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TRACK24 UNVEILS ATLASNXT TO REDEFINE GLOBAL DUTY‑OF‑CARE AND RISK INTELLIGENCE

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Exclusive interview with Andrew McInerney (CEO) and  Ebad Abid (Head of Product), Track24

Can you introduce your company to us? What does AtlasNXT do?

AtlasNXT, from TRACK24, is a duty-of-care location services and communication system. So, it enables a business to know where its people are and relate those people to the risks and other information they might face and then enables them to make decisions and communicate about to ensure the duty-of-care of their teams.

So, what inspired the founding of AtlasNXT and how does its mission differ from other duty-of-care and operational communication platforms?

TRACK24 was formed in 2004 as a location services company in high-risk environments, principally using satellite locations and satellite communication devices. And that remains one of our key differentiators, the ability to integrate satellite communications and satellite devices from any of the competitors. Since then, the world and the technology has moved on.

And in the last five years, we at TRACK24 have integrated lots of different, divergent bits of our software into AtlasNXT as a single software offering. And that provides those location services, not just to high-risk environments, but to GSM-capable and GPS-capable devices across any environment. So, where risk moves across place and time, then any business can use this, not just those ones in high risks as well.

So, it helps with travel risk management, it helps with precision communications to people, it reduces the amount of noise compared to the amount of signal that individuals get. So, precision information to the right people at the right time.

In your view, what is the biggest misconception organizations still have about modern duty-of-care technology?

We’ve come from a high-risk environment, from the most high-risk, and bring with us that sort of ethos of protection. Many organizations have come from a travel risk management environment, and therefore that tends to be diary predictions of where your diary says you’re going to be traveling that day, rather than precision location. And so, a lot of people bring with them the expectation that they get a generic travel risk management update, rather than something precise for their own movements, which changes as their own movements change.

So, the adaptability of a live tracking system enables that. The other key differentiator is the ability to maintain privacy. I’ve done that quick demonstration of the system.

So, the individual knows when they’re able to be seen by their operation, by their operators, by their employer, and when they’re not, so they can maintain their privacy. And they only lose their privacy through consent. They press a button on the app and say, track me, or check me, overwatch me, or I’m in a panic mode, or by event, and they go inside a geofence, which their employer has put up on the map.

It might be their location, it might be a risk environment, and even then, the app tells the individual that you’re now visible to your operator. So, I think it’s key, the privacy element, and the live tracking, rather than any predictive element. Coming to the privacy part, AtlasNXT emphasizes privacy-first location-based communications.

How do you balance delivering critical information with user privacy concerns?

One of the challenges is, as you have said, is if you give the user the control, you won’t be able to actually support the user, because they’ll just switch it off. So, what we do is, we allow the system to share information, but we manage privacy through the visibility of the data that’s transferred, as opposed to switching it on and off, as most people do.

Because once you switch it off, the person’s MIA, and you can’t do anything to support them. They’re not going to get any notifications; we’re not going to know where they are. But if the system is always sharing, if their device is always sharing a location, or any form of notification with our system in the background, then we’re always able to reach them in the event something goes wrong.

The way we manage privacy is we essentially make them invisible, and they become visible by consent or event. So, one of the main things in data protection laws is legitimate interest. So, you should only ever have access to somebody’s information if you actually need it.

And so, you either give consent, that you can use my location data, or there’s a legitimate interest, such as they are in a potential area where there is a risk to them. At that point, we can reveal that location, and therefore, we’re always in control.

AtlasNXT integrates geofencing, precision messaging, and real-time operational intelligence. How do you see these capabilities?

Geofences themselves have evolved. First, they just used to be sort of a digital perimeter. Now, we’ve introduced smart geofences, which essentially allows you to track people coming in and out of that perimeter. What we also do is see what impacts that perimeter.

So, we have various intelligence feeds we integrate with, and you can see if a particular perimeter is impacted by that. Now, with AI, you can also then say, is that piece of intelligence relevant to the perimeter I’m monitoring? When you’re integrating with data providers, you’re probably getting a few thousand events a day. As humans, we can’t consume that much information, or if we can, we can’t comprehend what it means.

With the power of AI, we can summarize information and allow it to provide clarity. We can also use it to generate reports and deliver trend analysis.

