Securing the Future

How, AI, Cloud and Cybersecurity are shaping the tech landscape

• By Ralph C. Jensen
• Mar 10, 2025

Two security experts sit down with Security Today’s editor in chief Ralph C. Jensen to discuss what they see emerging and changing over the next several years along with how security stakeholders can harness these innovations into opportunities.

Patrik Pettersson is strategic advisor at Axis Communications, working to develop, analyze and implement new concepts, markets and business opportunities. Prior to this role, Pettersson led the future business team and other roles for almost 20 years. He has more than 30 years of experience in IT and technology.

Quang Trinh is the business development manager for Platform Technologies for Axis Communications’ future business team. Trinh focuses on AI, cloud, analytics, and data and has more than 20 years of experience in the security industry.

Let us discuss emerging technology and trends in the security industry. What are you both seeing?

Quang Trinh: The last decade we have seen emerging technologies in the evolution of artificial intelligence (AI), cloud and cybersecurity. Within the last couple of years, we have experienced a huge advancement in a subset of AI focused on computer vision using images from video surveillance. The architecture around computer vision, called deep learning, and advancements around object detection, have elevated the efficiencies of video surveillance and security systems. These AI advancements will impact other devices in this industry as well, but IP cameras and video have been impacted the most.

Patrik Pettersson: I agree that the three biggest accelerations in the security space are AI, cloud, and their cybersecurity. AI requires high-quality data, and to obtain that, you need top tier cameras. Together, cameras and data are essential for AI development. Beyond quality imagery, today’s advanced AI-enabled cameras process data at the edge, providing real-time analysis. They can detect and act, sending only relevant metadata to the cloud, reducing data transfer, optimizing bandwidth and lowering costs. This approach accelerates cloud processing, supports efficient storage, and enhances applications like security monitoring and data analytics by focusing on key events.

The rise of the cloud is driven by the demand for connectivity and the assurance that systems are always online. Connectivity can improve services and facilitate system management. Integrators seek to deliver managed services, while users want confidence that their systems are up and running. Cybersecurity underpins both AI and cloud connectivity, ensuring systems run securely and information remains safe.

Trinh: Another impact of cloud in this emerging tech market is the accessibility it brings—providing customers with easier access to high-end, high-powered technology. The combination of AI-enabled cameras, built on open architecture, and cloud-based functionality offers flexibility and scalability—allowing businesses to adapt as their needs evolve. This approach enables companies to start small and scale seamlessly.

You both mentioned some of the synergies between AI, cloud and security. What else is driving this trend toward technology innovation?

Pettersson: It is no longer our industry proposing technology to the end user—it is the end user and operator coming to us with expectations. This is because today’s consumer technologies work in a friendly way for overly complex things. Accordingly, tech-savvy users have advanced requests, and they expect all technology to be as easy to work with as consumer technology, but – in the security industry – an emphasis on safety, reliability and managing risks is paramount.

Trinh: Thanks to innovations like ChatGPT, advanced AI is now more mainstream. Additionally, since many open-source models from the consumer industry have relied on the cloud and the Internet, the architecture has been proven using publicly available data. The relevance to the security industry lies in the fact that we manage vast amounts of confidential data that have yet to be tapped into. The infrastructure behind these new AI advancements, particularly large language models, is well-suited for companies, solution providers and developers in our sector. With proper controls in place, they can leverage these technologies to manage confidential data securely and unlock significant value. This synergy between cloud, AI and cybersecurity offers substantial opportunities for improving systems and data security.

Another factor driving this shift is that many companies have already been integrating business intelligence (BI) platforms and AI algorithms to analyze their structured data. Now, they are focusing on unstructured data – video, images, audio and sensor data – to derive even greater insights, drive growth and enhance business capabilities.

How can security stakeholders take advantage of these innovations and harness their data in a practical, economical and scalable way?

Pettersson: Referring back to the three pillars of AI, cloud and cybersecurity, it is important to remember that the camera is the genesis of any data-driven solution. The camera, or edge sensor, is increasingly important to providing good reliable data for these innovations to take effect, so the last place to cut corners is at the edge. What is more, it is not going to be economically feasible or scalable for everyone to centrally invest in the processing capability. Users will need distributed intelligence with good devices at the far edge to offload the requirement of that very heavy centralized infrastructure.

You cannot just send everything to the cloud – there is an economy at scale here. There is a point at which the number of cameras or devices becomes too large for the cloud to effectively manage. While the cloud is useful for experimentation and scaling, a hybrid environment becomes crucial beyond this threshold. Of course, there will be a need for small systems to go right from the device to the cloud, and some very secure environments will have to do everything on prem, but we will see the vast majority of our market go to a hybrid environment depending on scale, competence and need for privacy and data control.

