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HOW BUSINESSES CAN UNLOCK THE TRUE VALUE OF MODERN LOG MANAGEMENT

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Mala Pillutla, Vice President of Sales for Log Management, Dynatrace

Without logs, it would be almost impossible to keep modern applications, cloud platforms, or customer-facing services running efficiently. Some might argue that logs are one of the most critical but least celebrated sources of truth in the digital era.

At its core, log management is about turning raw system logs — unprocessed, detailed records of a system’s activities, including server actions, user interactions, and error messages — into actionable insights. As digital systems grow in scale and complexity, logs have evolved from a backroom tool into a critical driver of reliability, performance, and security across an entire business.

From a website crashing or pages loading too slowly, to customers encountering errors or even early signs of a cyberattack, logs provide teams with a clear view of what’s happening inside their digital systems. Within an observability platform, they present the detailed “story” behind these events, helping teams move from simply knowing something is wrong to understanding why it’s happening and how to fix it before it impacts users.

Research has found that 87% of organizations claim to use logs as part of their observability solutions. That number shows how universal log usage has become. The question now is whether businesses are unlocking their full value. Collecting logs is one thing but interpreting them is another.

For too long, logs have been treated as clutter, something to store, sift, and forget. The reality is that they’re one of the clearest signals of how a business is running. Modern log management makes those signals impossible to ignore.

The limits of traditional log management

As business digital estates grow more complex, the volume of logs generated across applications, infrastructure and business services has exploded. However, more logs do not automatically mean more insight. In fact, many teams are overwhelmed by sheer volume, struggling to separate meaningful signals from background noise. This overload creates noise that makes it difficult to identify urgent issues, leaving IT and Security teams on the back foot during critical incidents and proactive response.

The problem is as much about cost as complexity. Storing and managing log telemetry without a clear purpose often leads to escalating expenses that outpace the value delivered. Traditional licensing and infrastructure models add to the problem. They often make log management feel like a financial liability than a strategic advantage.

Another common constraint is fragmentation. Logs often live across multiple tools, with different interfaces and storage models, slowing root cause analysis and complicating cross-team collaboration. In a cloud-native world where speed and scale are vital, this siloed approach is out of step with modern business needs.

Together, these shortcomings point to the need for a smarter approach—one that focuses on clarity, efficiency, and value.

Turning logs into actionable intelligence

Taking a smarter approach to log management starts with a shift in perspective. Rather than treating logs as an endless stream of technical data, leading organizations use them as a lens to understand how their digital ecosystems truly perform. The real value lies in not collecting everything but in knowing what matters and identifying which logs drive resilience, security, customer experience, or compliance, and filtering out the rest.

AI is becoming an essential part of this process. Modern techniques can detect anomalies, trace issues back to their root cause, and even trigger automated fixes. This reduces manual investigation and accelerates recovery, allowing teams to move from firefighting to foresight.

Equally important is being selective. Forward-thinking organizations decide which logs to capture, which to discard, and how to route them most effectively. This helps control costs and ensures that attention is focused on the telemetry that delivers the greatest value. When organizations find this balance, log management evolves from a tactical task to a strategic capability that strengthens both performance and resilience.

Observability and the bigger picture

Log intelligence on its own is valuable, but it is only part of the story. The next frontier is AI powered observability, uniting logs with metrics that track performance, traces that map interactions, and events that reveal key system changes. Combined in a single platform, these data types give teams a complete picture – connecting technical performance with genuine business impact and moving from a view of what happened to an understanding of why it happened and how to respond quickly.

Consider a global telecommunications provider that recently re-evaluated its log strategy. Managing more than 15TB of logs every day, stored for long periods and spread across thousands of dashboards, the team was buried in dashboards and redundant data. By consolidating logs within a broader observability framework and replacing static alerts with intelligent detection, they cut through the noise across its systems. Able to focus on the signals that mattered most, the organization improved uptime, speed, and overall resilience.

This example shows that observability delivers its greatest value when it helps teams cut through complexity. With logs feeding into a single platform, data becomes easier to interpret and act on, transforming technical insight into business intelligence.