For example, it can extrapolate that over X period of time, we’ve had X types of risk, which gives us the ability to predict future risk. So, if there is, for example, a civil conflict near a particular geofence, you’ll find that there are X amount of panic alarms pressed in the vicinity.

So, what AI will be able to do is allow us to forecast whether, you know, because of this event, we can expect this many people to be at risk. Which sends out early warnings automatically without human intervention being required.

From our engagement with customers, it’s clear that they want to maintain an operator in the decision loop. So, our approach to AI is that it does the heavy lifting, but only suggests options to the operator. This ensures a human remains in command and makes the critical decisions.

AI is powerful and can save a great deal of time, but we’re not at the point where life-and-death security decisions can be handed to a machine. It performs the groundwork while a human operator remains in control. One of its strengths is pattern recognition.

It can say to the operator, ‘we’re noticing this, do you want to take this action?’ It’s a co-pilot, not a pilot. It also improves efficiency, as AI can process large volumes of information instantly, reducing response times. The earlier an organisation can intervene, the safer its people are. AI summarises the situation, and the operator decides whether and how to act.

And how important was InterSec for you and this region, Middle East, for your company?

We’re headquartered in London with two subsidiary organizations in the Emirates and a country office in Iraq. The region is hugely important. It’s where we originated as a species and as a company. So, we started in 2004 in Baghdad, and we’ve always maintained a large presence in Iraq, Kurdistan and across the Middle East.

The world isn’t getting any easier. The world is not getting any less risky. The world is not getting any more certain. Risk is spreading and becoming quite unpredictable whether you’re the president of an independent nation or an independent nation that belongs to somebody else. Risk is coming to you around the globe.

Our services become more and more important and more relevant globally. The region of the Middle East is important because I think it’s a region that understands security in a very central way.

It was our first attendance at InterSec. We’re a software provider. From what I’ve seen so far, there’s lots of hardware providers.

And that means there’s lots of potential partners for us. We can integrate any of their systems into our system and make access control useful for decision support which is what we’re here to do.

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UAE Enterprises Shift Focus from AI Adoption to Measurable Business Value

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Exclusive interview with Shadi Hatoum, Regional Director MEA at Tealium

The UAE is moving quickly from AI experimentation to deployment. What do you think will determine which organizations actually turn adoption into measurable business value?

The organizations that create measurable value will be those that connect AI to a clearly defined business decision, then give it the right data and operating model to support that decision.

The UAE has already built significant momentum. Boston Consulting Group found that 42% of UAE organizations qualify as AI Leaders, while 37% have reached the scaling stage of AI maturity. The next test is whether that maturity translates into sustained outcomes.

Deploying a model is not the same as changing how a business operates. AI needs trusted, consented, and real-time context around customer identity, behavior, intent, and journey stage. It also needs clear ownership, measurable objectives, and teams that understand how to use the output.

From my perspective, data readiness and organizational adoption will be the two biggest differentiators. The organizations that can put reliable context in front of AI at the moment of decision, and embed the resulting insight into daily workflows, will be best positioned to turn adoption into measurable value.

How much of the current gap between AI ambition and AI impact comes down to fragmented or outdated customer data?

A significant part of the gap comes down to data readiness, although technology alone is not the whole answer. Most organizations do not lack data. Their challenge is that the data is fragmented, difficult to interpret, or unavailable when a decision needs to be made.

Historical data provides useful depth, but AI also needs data in motion. It needs to understand what a customer is doing now, what has changed, what the customer has consented to, and whether the signal belongs to the correct individual or account.

Tealium’s Future of Customer Data research found that 88% of organizations consider real-time data important to achieving business objectives. That is important because an AI system working from yesterday’s profile may produce a technically valid recommendation that is no longer relevant.

The real opportunity is to create a trusted context layer that connects identity, behavior, consent, and intent, then makes that context available to models and decisioning systems while the customer interaction is still taking place.

Does agentic AI create a new governance problem for enterprises, particularly when agents are acting on customer data without constant human intervention?

Agentic AI does not make the principles of governance entirely new, but it raises the stakes and increases the speed at which controls need to operate. When an AI agent can move from recommendation to action, governance can no longer be treated only as a periodic policy or review exercise. It needs to operate within the data flow and decision process itself.

