sharma, A. “Counter-Unmanned Aircraft Systems (C-UAS): Future of warfare”. Journal of Defence Studies, 16(4). (2022).

Khosla, A. “India’s tryst with combat drones: SP’s Aviation, 8 (2025).

Khosla, A. “Air power and war endurance in the Indian context”. CLAWS Journal, 16(2), 30–48. (2023).

Scharre, P. “Army of none: Autonomous weapons and the future of war”. W. W. Norton. (2018).

Ansari, H. Z. “Unmanned combat aerial vehicles: Some ethical considerations for the defence applications of AI”. Journal of Defence Studies, 16(4). (2022).

Palkar, D., & Pande, D. “Rethinking ‘air power’ for the governance of unmanned aerial vehicles in India”, Journal of Defence Studies. (2023).

RAND Corporation. “Countering small unmanned aircraft systems”. RAND Corporation. (2022).

July 20, 2026

830: AI-ENABLED COLLABORATIVE COMBAT AIRCRAFT RESHAPING THE AIR POWER

On July 10 this year, over restricted airspace at Edwards Air Force Base in California, an uncrewed aircraft crossed an important threshold in military aviation. An Anduril Industries YFQ-44A fired a live AIM-120 Advanced Medium-Range Air-to-Air Missile at a simulated target after receiving only the command to strike from a human operator. The aircraft itself handled the engagement geometry, target tracking and weapon release, becoming the first American autonomous combat wingman to complete a live air-to-air weapons engagement. The test, supported by the Air Dominance Combined Test Force from Edwards’ 412th Test Wing, marked far more than a successful missile launch.

The event’s demonstration was significant. The autonomy software managed the entire sensor-to-shooter chain. The aircraft managed the mechanics of the engagement while the human retained the firing authority. It was a clear demonstration of how future air combat is likely to be fought. Allowing pilots to command formations of autonomous teammates rather than fly every engagement themselves.

Collaborative Combat Aircraft

An AI-enabled collaborative combat aircraft, also known as an ‘Uncrewed collaborative combat aircraft’ (UCCA) or ‘loyal wingman’, is an autonomous, armed aerial platform designed to operate alongside fighter jets. It can fly in formation, engage threats, and respond to changing battlefield conditions without requiring a ground operator to manage its every move. The main idea behind the CCA is to increase ‘combat mass’ during operations and extend the reach of crewed aircraft.

This is where the concept of Manned-Unmanned Teaming (MUM-T) comes in. In essence, crewed combat aircraft act as the command centre, while the CCA is the operator’s ‘extended arm’. The pilot provides high-level mission objectives, which the CCA then executes at the desired level of autonomy. They can take on specialised roles: for instance, one CCA might engage an enemy target while others jam enemy radar or scan the battlefield and relay real-time data back to the pilot.

The CCAs can even coordinate among themselves, dynamically dividing responsibilities for reconnaissance, electronic warfare, decoy operations, and strike operations. Authority over the use of lethal force remains with the human operator, who is assisted by AI-based decision-support software.

The concept also changes how missions are executed. AI fuses all the sensor inputs (radar returns, infrared imagery, electronic support measures and off-board sensor feeds) into a single tactical picture. Machine-learning algorithms continuously improve target recognition.

All of this is made possible by a sophisticated mission system. These systems allow humans and machines to work together seamlessly as a team. The CCA takes on the cognitive burden of processing data and carrying out routine manoeuvres, allowing the human pilot to focus on high-level tactical decisions.

CCA Necessity

In modern warfare, the side that can process information and act fastest has the advantage. In addition, it’s not just about the first 24 hours of a conflict; it’s also about endurance. The attraction of Collaborative Combat Aircraft is as much economic as technological.

Modern fifth-generation fighters are extraordinarily capable but also extraordinarily expensive to procure, sustain and replace. Every aircraft lost represents not only a financial cost but also years of pilot training. CCAs are designed to generate what air forces increasingly describe as affordable combat mass: multiplying combat power by pairing each crewed fighter with several autonomous aircraft that can undertake high-risk tasks without putting pilots in harm’s way.

This development changes the way air superiority is achieved, especially against a peer competitor. Commanders can distribute tasks, sensors, payloads, and weapons across a larger network of autonomous platforms.

They do not have to rely solely on a relatively small number of exquisite aircraft.

