Tech Interviews
NETWORKS MUST EVOLVE BEFORE AI CAN SCALE
Rohit Chowdhary, Head of Advanced Consulting Services at Nokia, sat down with The Integrator to share insights into the company’s vision for enabling the AI Supercycle. He outlined how Nokia’s end-to-end portfolio spans everything from AI-ready connectivity and energy-efficient 800G data centre networking to intelligent, self-optimising home Wi-Fi experiences powered by AI.
A key focus of the discussion was Nokia’s shift from strategic advisory to real-world execution through its dedicated Automation Excellence Practice, helping operators translate ambitious transformation roadmaps into measurable outcomes. The conversation also highlighted the growing importance of integrated, intelligent and secure networks that can support rising AI workloads, eliminate infrastructure bottlenecks and unlock tangible business value, while maintaining the highest standards of security, privacy and resilience
Could you begin by telling us about your role at Nokia and the journey that brought you here?
I lead Nokia’s Advanced Consulting Services business across Europe, the Middle East and Africa. My journey with Nokia spans nearly seventeen years, beginning at a time when consulting was largely focused on network transformation initiatives. Over the years, I have worked closely with operators around the world on transformation programmes, analytics adoption, customer experience management and digital modernization.
As the industry evolved, so did our consulting focus. Following the Nokia and Alcatel Lucent merger, we established what is today known as Advanced Consulting Services. The organization now spans several domains, including Security, Business monetization, Cloud and Technology transformation, Autonomous Networks, and Data & AI.
More recently, we launched an Automation Excellence Practice. The idea was simple. Customers often appreciated our strategic blueprints but needed practical expertise to implement them. Today, we have specialized engineers who combine telecom expertise, AI capabilities and software development skills to turn strategic visions into real automation pipelines, AI-driven workflows and production-ready use cases. Our role is to help customers move from concept to measurable business outcomes.
Nokia is often associated with connectivity, but the company is increasingly talking about AI readiness. How does Nokia’s infrastructure portfolio support this transition?
AI is creating what we describe as an AI Supercycle. It is transforming everything from data centres and cloud infrastructure to network architectures and edge computing. Supporting this shift requires a complete ecosystem rather than isolated technologies.
Nokia’s portfolio addresses this across multiple layers. On the network side, we continue to innovate in radio technologies, including AI-RAN capabilities developed alongside strategic partners such as Nvidia. We also have a strong optical networking and IP portfolio that enables the high-capacity connectivity required between data centres, edge locations and cloud environments.
One area that excites me is our innovation in data centre networking. We are introducing highly efficient coherent optical technologies and advanced switching platforms that significantly reduce infrastructure footprints while improving performance and energy efficiency. These innovations are becoming increasingly important as organizations invest in AI factories, AI grids and large-scale inference environments.
Beyond connectivity, we also provide intelligent automation layers through our Autonomous Networks platforms, enabling operators to manage complex, multi-vendor environments more efficiently and intelligently.
What are some of the biggest infrastructure bottlenecks you see operators and enterprises facing as AI adoption accelerates?
One of the biggest challenges is understanding that AI infrastructure is not just about compute power. Organizations often focus heavily on GPUs and processing capabilities, but connectivity can quickly become the limiting factor.
You can deploy the most powerful AI infrastructure available, but if the network cannot support the required data movement between racks, data centres and edge locations, performance suffers. This is where intelligent networking becomes critical.
At Nokia, we are helping customers design what we call AI-ready connectivity. This includes high-capacity optical networking, intelligent routing and the seamless interconnection of compute environments. As AI workloads become increasingly distributed, the ability to move data efficiently becomes just as important as the ability to process it.
On the consumer side, Nokia has been showcasing AI-driven Wi-Fi management capabilities. How does this improve the end-user experience?
The home network has become far more complex than it was a few years ago. Consumers expect flawless connectivity across multiple devices, applications and services.