Trinh: For systems integrators (SIs) taking a practical approach to this journey, it is crucial to leverage vendor relationship. Ask vendors to provide quantifiable metrics that demonstrate the value of specific technologies to end customers. For example, for AI models that impact computer vision, what are the minimum detection and classification thresholds the vendor’s analytics provide? Additionally, investigate potential integrations into other systems that are not physical security-related, such as enterprise resource planning (ERP), finance & operations and BI systems.

What tools harness new innovations for everyone in this value chain from the developer to the SI to the end user?

Pettersson: From a device manufacturer’s standpoint, we need to easily integrate into the commonly used development environment where developers work. This requires a developer suite with open integrations into third-party systems and platforms including those from mainstream tech players like Google Cloud, AWS and Azure. Key factors for success include open architecture for seamless integration, scalability to meet growing demand, and a strong focus on cybersecurity to protect data and maintain trust. Additionally, supporting the entire channel and value chain ensures that solutions remain implementable, effective and competitive.

In addition, the end user needs, and expects interoperability and collaboration of their workflow with digital collaboration spaces. If we are the genesis of data, we need to facilitate the data to these platforms, because that is where the developers will meet us. There are also tools that manufacturers must provide system integrators--and many are built upon cloud connectivity. These tools can be in the form of deployment and lifecycle management services so SIs can rapidly deploy, onboard and scale devices and then streamline maintenance.

Trinh: When we talk about fostering innovation and development through open platforms and no-code environments, the key focus always comes back to security. All advanced AI tools will leverage and interconnect data, and this is where vendors must make significant investments in the cybersecurity of their devices, while also verifying how others validate the data that they push out. Cameras capture data at its purest form at the far edge, so you need to ensure that the data has been validated and has not been altered. While chain of custody processes is typically managed by larger, higher-level systems, it is beneficial for the industry to have checks and balances throughout the chain.

Are there opportunities for new partnerships and what roles will the SI and security director play in the future?

Pettersson: There are many new players entering the market, so it is crucial to stay cognizant of all emerging trends. The key will be identifying opportunities to collaborate effectively— leveraging those partnerships to strengthen your business and adapt to the changing landscape.

We are seeing a lot of AI and smart applications in the security space that extend into safety areas — addressing challenges such as accidents, PPE requirements, etc. The business efficiency space is also showing its validity by adding safety functions into their applications and drawing on various forms of AI, like computer vision. A notable example is how BMW and Volvo are using computer vision for real-time, production-line analysis to advance efficiency and ensure quality. Those working with business and operational efficiency applications tend to be more agile, and they will easily expand into security through these safety-focused applications. Furthermore, professionals outside the security industry are uninhibited by legacy and are apt to adopt modern development tools. In contrast, and understandably so, those from the security industry are more privacy-conscious and risk-averse.

Another important aspect to consider is that consultants and solution providers — such as Accenture, Deloitte and Ernst & Young — with whom many companies partner to implement BI and operational efficiency applications. They have established relationships with key stakeholders across business units within the client organization, so it is an opportunity for the SI to collaborate with them. While these consultants may already be solid advisors in operational efficiency, it is an opportunity for the SI to take on the role of trusted advisor in the security realm. These consultants, including the independent software vendors they employ, are not really competitors with SIs – because they are not in each other's domain – but they may all start to aggregate around the camera.

From my experience, the security director will rarely allow another application to use their cameras because those cameras have been positioned for security purposes and may not be perfectly angled for a business outcome application. To serve these newer applications, more cameras are necessary, and this is where SIs can look at these trends as bona fide business opportunities.

Trinh: I agree. The opportunity comes from a physical installation, maintenance and servicing standpoint for the SI and that provides value.

Pettersson: That skillset, installation and physical maintenance of the infrastructure, is never going away. Infrastructure must be lifecycle managed and that is where new opportunities exist. I would even say that the price elasticity for a bottom-line business-impacting solution is vastly different from a security solution. And that is a compelling reason for an SI to be involved in computer vision initiatives for their customer. When you use video in an operational efficiency application, you will rarely experience an objection to camera cost, because it gets baked into the overall business outcome driven by the consultant.

Trinh: There are also opportunities for security directors, when it comes to access control, video, and all the data produced, valued and can be leveraged in new ways — not only for security’s sake but also for the greater organization's benefit. Therefore, it is important for SIs to find a seat at the table, involve themselves and amplify the value they bring. There is a huge opportunity in this emerging technology space to be a thought leader, trusted advisor and to branch out of your domain.

Emerging technologies in AI, cloud computing, and cybersecurity are reshaping the security industry, driving innovation and new opportunities. These advancements enhance video surveillance with AI-powered computer vision, enable scalable cloud solutions, and strengthen cybersecurity as a foundation for these technologies. As end users demand seamless integration, stakeholders — from manufacturers to integrators — must leverage vendor relationships, adopt hybrid environments, focus on data value, and ensure cybersecurity. Success lies in embracing these trends, expanding roles beyond traditional security, and contributing to broader organizational goals with innovative, data-driven solutions.