Enterprises need clear controls over which data an agent can access, the purpose for which it can use that data, how identity and consent are verified, which actions it is authorized to take, and when a person must review or approve the outcome.

The key question is not only whether an agent can access a piece of customer data. It is whether the agent should use that data for this customer, for this purpose, at this moment.

That requires trusted data, current consent, auditability, defined action limits, and clear escalation paths. As autonomy increases, accountability needs to become more precise, not less.

Which sectors in the Middle East do you think are furthest ahead in using real-time customer data and AI together effectively?

From my experience across the region, telecommunications and travel, hospitality, and tourism are among the most active and promising sectors because they generate frequent customer signals and have a clear need to respond in the moment.

In a recent discussion with the Chief Commercial Officer of a major telecom operator in the region, we talked about growth as filling a bucket while also stopping the leaks. Acquisition fills the top, but poor service, irrelevant engagement, and unresolved friction allow value to escape through churn. Sustainable growth requires both attracting new customers and protecting the loyal customer base already in the bucket.

This is where AI-supported decisioning can create real value. Trusted, consented, real-time behavioral data can help an operator recognize changes in usage, service issues, digital engagement, and signs of churn. The next best action may be to resolve a problem, recommend a more suitable plan, position a bespoke package at the right time, or avoid making an offer when the customer first needs support.

The objective is not to push more offers. It is to improve relevance and timing. That can support retention, strengthen loyalty, and create opportunities to grow average revenue per user, or ARPU, by responding to what the customer needs in that moment.

Travel, hospitality, and tourism have a similarly strong opportunity. The customer journey moves from inspiration and research to booking, arrival, the in-destination experience, and loyalty. Each stage creates different needs. A traveler facing disruption needs assistance, while a guest already at a destination may value a timely, personalized experience or service.

These sectors show why hyper-personalization at scale depends on trusted, consented behavioral data in motion. The value comes from giving AI initiatives the current context they need to choose the next best action for that specific moment.

At AI Everything Abu Dhabi 2026, what are the biggest changes you are seeing in the conversations enterprises are having compared with a year or two ago?

The biggest change is that enterprises are no longer asking whether they should adopt AI. They are asking how to move it into production, connect it to measurable outcomes, and govern it at scale.

A year or two ago, many conversations centered on experimentation and individual use cases. Today, the questions are more operational. Leaders want to understand how AI will work with their existing data, how agents will receive current customer context, how decisions will be controlled, and how value will be measured beyond a successful pilot.

I am also hearing much more emphasis on adoption. Organizations recognize that a model does not create value by itself. Teams need clear use cases, practical training, shared measures of success, and confidence in the data behind the recommendation.

The conversation has therefore moved from AI capability to AI readiness. That includes the quality of the data foundation, the governance around it, the ability to make decisions in real time, and the people and processes required to turn those decisions into action. For me, that is a sign that the market is becoming more mature and more focused on sustainable business impact.

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AI Is Expanding the Cyberattack Surface and Redefining Resilience

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Exclsuive interview with Fady Richmany, Corporate Vice President and General Manager, Emerging Markets at Commvault

Integrated Media is at GISEC Global Dubai 2026 with Fady Richmany, Corporate Vice President and General Manager, Emerging Markets at Commvault

How is AI changing the attack surface for organizations in the region?

AI is crucial for digital transformation, so we are not debating the importance of AI. I think the UAE is one of the most advanced countries when it comes to adopting technology. The Dubai Government has also announced plans to use agentic AI extensively in the coming years

However, AI comes with a significant amount of data and introduces new types of identities. We are no longer dealing only with human identities but are increasingly dealing with robotic and AI-agent identities that can access data and systems. This creates additional complexity and consequences from an identity and security perspective.

At the same time, AI-powered attacks are another major concern. In the past, a hacker typically needed to be highly technical. Today, with AI, launching sophisticated attacks can become much simpler.

So, AI is important, but it needs to be utilized properly and governed effectively. There needs to be a balance when organizations and large enterprises adopt these technologies.

Why are threat actors increasingly targeting backup and recovery environments?

Backup and recovery are the last line of defence.

When a company is compromised, one of the first things it needs to do is access its backups to recover its data and operations. Hackers understand this. If they want their attacks to be effective, they also need to target the backup environment.