Unlocking the true value of modern log management

Modern log management gives organizations the context they need to turn massive volumes of data into meaningful insight. Organizations that harness AI, automation, and broader observability, gain a clearer view of how their technology is supporting their goals. Enterprises can analyse faster, automate smarter, and innovate with confidence.

True modernization comes from changing how teams think about data. Now is the time to review current strategies, identify gaps, and adopt modern platforms that integrate AI, context, correlation, and smarter telemetry management practices because organizations can no longer afford to treat log management as a background IT task. The companies that thrive will be those that treat logs not as exhaust from their systems, but as evidence of how their business thinks and performs. By bringing intelligence to the data they already have, they will turn observability into a source of continuous advantage and understand their business like never before.

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Tech Features

WHY EXCEPTIONS, NOT INVOICES, ARE COSTING FINANCE TEAMS THE MOST

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By Ionut Valentin Sas, SVP Finance, UiPath

Across the GCC, processing standard invoices has become relatively straightforward. Routine invoices are no longer the problem. The real bottleneck begins the moment an invoice falls outside the expected workflow, whether that is a mismatched PO, a missing approval, incorrect coding or a supplier query. From there, the process spills into email threads and spreadsheets, and finance teams pay for it in delayed cash flow, missed early payment discounts, strained supplier relationships and tied-up working capital. The invoice itself was never really the problem. The problem is what happens when it does not follow the usual pattern.

The Trouble with Exceptions

Straight-through processing, where an invoice moves from receipt to payment without human intervention, has been one of finance teams’ most effective ways to handle higher invoice volumes at lower cost. Companies like Canon have reported up to 90 percent STP for certain invoice types.

Yet according to Ardent Partners’ State of ePayables report, even top-performing AP teams only reach around a third. That gap reflects a shift already under way in accounts payable. As routine invoices increasingly process themselves, less time goes into verifying standard transactions, and more of the team’s effort shifts toward judgment, coordination and resolving what falls outside the pattern, such as invoices missing a PO, mismatched purchase orders, supplier follow-ups and approval bottlenecks.

Most automation was built for the predictable majority of transactions. The remaining cases still get routed back to people, with no system designed to resolve them faster or more consistently. Resolving an exception often means pulling information together from ERP systems, procurement platforms, contracts, past transactions and supplier communications before a decision can be made. The challenge is rarely a lack of information. It’s that the information sits across multiple systems and requires someone to piece it together before a decision can be made. That’s where most of the time is lost.

Invoicing in the UAE

The UAE’s move toward mandatory e-invoicing is one of the clearest signals of this shift. For many organisations, this transition will expose processes that have remained largely hidden while invoices were handled manually. Standardised, machine-readable invoices make routine processing easier, but they also shine a light on the exceptions that continue to require human intervention. As a result, organisations have an opportunity to redesign how those exceptions are managed, rather than simply digitising existing processes. The mandate requires structured, machine-readable invoices in place of the PDFs and spreadsheets many finance teams still rely on, and it is pushing organisations to take a hard look at how they handle exceptions today.

Compliance is only the starting point. The bigger opportunity is using this transition to modernise broader finance operations and rethink how exceptions get managed, not just to meet the regulatory deadline.

The Importance of Governance

As more of this resolution work shifts to AI agents, visibility, auditability and control become essential. Governance is not there to slow decisions down. It is what gives organisations the confidence to automate lower risk work while keeping higher risk decisions transparent, explainable and subject to human oversight. Done well, orchestration keeps people in charge of decisions, not just faster at processing them. That becomes increasingly important as finance teams automate larger parts of the invoice lifecycle. Confidence in AI comes not from removing people altogether, but from knowing when human judgement should remain part of the process.

The UAE’s e-invoicing mandate makes this need for governance harder to ignore. But governance should not be seen as a brake on AI adoption. It is what makes that adoption trustworthy.

The Shift Finance Leaders Must Make

The old mindset was to automate invoices. The new one is to resolve exceptions.

