6 Key Technology Trends Affecting the Security Sector in 2025

As we approach the new year, it’s time to explore the key technology trends set to influence the security sector over the next 12 months. The pace of change remains rapid, with some trends evolving from previous years and others emerging, or even resurfacing, after some time.

One major trend is the growing application of AI in our sector. We’ve highlighted new considerations that will need to be addressed moving forward. Additionally, national and regional legislators will strive to keep pace with technological innovation, focusing on AI, cybersecurity, privacy, and resilience in critical infrastructure. While we haven’t called this out as a specific trend, it’s no less important, and organizations will need to respond to evolving regulations.

Within these trends lie significant opportunities for the sector, offering enhanced capabilities, increased flexibility, greater efficiency, and added value for customers.

Hybrid Solutions: The Foundation for Freedom of Choice

Hybrid architectures—those leveraging edge, cloud, and on-premise technologies—have become the default choice for security solutions in recent years. The drivers behind this choice will vary for each organization, influenced by technological, legal, ethical, and governance concerns. The rapidly changing environment demands freedom of choice, and hybrid solutions offer flexibility to store, view, or manage video and devices, or select the preferred instance.

Whether driven by emerging local regulations or concerns over data control, cost, or energy efficiency, hybrid solutions will continue to offer the greatest flexibility, allowing organizations to scale systems to meet specific needs.

AI Evolution Alongside AI Efficiency

AI development continues at a breakneck pace. Deep learning technologies are already integral to most security analytics solutions, while newer generative AI technologies are maturing rapidly. While there is still a lot of hype in certain areas, real-world applications of generative AI are now available in the security sector.

Each step in AI’s evolution brings new opportunities, but also raises ethical, legal, and corporate considerations. Generative AI models require substantial compute power, raising questions about balancing AI costs—both financial and environmental—with its value. Efforts are underway to reduce model sizes without compromising quality. The increased use of AI further reinforces hybrid architectures as the standard.

AI’s various “flavors”—from deep learning-based object recognition to generative AI—demand or benefit from different applications at various stages of the value chain. Generative AI can assist operators in interacting with security systems using natural language, but for the foreseeable future, it will require significant processing power. Meanwhile, deep learning-based analytics, such as enhanced object recognition, can be performed within surveillance cameras themselves.

Ultimately, as models improve, there is a significant opportunity to enhance the efficiency and effectiveness of security operations. Algorithms will increasingly understand scenes and react to anomalies based on diverse input data, including radar, audio, and other sensors, enabling more proactive capabilities and valuable long-term insights.

Beyond Safety and Security Becomes Real

The application of advanced technologies like computer vision, audio, and access control is expanding beyond traditional security and safety use cases. AI-driven improvements in object recognition enable faster and more effective incident responses. Moreover, data from various sensors—including video, audio, and environmental inputs—can support applications beyond security, driving operational efficiency and business intelligence.

This trend fosters greater collaboration across organizations. Technology designed for one use case can often be leveraged for other business operations. For example, data from security cameras can be analyzed to enhance customer or employee experience, sustainability, or operational processes.

The pace of development is astounding, with hardware vendors that encourage open, collaborative ecosystems of developers and system integrators bringing the greatest value to customers.

The “Rebirth” of Image Quality

Though it may seem counterintuitive, a renewed focus on image quality is an emerging trend. While image quality has always been important, the shift is in how visual sensor images are used. With advances in analytics and AI, high-resolution images are now analyzed more frequently and often by computers instead of humans.

Better image quality leads to improved results in object recognition and enhanced data creation. High-resolution images enable better analytics, even in complex environments like large crowds, busy intersections, or fast-moving production lines. Single cameras can cover larger areas, reducing the need for multiple units. Operators will be automatically alerted to areas needing attention, improving response efficiency and effectiveness.

Long-Term Value Through Software Support

While hardware quality has improved year after year, the key to maximizing a device’s value lies in ongoing software support. Quality hardware can last for years, but its functionality—particularly in terms of cybersecurity—depends on continued software updates.

Vendors committed to supporting software throughout a product’s lifecycle will provide greater value. High-quality hardware, combined with comprehensive software support, offers a more effective and efficient long-term solution, enhancing the total cost of ownership.

Technology Autonomy to the Customer’s Benefit

At its core, the role of technology vendors is to meet customer needs. Innovations must align with customer priorities, whether in safety, operational efficiency, business intelligence, cybersecurity, or sustainability. Vendors with greater autonomy over their core technologies—such as designing their own semiconductors—are better positioned to tailor products to customer needs and ensure “secure by design” solutions.

This control allows vendors to mitigate risks from global supply chain disruptions, ensuring they meet customer requirements when needed. Companies traditionally seen as software vendors are increasingly designing their own semiconductors, particularly in AI. Axis Communications has been ahead of this trend, developing our own system-on-chip, ARTPEC, for over 25 years.

The article is authored by Johan Paulsson, CTO of Axis Communications, Mats Thulin, Director of Core Technologies at Axis Communications, and Thomas Ekdahl, Engineering Manager at Axis Communications.