This is where companies like ours, along with many others in the industry, play an important role in making sure that backups remain clean, protected, and safe so organizations can recover when an incident occurs.

How does identity management need to evolve as AI agents and autonomous workloads multiply?

Agentic AI is putting additional pressure on IT because it is creating many robotic identities.

We have also seen attacks where AI has been used with little or no human intervention. This creates an additional security burden, which means these identities need to be properly protected.

Our approach focuses on the recovery side. Organizations need to use the appropriate security technologies available in the market to protect their environments and ensure that the right identities have access to the right resources.

But we also need to address what happens when an identity is compromised. How do you recover the environment? How do you recover the identity infrastructure? That is becoming a very important topic.

What does Cloud Unity offer beyond separate point solutions?

Cloud Unity brings together identity, security, and operational resilience. We combine people and processes and work closely with many of the leading security technology partners in the market.

We integrate information from different technologies and provide identity resiliency to help protect organizations from both sides of the problem.

We also have something called ResOps, or Resiliency Operations. It is a methodology for how organizations should operate. We believe organizations need to educate their people, keep them aware, and make sure everyone understands their role during a crisis. They also need to modernize their processes.

All of this comes together to make sure the environment remains resilient and productive. And this is not a one-time exercise but has been continuously tested – time and again.

How does ResOps help organizations move from reactive security to a more measurable and proactive approach?

In the olden days, we used what we called backup drills. This is particularly common in banking and government, where people would come together every quarter and check whether the backup was working.

But that approach is no longer enough.

Recovering data is not simply about recovering the information. During a cyberattack, you need to recover clean data and ensure that the environment you are restoring is safe. That means organizations need continuous testing. You have to align people, processes, and technology and make testing an ongoing activity.

When a compromise happens, everyone needs to know their role – Who has access? What are the steps that need to be followed? Who is responsible for each action? The ultimate objective is to be able to recover a clean copy of the data and get the organization back into operation as quickly and safely as possible.

What will the new Center of Excellence in Abu Dhabi focus on, and how will it support the UAE’s digital transformation goals?

One of our strategies is to align closely with local authorities, and work together with them. We work very closely with the UAE Cyber Security Council and have developed this initiative together with them.

The purpose of the Center of Excellence is to bring innovation to the region. It will be a center for innovation, with R&D and technology development taking place in the region. It will also be a center for developing local talent. We are partnering with universities and aim to train young Emiratis in areas such as cyber resilience and cyber defense. It will also be a center for awareness.

I would quote what Dr. Mohamed Al Kuwaiti said- the responsibility for cyber defense does not rely on one technology, one individual, or one government. It requires the entire community to work together to fight cyber threats. That is the purpose of the center. It is to bring all these elements together, support the cybersecurity community, and give back to the region. We want to create awareness, talent, and innovation.

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THE AGENTIC AI ERA: RETHINKING CYBER RISK, GOVERNANCE AND RESILIENCE

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Exclusive interview with Bilal Baig, Vice President, Solutions Engineering, Trend Micro

What is Trend Micro showcasing at GISEC Global 2026, and how does it reflect the shift towards proactive, AI-powered cyber risk management?

We are highlighting our unified cybersecurity platform, Trend Vision One, which is designed as a proactive security platform.

AI has shifted how organisations, governments and agencies respond to threats. It is no longer enough to take a reactive approach. Security needs to become proactive, particularly given the speed at which AI is developing.

We are using AI in two ways. First, we are using AI internally within the platform to identify vulnerabilities. Second, we are using AI to protect our customers.

At GISEC, we are showcasing agentic SIEM, agentic SOAR, XDR capabilities and our full-stack AI security platform. We are also highlighting new developments in AI security, including how AI can help protect against vulnerabilities and zero-day attacks.

How has Trend Micro evolved in both using AI for cybersecurity and securing AI systems themselves?

AI has increased the speed at which organisations can move into production. At the same time, both defenders and attackers now have access to AI. The key question is how organisations manage that risk and how quickly they can protect customers and predict an attack before it becomes a breach.

We created Cybertron, an industry-first cybersecurity LLM, and we also work with frontier AI providers including Anthropic, OpenAI and Microsoft. We use frontier AI to consume vulnerability information, while our customers have access to our broader AI security capabilities.