That is the shift finance leaders now need to make, treating exception management as the next frontier in finance automation rather than an afterthought bolted onto invoice processing. The foundation for that shift is orchestration, bringing people, systems and AI agents together around each exception instead of simply flagging it for someone to pick up later.

AI agents can do much of the groundwork before a person is even involved, gathering supporting information, analysing how similar cases were resolved in the past, recommending next steps and drafting supplier communications. That does not replace judgment. It means the judgment that does happen is faster and better informed. The organisations that gain the greatest advantage will not necessarily be those processing the highest number of invoices automatically. They will be those that can resolve exceptions quickly, consistently and with the right level of oversight, turning what has traditionally been a source of delay into a competitive advantage. The GCC built its reputation in digital government and public services by fixing what was not working, not by polishing what already was. Finance now has the same opportunity in front of it. The invoices were never the hard part. The exceptions are, and the organisations that get ahead of them will be the ones setting the pace for the next phase of digital invoicing in the region.

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Tech Features

THE BEAUTIFUL GAME, FOR EVERYONE: HOW TECHNOLOGY REWROTE THE RULES OF FOOTBALL FANDOM

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By: Jason Ou, President at Hisense MEA

As the FIFA World Cup 2026 final approaches this week, we reflect on a tournament that transformed how millions experienced the sport, from living room stadiums to quiet spaces in packed arenas

As we count down the final hours before this week’s showpiece final, the FIFA World Cup 2026 has delivered 103 matches across 16 cities, and with it, a reimagining of what “experiencing football” means.  Hisense served as the official and exclusive Video Assistant Referee (VAR) Review TV Provider for the entire tournament across the United States, Canada, and Mexico. Every controversial offside call. Every penalty review that had fans screaming at their screens. Every red card confirmation that shifted the momentum of a knockout match. The technology referees used to make those match-defining decisions ran on Hisense RGB MiniLED displays. The Video Operation Room in Zurich was upgraded specifically with these screens because VAR officials needed “clear and authentic restoration of live match footage.”

And it delivered.

Two parallel revolutions unfolded across this tournament: one that transformed homes into legitimate viewing destinations, and another that finally opened stadium doors to millions who’d been locked out for decades.

Hisense made an argument before kickoff: the home viewing experience could, in some ways, surpass what you’d get at the stadium itself. If the technology was precise enough for officiating decisions scrutinized by billions and debated across social media within seconds, it was good enough for living rooms worldwide.

For those who invested in the L9Q TriChroma Laser TV, everyday living spaces became premium match-day destinations throughout the tournament. With ultra-large displays up to 200 inches, fans followed every run, pass, tackle, and goal with remarkable clarity.

The flagship UXS RGB MiniLED TV, powered by breakthrough RGB MiniLED technology that delivers exceptional color accuracy, brightness, and contrast, brought fans closer to every moment on the pitch and created a more immersive and lifelike viewing experience for sports, entertainment, and gaming.

The Party Everyone Could Finally Join

For millions of fans living with autism, PTSD, dementia, anxiety, and other sensory processing conditions, the stadium experience had remained firmly out of reach, a party they could hear from outside but never truly join. This tournament changed that.

At this year’s tournament, all 16 host stadiums featured dedicated sensory rooms, making this the first-ever Sensory Inclusive FIFA World Cup. Hisense collaborated with FIFA and KultureCity to install these spaces across every venue in the United States, Canada, and Mexico, and they were used.

As Hisense continues pushing boundaries, making every match feel bigger, every celebration more immersive, and every memory more unforgettable, one truth has emerged from this tournament: the hierarchy of World Cup viewing has been expanded, making room for everyone who loves the beautiful game.

This week, as billions watch the final from living rooms with 300-inch screens and fans with sensory needs take their seats in the stadium, football’s promise will be fulfilled. The beautiful game. Finally, for everyone.

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Tech Features

HOW AI IS RESHAPING HIGHER EDUCATION, AND WHY UNIVERSITIES MUST REINVENT THEMSELVES

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By: Prof. May El Barachi, Dean & Full Professor, University of Wollongong in Dubai

Artificial intelligence is no longer a future technology. It has become part of our everyday lives almost overnight. Whether we are writing emails, analysing data, generating code, creating presentations, or conducting research, AI has fundamentally changed how knowledge is created and consumed.