Our AI-enabled Wi-Fi solutions continuously monitor network performance and user experience. They can identify coverage gaps, detect congestion, analyze interference patterns and even recommend or automatically implement corrective actions.
The goal is to create a self-optimizing network environment where many issues can be resolved autonomously before they impact the user. This reduces support requirements for service providers while delivering a more consistent and reliable experience for customers.
The Middle East is witnessing an unprecedented surge in data centre investments. How do you see this shaping Nokia’s opportunities in the region?
The Middle East has emerged as one of the most dynamic markets globally for AI infrastructure investments. Governments and enterprises are actively investing in sovereign AI capabilities, advanced data centres and digital ecosystems.
This creates significant opportunities, not only for Nokia but for the broader technology industry. The success of these initiatives depends on having secure, scalable and efficient connectivity between compute resources, cloud environments and end users.
Our role is to help customers build these foundations. Whether it is data centre interconnectivity, optical networking, intelligent routing or autonomous operations, Nokia’s technologies are designed to support the scale and performance requirements of AI-driven economies.
As data volumes continue to grow, security and data sovereignty are becoming increasingly important. How is Nokia addressing these concerns?
Security is deeply embedded into Nokia’s strategy and innovation roadmap. As a European technology company, trust, resilience and security have always been fundamental principles in how we design and operate our solutions.
While we continue to invest heavily in AI innovation, we are equally focused on strengthening security capabilities across our portfolio. This includes advanced network security architectures, AI-driven threat detection and preparations for future technologies such as quantum-safe networking.
We are actively engaged with industry bodies, standards organizations and ecosystem partners to help define the next generation of secure digital infrastructure. As AI becomes increasingly pervasive, security must evolve alongside it, and that is an area where Nokia continues to invest significantly.
Looking ahead, what excites you most about the future of AI-driven networks?
What excites me most is the convergence of AI, automation and connectivity. Networks are evolving from passive transport layers into intelligent platforms that can learn, adapt and optimize themselves.
The future will be defined by autonomous operations, AI-native networks and real-time decision-making at scale. Organizations that successfully combine these capabilities will unlock entirely new business models and levels of operational efficiency.
For us, the opportunity is not just about deploying technology. It is about helping customers transform the way they operate, innovate and create value in an increasingly AI-driven world.
Tech Interviews
THE AGENTIC AI ERA: RETHINKING CYBER RISK, GOVERNANCE AND RESILIENCE
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.
Tech Interviews
Building the AI Backbone: How the Middle East Is Rethinking Data Centres
Dave Philp, Chief Value Officer at Bentley Systems, discusses how AI, digital twins, clean energy and integrated infrastructure planning are shaping the next generation of data centres across the UAE and wider Middle East.

The UAE and Saudi Arabia are investing heavily in AI and digital infrastructure. From your perspective, what makes the Middle East such an exciting market for the next generation of data centers?
One of the most substantial transformations we are witnessing is the transition of the UAE to a programmatic mindset in terms of data centre development, which makes it a desirable market for the next generation of data centres. We usually consider countries such as UK in terms of building or developing a singular project, but it is impressive that the UAE has been prioritising data centre corridors and digital infrastructure instead of focusing on individual hyperscale data centres.
While speaking to colleagues across the UAE and the Middle East region, I found it interesting as the UAE is constantly investing in the infrastructure needed to achieve its ambitious AI goal. This further includes larger digital ecosystems, sovereign cloud capabilities, and energy infrastructure. I believe it is not just about creating more data centres; it is also about establishing an infrastructure that can help achieve the ambitious economic vision of the UAE. It is important to understand that establishing a robust digital infrastructure is key to power AI, smart city initiatives and industrial diversification. This strategy is part of a much larger national economic plan. By combining digital aspirations with investments in energy and physical infrastructure, the UAE is successfully laying the groundwork for an AI-powered economy. We can also witness that the UK is making efforts to move towards a future economic model, which can motivate other countries to follow suit.
