Beyond its technical capabilities, the rise of Artificial Intelligence has prompted renewed conversations about the very nature of surveillance.
Around a decade ago, when AI solutions first started to make the leap from experimental programmes to practical, real-world deployments, the focus was firmly on what such surveillance systems could do: they could detect threats faster, monitor larger areas, reduce response times and help human operators make quicker decisions. As AI adoption and investment accelerated, those capabilities became increasingly sophisticated leading to real-time identity verification and the rise of integrated command centres that can combine information from hundreds of systems into a single operational picture.
Across the GCC, these technologies are becoming central to ambitious smart city programmes, supporting everything from public safety and critical infrastructure protection to traffic management and emergency response.
Yet, as AI-powered surveillance becomes more deeply embedded in everyday urban life, a different question is beginning to emerge. The greatest challenge is no longer whether the technology works, but whether people trust how it is being used.
The next phase of smart city success will depend as much on governance, transparency and public confidence as it does on technological innovation. Without observing this delicate balance of security, privacy and public trust, even the most powerfully effective AI tools run the risk of alienating the very people they are designed to protect.
Intelligence is only part of the equation
Rather than relying on operators to monitor hundreds of camera feeds, AI can identify anomalies, flag potential incidents and prioritise alerts before escalating them to security teams. When combined with Physical Security Information Management (PSIM) platforms and citywide command centres, these insights enable authorities to coordinate responses across multiple agencies and gain a more complete understanding of events as they unfold.
In the smart city context, the value extends far beyond security alone. Those same technologies can help optimise transport networks, monitor crowd movements during major events, improve emergency response and support more efficient management of public infrastructure.
This convergence of physical and digital systems is one of the defining characteristics of next-generation cities. As connected infrastructure becomes a more common characteristic of these urban environments their ability to “bake in” security considerations grows in line with their intelligence-gathering capabilities
But the collation and usage of greater intelligence also come with a heavier burden of responsibility.
Public trust cannot be an afterthought
For citizens of any country, not just those living in the GCC, the distinction between security and privacy is becoming increasingly difficult to separate.
People generally recognise the benefits of safer public spaces and faster emergency responses. At the same time, they want reassurance that surveillance technologies are being deployed proportionately, that personal information is protected, and that appropriate safeguards exist around data collection and use. These concerns are not barriers to innovation. They are part of what responsible innovation looks like.
Successful AI deployments therefore need to treat governance as a core design principle rather than a regulatory obligation. Privacy-by-design, secure data architectures, clearly defined retention policies and rigorous access controls should be considered as fundamental as the AI models themselves.
Transparency is equally important. When authorities communicate openly about why systems are being deployed, what information is collected, and how oversight is maintained, they create the conditions for greater public confidence. Without that dialogue, even well-intentioned technologies risk misunderstanding or resistance.
Trust, once lost, is far harder to rebuild than any technology platform.
In the Spotlight – GCC deployments that balance the ticket
Across the GCC, AI-powered surveillance is evolving beyond standalone security systems into connected platforms that support public safety, transport, emergency response and wider city operations.
Abu Dhabi's Safe City programme remains one of the region's most mature examples. By integrating CCTV, automatic number plate recognition (ANPR), facial recognition and other data drawn from over 45,000 citywide sensors into a central command platform, authorities have strengthened situational awareness and accelerated multi-agency responses to incidents. The programme illustrates how AI, analytics and command-and-control integration can improve both public safety and operational resilience. Proof of its ability to inspire safety and trust in its citizens as well as in terms of tangible crime and other safety statistics is the fact that Abu Dhabi has been ranked the world’s safest city for the last 10 years in a row.
Qatar demonstrated the potential of AI-enabled urban management during preparations for and delivery of the FIFA World Cup 2022. Intelligent video analytics, crowd monitoring and integrated command centres helped authorities manage millions of passenger journeys across the Doha Metro and key transport hubs while maintaining public safety during one of the world's largest sporting events. Building on that experience, Qatar's TASMU Smart Qatar programme continues to promote AI-driven crowd analytics and intelligent transport systems as part of its long-term smart city strategy.
In Saudi Arabia, NEOM is taking an AI-first approach to city management. Designed around connected digital infrastructure from the outset, the development will integrate AI, digital twins, sensor networks and intelligent command-and-control capabilities to manage everything from mobility and utilities to public safety. Rather than adding AI to an existing city, NEOM is embedding it into the city's operating model from day one.
Meanwhile, Oman is gradually incorporating AI-powered video analytics into its wider Vision 2040 digital transformation agenda. Intelligent CCTV, licence plate recognition and centralised monitoring platforms are increasingly being deployed across critical infrastructure, transport and industrial sites, supporting both security and operational efficiency. Although these deployments are more targeted than some of the region's flagship smart city programmes, they reflect a growing emphasis on using AI to enhance resilience while aligning with national data governance and digital transformation objectives.
Taken together, these examples highlight a broader regional shift. AI is no longer viewed simply as a surveillance tool, but as an operational layer that connects security, mobility, emergency response and city management. As these ecosystems become more sophisticated, maintaining public trust through transparent governance, strong cybersecurity and responsible data management will become just as important as the technologies themselves.
Technology alone will not define smart cities
The conversation around AI surveillance is often framed as a choice between innovation and privacy. In reality, the most successful smart cities will recognise that the two are mutually reinforcing.
Security technologies are most effective when the public has confidence in the institutions that deploy them. Likewise, privacy protections are strongest when they are built into systems from the outset rather than added retrospectively. This requires collaboration that extends well beyond security teams. Technology providers, municipal authorities, regulators, cybersecurity specialists and community stakeholders all have a role to play in establishing clear governance frameworks and shared expectations.
For solution providers, this represents an important shift. Increasingly, customers are not only evaluating the accuracy of AI algorithms or the capabilities of video analytics platforms; they are also asking how solutions support compliance, data governance, cybersecurity and ethical deployment.
Those questions are likely to become even more important as cities continue their digital transformation. However, they are already pertinent to the conversation as the global market for AI in video surveillance alone is valued to reach approximately $4.04 billion to $7 billion by the end of 2026. The GCC is expected to occupy $0.22 billion of that total, making it a key segment of the region's broader $8.4 billion AI technology expenditure.
Ultimately, AI-powered surveillance should not simply be judged by how effectively it identifies threats. Its lasting success will be measured by whether it strengthens the relationship between citizens and the institutions responsible for keeping them safe. Regardless, finding that balance between security, privacy and public trust is not a challenge that any organisation can solve alone. As AI adoption accelerates, events such as Intersec Global offer a valuable platform for governments, municipalities and industry to exchange ideas, showcase best practice and shape the future of responsible smart city security.
In the cities of tomorrow, security, privacy and public trust will not be competing priorities. They will be three pillars of the same smart city strategy.