For higher education, this represents one of the biggest disruptions since the arrival of the internet.

Much of today’s conversation revolves around a simple question: Will AI replace educators?

I believe we are asking the wrong question.

The real question is whether universities can reinvent themselves quickly enough to prepare graduates for an AI-first world.

Having worked extensively with generative AI technologies, I see AI not as a replacement for education, but as an extraordinary opportunity to redefine it. From One-Size-Fits-All Learning to Personalized Education.

Traditional education has largely been built around standardized delivery: one lecturer, one classroom, one pace, and one curriculum for every student.

AI changes that equation.

For the first time, every learner can potentially have access to an intelligent learning companion available 24 hours a day. AI tutors can explain difficult concepts, generate additional practice exercises, adapt explanations to different learning styles, provide immediate feedback, and support students until genuine understanding is achieved.

Instead of asking students to adapt to education, education can finally adapt to students. This has important implications for accessibility, allowing high-quality learning experiences to reach individuals regardless of geography or socioeconomic background.

In many ways, AI has the potential to become the great equalizer in education.

Teaching Students How to Think; Not What to Memorize

At the same time, AI forces universities to rethink their educational philosophy.

When information is instantly accessible, memorization becomes less valuable.

Future graduates will be judged less by what they know, and more by how effectively they can solve problems, evaluate evidence, think critically, collaborate, communicate, and exercise sound judgement. This means assessment methods must evolve as well.

Rather than rewarding students for reproducing information that AI can generate in seconds, universities should increasingly emphasize authentic projects, real-world problem solving, teamwork, creativity, ethical reasoning, and applied learning. Ironically, AI may push higher education to become more human, not less.

Educators Are Becoming AI-Enabled Mentors

There is growing concern that AI will eventually replace lecturers. I see the opposite happening.

The educator’s role is becoming even more important; but it is changing.

Rather than acting primarily as transmitters of knowledge, educators are evolving into mentors, coaches, facilitators, and critical thinking partners who help students interpret information, challenge assumptions, and develop professional judgement.

To do that effectively, universities must invest heavily in AI literacy. Faculty need more than basic familiarity with AI tools. They must understand how these systems work, their limitations, their biases, and how they can be integrated responsibly into teaching, assessment, and research. AI literacy is rapidly becoming as fundamental as digital literacy was twenty years ago.

Preparing Graduates for an AI-First Workforce

Perhaps the biggest transformation is happening outside the classroom. Virtually every profession; from healthcare and finance to engineering, education, law, and government; is being reshaped by AI.

Graduates entering the workforce will collaborate with intelligent systems every day. This requires a new combination of technical and human capabilities. Understanding AI, data, automation, and digital technologies will become essential across disciplines. Equally important will be creativity, emotional intelligence, leadership, adaptability, ethical decision-making, and lifelong learning. The most successful professionals will not compete against AI. They will learn how to work alongside it.

Looking Ahead

The future university may look very different from today’s institution. Degrees are likely to become more modular and flexible, complemented by stackable micro-credentials that allow professionals to continuously update their skills throughout their careers.

Immersive technologies such as virtual and augmented reality will create richer learning experiences, while learning analytics will enable institutions to identify struggling students earlier and provide personalized support. Education will become increasingly global, connected, and lifelong.

The Human Advantage

Despite all these technological advances, one thing remains unchanged. Education has never been solely about transferring knowledge. It is about inspiring curiosity, building confidence, developing character, nurturing empathy, and preparing individuals to make meaningful contributions to society.

No algorithm can replace the inspiration of a great teacher or the mentorship that shapes a student’s future.

AI should not diminish the human element of education. It should amplify it.

The universities that thrive over the next decade will not be those that simply adopt AI tools. They will be those that successfully combine technological innovation with the uniquely human qualities that no machine can replicate. Because ultimately, the future of higher education is not about artificial intelligence. It is about human intelligence; enhanced by AI, guided by educators, and applied to solve the world’s most complex challenges.

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