Global Programs

The United States Move from Experiment to Capability Development. The United States has progressed further than any other country in translating this concept into operational capability. The Air Force’s Increment 1 programme selected two aircraft for production: Anduril’s YFQ-44A and General Atomics’ YFQ-42A Dark Merlin. Together, they will form the service’s first operational fleet of Collaborative Combat Aircraft. The pace of their development has been remarkable. Within less than a year, the YFQ-44A progressed from its maiden flight (in October 2025) to a successful live air-to-air missile engagement. The industrial ecosystem is also expanding rapidly. Northrop Grumman, Kratos and General Atomics’ modular Gambit family are all developing related concepts. At the same time, the Air Force has indicated that future increments could follow a collaborative approach with allied participation. The objective would no longer be to build a better aircraft but to field interoperable autonomous combat fleets capable of operating alongside allied air forces.

British Program. Britain’s Royal Air Force has launched the £300 million Storm Fighter programme to develop autonomous aircraft capable of operating alongside the Typhoon, F-35, and, eventually, the Tempest sixth-generation fighter.

Australian Program. Australia’s Boeing MQ-28A Ghost Bat, developed under the Airpower Teaming System, predates the American CCA designation and has accumulated significantly more flight experience than either of the US Increment 1 designs.

Although these programmes differ in design philosophy and industrial approach, they reflect a striking convergence. Independent air forces have reached the same operational conclusion: future air superiority will depend less on ever more expensive crewed fighters operating alone and more on tightly integrated formations of humans and autonomous systems.

Chinese Program. China has pursued a more opaque but equally ambitious path towards AI-enabled collaborative combat aircraft. Rather than treating loyal wingmen as standalone projects, the People’s Liberation Army Air Force (PLAAF) appears to be developing them as integral components of a networked combat ecosystem centred on the J-20 stealth fighter and future sixth-generation aircraft. State-owned Aviation Industry Corporation of China (AVIC) has unveiled several candidate platforms, including the FH-97A, widely regarded as China’s analogue to the US Collaborative Combat Aircraft, as well as concepts such as the Dark Sword and other high-speed unmanned combat air vehicles. Chinese military publications suggest these systems are intended to undertake high-risk missions including forward reconnaissance, electronic attack, suppression of enemy air defences, decoy operations and air-to-air combat, while remaining under human command for the employment of lethal force.

The Indian Approach

On the indigenous side, Hindustan Aeronautics Limited’s Combat Air Teaming System (CATS) envisions a Tejas or future AMCA acting as a “mothership”, controlling multiple Warrior and Hunter drones capable of conducting reconnaissance, suppressing enemy air defences, defending the crewed fighter and striking high-value targets. HAL’s Unmanned Kiran programme offers a complementary, lower-cost route by converting existing Kiran Mk-II trainers into optionally manned aircraft capable of both piloted and autonomous operation.

The longer-term vision extends into the AMCA programme itself. Rather than retrofitting autonomy onto an existing platform, the AMCA is expected to incorporate manned-unmanned teaming from the outset, potentially supported by a future Combat Cloud architecture that links fighters, satellites, AWACS, and autonomous aircraft into a single combat network.

The Bottom Line

Collaborative Combat Aircraft represent the most significant conceptual shift in the application of airpower since the advent of stealth. CCAs would not replace the pilots but redefine their role. Future aviators will increasingly command formations of autonomous formations.

The air force that masters networked integration will enjoy advantages in decision speed, survivability, and operational endurance. The future of air power will belong not to the aircraft with the best individual performance, but to the force that can most effectively combine humans, machines and networks into a single fighting system.

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References: –

U.S. Air Force News, “Air Dominance Combined Test Force conducts first autonomous CCA live missile firing at Edwards AFB”, 2025. https://www.af.mil/, https://www.edwards.af.mil/

Anduril Industries. “YFQ-44A Autonomous Collaborative Combat Aircraft”, 2025. https://www.anduril.com/

General Atomics Aeronautical Systems. YFQ-42A Collaborative Combat Aircraft. (2025). https://www.ga-asi.com/

Future Combat Air System (FCAS), Tempest Programme, https://www.raf.mod.uk/

Boeing Defence Australia. MQ-28 Ghost Bat (Airpower Teaming System). https://www.boeing.com/defense/

Hindustan Aeronautics Limited (HAL). Combat Air Teaming System (CATS) https://hal-india.co.in/

Scharre, P. Army of None: Autonomous Weapons and the Future of War. W. W. Norton. (2018).

RAND Corporation. Studies on Autonomous Air Combat, Human-Machine Teaming, https://www.rand.org/

Center for Strategic and International Studies (CSIS). Airpower and AI Future Combat Aircraft, https://www.csis.org/

Endsley, M. R. (2017). From Here to Autonomy: Lessons Learned From Human–Automation Research. Human Factors.