We are now moving into the agentic AI era, where AI agents can make decisions on behalf of humans. These agents can access systems, emulate human behaviour and perform tasks independently.

For us, agentic AI security comes down to four key areas: visibility, observability, governance and response.

Visibility means understanding what is happening. Observability goes a step further by understanding what an action performed by an AI agent could cause. Governance determines how those agents should be controlled, while response is about deciding what action to take.

What new security and governance challenges arise as agentic AI moves from experimentation to enterprise deployment?

One of the biggest questions is whether an agentic AI system should be treated like a human identity or like software.

A software system needs updates, patches and maintenance. A human has an identity, a job and defined responsibilities. Agentic AI combines elements of both.

Organisations therefore need to give AI agents an identity, establish guardrails around what they can do and ensure that someone within the governance structure is responsible for their actions.

If an agent is given additional responsibilities, organisations need to understand how those permissions are managed and eventually removed when they are no longer required.

In an agentic AI environment, every communication and action needs to be considered within a governance framework. Organisations need to look at every interaction, understand its potential outcome and decide whether an action should be allowed to proceed or stopped.

What does the rise of autonomous or rogue AI agents mean for cybersecurity?

We are entering a world where rogue AI agents can become highly sophisticated systems. This means security cannot focus only on whether the underlying AI model is secure. Organisations also need to examine the actions those models are performing and whether those actions could create a cybersecurity problem.

The attack surface is now changing in terms of both scale and sophistication. Attackers have AI capabilities that can help them launch sophisticated attacks much faster.

This means organisations need AI on the defensive side as well. Security solutions need to match that speed and sophistication while ensuring that governance frameworks prevent malicious outcomes.

How should organisations manage the growing number of vulnerabilities identified by AI?

AI and frontier models can identify vulnerabilities that may not have been visible previously. An organisation that once had to manage 30 or 40 patches could suddenly face thousands.

It is not realistic to address every vulnerability in the same way. Organisations need to prioritise based on the risk and importance of their environment.

They need to identify which vulnerabilities are most important for their particular environment rather than simply looking at a vulnerability’s CVE score.

This is where cyber risk exposure management becomes important. Organisations need to understand the risk, the asset and the identity involved, and then decide which security gaps are most important to close.

How is the UAE’s cyber threat landscape changing as AI adoption and digital transformation accelerate?

The UAE is at the forefront of AI transformation. We are seeing multiple initiatives from the UAE Government, including AI training for government employees, government-focused AI initiatives and the introduction of AI education in schools.

There are already AI systems operating within government, so the digital transformation of AI in the UAE is moving forward rapidly.

Our focus is on helping secure that transformation. As AI systems become more interconnected and increasingly make decisions, the attack surface becomes more complicated.

A layered security approach is therefore important, from the large language model and API access through to the decision-making processes of AI agents, while monitoring for malicious activity.

What should organisations consider around security controls and data sovereignty as they expand their cloud and AI environments?

There is sometimes a misconception that moving to the cloud automatically means an organisation is secure. When cloud computing emerged, we often talked about security as a shared responsibility.

The exposure changes as organisations move from on-premises environments to the cloud and then into AI. The same threat can look very different across these environments.

Organisations need to consider where their assets and identities are located and how they will manage security across these different layers.

For highly sensitive environments, including air-gapped networks and systems involving critical data sovereignty, security may need to remain on-premises. In some national security environments, data cannot be processed outside the country.

Trend Micro has Vision One Sovereign and Private Cloud, which extends our AI cybersecurity unified platform to air-gapped and sovereign environments, with a focus on data sovereignty, localisation and air-gapped deployments.

What role does government-industry collaboration play in strengthening national cybersecurity preparedness and resilience?

Government-industry collaboration is extremely important. Working with organisations such as the Cybersecurity Council, national CERTs and government security services brings together different perspectives.

As governments move towards greater use of AI, industry can help secure that journey while governments provide the regulations and governance frameworks needed to manage these systems.

Without close collaboration, it becomes difficult to create policies that reflect what is actually happening in the private sector.

The objective should be to support innovation without overlooking cybersecurity. Technology is developing extremely quickly, particularly AI, so cybersecurity needs to be considered alongside that innovation.

Government and the private sector need to work together to make sure that while organisations remain at the forefront of technological development, they do not overlook the cybersecurity implications.

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