- Power is a growing challenge for AI data centers. How can the Middle East balance rising AI demand with its clean energy goals?
I believe that the UAE has secured a unique position in this regard as any capital investment in AI infrastructure needs to be strategized according to clean energy goals. As the Minister of Energy and Infrastructure highlighted, AI-enabled optimisation can coordinate data-centre demand with grid capacity, renewable generation, storage and shared cooling infrastructure. It can also identify opportunities to recover and reuse waste heat where local conditions make that technically and commercially viable.
This, in my opinion, will define the UAE’s next generation data centres. Integrated planning, which takes into account how data centres interact with renewable energy, solar opportunities, district cooling, battery storage, and demand management, will be prioritised over isolated engineering decisions. These factors need to considered by the UAE, not just in terms of separate workflows.
As I mentioned, these will be common across the region, but we are also witnessing unique models in the UAE. We are seeing a shift from isolated projects towards phased campuses and data-centre corridors supported by shared power, water, cooling and connectivity infrastructure.
- As AI data centers require more cooling, how can operators build facilities that are both efficient and responsible with water use?
Yes, it is interesting. It is similar to not having a favourite child, like you do not want operators to choose between energy and water, but how to optimise both to create a resilient thermal management system. However, it is my belief that it should start the very beginning of the project, investment level, thinking about it as a water ecosystem. It is not just about water on site, but about the sourcing within it.
Additionally, I believe that there is a lot of innovation within data centres as well. Now, when it comes to water-stressed environments, usage of reclaimed water should be considered. On the other hand for high-density AI workloads, direct-to-chip and other liquid-cooling approaches can remove heat closer to the source. Closed-loop systems recirculate coolant rather than continually consuming it, although the overall water and energy performance still depends on how the facility rejects heat to the external environment. Also, we must understand how it will integrate within the local recycling infrastructure within there as well.
As a result, we can now model data centres, which will reduce pressure on potable supplies and improve operational resilience. Effective energy and water management are beneficial for businesses as well. They can monitor performance and optimise water usage, which benefits both the community and operators.
The most significant factor, in my opinion, is that we can move from reactive to predictive water and cooling management with digital twinning and AI. When connected to trustworthy operational data and engineering models, infrastructure digital twins can help operators move from static reporting towards predictive management, testing changes in workload, climate, water availability and equipment performance before those conditions affect operations.
And that can offer significant potential for resilience as well as sustainable data centres with robust governance. This requires a comprehensive and holistic approach to both energy and water, rather than individual components.
Ultimately, the objective is not simply to minimise water consumption in isolation. It is to optimise the complete thermal system, because some lower-water cooling configurations may use more electricity. The right solution depends on climate, workload density, water stress, grid carbon intensity and resilience requirements.
- As the Middle East invests in smart cities like NEOM, what role will data centers play in enabling these developments?
I believe that smart cities should communicate with each other as they are powered by AI. This, showcases proper planning works exceptionally when we consider master planning and data centre planning from urban systems that will be integrated into it.
Additionally, integrated value chains are necessary for communities within the UAE to move forward with smart cities. Now, when we discuss value chains, we mean the energy, water, cooling, mobility, and data services.
A significant portion of our work is conducted on city or municipality level, where we use digital twins to enable planners understand interdependencies and future scenarios that can optimise assets within the framework of smart cities. This is where Bentley Systems’ approach to infrastructure digital twins Infrastructure can provide planners with a shared environment in which to understand dependencies, test future scenarios and make more confident investment and operational decisions.
We frequently consider the data centre to be something we would prefer to keep hidden. But, in reality it is a strategic enabler of better, more resilient urban growth. If we do it correctly and consider, let us call it a digital built UAE, which is plausible, becoming an engine room for smart cities.
In fact, this achievement has to be celebrated. If we do it correctly, it becomes a positive contributor behind them. Therefore, I think that smart cities require smart infrastructure, and data centres are becoming a part of what we now refer to as civic backbone. It must be present, accountable, and advantageous to the communities it serves. Moreover, it all comes down systems, smart dependencies, and data exchange between various departments. Because city-scale infrastructure spans many owners and systems, the digital-twin environment must be capable of federating trusted information through open standards, interoperable interfaces and appropriate governance.
- Beyond speed to market, what do you think will define the next generation of successful data centers in the Middle East?
Speed to market is still a very significant factor, but it must transcend that. I believe that if I was an investor considering data centres, I would clearly want to increase revenue at an expedited rate, but I would also want to ensure that it is resilient for a substantial time, which obviously includes water and energy.
It can understand it is sustainable, but I also want certainty. There are certain longer-term concerns, such as whether there will be droughts in the future. My opinion is that it must evolve. Compute hardware and thermal requirements will continue to evolve over the life of the facility, often much faster than the supporting civil, power and utility infrastructure.
Additionally, I also believe it must be flexible and adaptable as cooling technology and workloads evolve. Therefore, we need to consider how we may apply digital twinning once again, not just for capital building, but also for operational excellence.
As AI campuses move into operation, investors will increasingly look beyond capital cost and installed megawatts towards the productivity of the infrastructure: how reliably and efficiently it converts energy and compute capacity into useful AI output. Measures such as cost per token and tokens per watt will sit alongside PUE, WUE, carbon intensity and availability, providing a fuller view of operational and commercial performance.
Tech Interviews
Temporalism Explores How Small, Consistent Actions Can Transform a Life
Ilia Sheludiakov’s story begins with a single decision — one that set off a complete transformation, physical, intellectual, and philosophical. He shed over 40 kilograms, trained for and completed marathons, and built businesses from the ground up. But it was in the process of rethinking his relationship with time that he arrived at something bigger: Temporalism, a philosophy built on the belief that time isn’t a pressure to outrun, but a long-term ally to work with.
At its core, Temporalism reframes time as our most valuable resource — one to be used consciously, not spent carelessly. It’s a philosophy rooted in a simple but powerful idea: small, consistent actions, repeated over time, compound into transformations far greater than any burst of intensity could achieve. Whether in health, wealth, or personal growth, Sheludiakov argues that lasting change comes not from perfect decisions made once, but from good decisions made repeatedly, with patience enough to let them compound.
Temporalism speaks to anyone who feels time slipping away too fast, or who senses untapped potential in their own ambitions but struggles to turn intention into consistent action. It’s a call to make peace with time — and to start using it as a partner in building a meaningful life.
Sheludiakov will next present Temporalism at the Sharjah International Book Fair, introducing the philosophy to a wider international audience and connecting with readers from around the world.
What is the core idea behind Temporalism?
Temporalism is about treating time as your most valuable resource and learning to use it consciously. It focuses on making better decisions today with your future self in mind, while building a meaningful life through consistent action.
How does Sheludiakov’s weight loss tie into this philosophy?
My weight loss was one of the experiences that shaped Temporalism. I lost over 40 kilograms, but the biggest lesson wasn’t about weight — it was realizing how much small actions, repeated over time, can completely change your life.
Why does he believe consistency beats intensity?
Intensity can create quick results, but it’s difficult to sustain. Consistency compounds. A small action repeated hundreds of times can ultimately have a much greater impact than a short period of extreme effort.
What role does patience play in building wealth?
Patience is fundamental. In investing and business, I try to think in years rather than weeks. Wealth is rarely created by one perfect decision; it is usually built through good decisions, discipline, and allowing enough time for them to compound.
Who is this book meant for?
It’s for people who feel that time is moving too quickly or that they could be doing more with their lives. Especially those who have ambitions but struggle to turn them into consistent action.
Where will he present the book next?
I will be presenting Temporalism at the Sharjah International Book Fair, where I look forward to introducing the philosophy to a wider international audience and connecting with readers from around the world.
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