A ransomware attack can leave an organization with a problem more difficult than encrypted files: the systems used to establish trust may also be compromised.  If attackers gain privileged credentials, compromise Active Directory, or reach backup infrastructure, recovery is no longer simply a matter of finding a clean copy of

A multimillion-dollar GPU investment can be underperforming before the first model finishes training. The problem may not be a shortage of compute but It may be that the storage and data infrastructure feeding that compute cannot deliver data quickly or consistently enough to keep the GPUs working.  Meta’s experience at

AI is exposing a limitation in the way enterprises have traditionally approached infrastructure costs: the price of running an AI workload cannot be understood by looking at compute expenditure alone. A company may reduce GPU costs and improve utilization while spending more on high-performance storage, networking, data movement, replication or

Agentic AI changes the infrastructure equation because AI is no longer limited to generating an answer. An agent can retrieve information from multiple systems, interpret it, call tools, trigger workflows, and write information back into enterprise applications. Every additional action creates another dependency on the data environment underneath it.  That

When AI infrastructure becomes expensive, the first instinct is often to look at the GPU bill. But in many production environments, the more important question is what those GPUs are waiting for.  Consider Synthesia, an enterprise AI video communications platform that uses large-scale computing to develop increasingly realistic text-to-video models.

It starts randomly, employees log in, customer portals are live, and business is running as usual. Then the first support tickets begin to appear. Files won’t open. Internal systems stop responding. Minutes later, a message flashes across hundreds of screens: Your files have been encrypted. The IT team immediately turns

Every organization has a backup strategy, far fewer know how long it would actually take to get their business back online after a cyberattack or a major outage. That distinction is becoming increasingly important. As ransomware grows more sophisticated and cloud environments become more complex, the conversation is shifting away

Organizations are rapidly adopting Microsoft Copilot and other AI-powered productivity tools to improve efficiency, streamline collaboration, and support faster decision-making. By helping employees summarize meetings, analyze documents, generate content, and surface relevant information in seconds, these tools are transforming the way people work. As adoption accelerates, however, organizations are beginning

Security Operations Centres (SOCs) have reached a tipping point. While organisations continue to invest heavily in cybersecurity technologies, many are finding that adding more tools alone is no longer improving security outcomes. Instead, security teams are grappling with an ever-growing volume of alerts, increasingly sophisticated attacks, and a persistent shortage

According to McKinsey’s 2025 State of AI report, nearly 80% of organisations have adopted AI in at least one business function, while enterprise investment in generative AI continues to grow at record pace. Yet despite this rapid adoption, disaster recovery strategies have struggled to keep up. Veeam’s 2025 Data Resilience

For years, enterprise storage was viewed as a behind-the-scenes technology—essential, but rarely strategic. Its primary role was to store data, support backups, and ensure systems could recover after an outage. That perception is changing rapidly. Today, storage infrastructure sits at the center of artificial intelligence, cybersecurity, analytics, and business continuity.

Artificial intelligence has become one of the defining technologies shaping the future of financial services. Banks are using AI to detect fraud in milliseconds, insurers are accelerating underwriting decisions with machine learning, and investment firms are leveraging predictive analytics to identify market opportunities faster than ever before. As global investment

When Three Days Became the New Standard June 2026, U.S. cybersecurity authorities shortened the remediation deadline for actively exploited vulnerabilities to just three days. The message was clear: attackers are moving faster than defenders. Artificial intelligence is playing a major role in that shift. Cybercriminals are now using AI to

Healthcare organizations have always been attractive targets for cybercriminals, but the threat landscape in 2026 has reached a new level of urgency. Hospitals, clinics, pharmaceutical companies, and healthcare technology providers are facing increasingly sophisticated attacks that can disrupt patient care, compromise sensitive medical records, and create significant financial and operational

For years, ransomware followed a predictable pattern. Attackers would break in, encrypt data, and demand payment. Backups were the safety net. If something went wrong, organizations could restore and move on. That model is breaking down. Today’s ransomware groups are changing the sequence. Instead of encrypting first, they are going

A security researcher was mapping publicly accessible cloud assets when they stumbled across a simple storage URL. No login prompt. No restriction. Just a bucket sitting openly on the internet. Out of curiosity, they clicked. What they found wasn’t test data. It was production-level information internal reports, user records, archived

Most disaster recovery strategies are built on an assumption that rarely holds in real environments: that systems will fail in a predictable, linear way. In practice, they don’t. Modern cloud environments are layered, distributed, and constantly evolving. Services depend on each other in ways that are not always fully visible,

Virtualization has long been the backbone of IT infrastructure in universities, research institutions, and public-sector organizations. It supports everything from academic applications and research workloads to administrative systems and data storage. For many years, institutions relied on familiar platforms that delivered stability and consistency but today, that familiarity is increasingly

An employee logs in, emails are flowing, systems are running as usual. No alerts, no obvious breach. But somewhere in the background, credentials have already been captured. Not through a flashy phishing link or malware, but through something much quieter. An old pathway has reopened. The SMTP-based exploit patterns tied

Traditionally, when people talked about AI security, they meant protecting the model. Lock down access, secure APIs, make sure no one can tamper with it. And for a while, that was enough. But things have shifted. Today, the bigger risk isn’t someone breaking into your model, it’s what your model

Toronto Canada, Seattle, WA [May 6, 2026] – A powerful new consortium of technology leaders today announced the launch of the Indigenous People Project (IPP), a collaborative initiative designed to empower Indigenous and Aboriginal communities by providing direct access to advanced technical skills, certifications, and pathways to high-paying technology careers.  The founding

Human Error Is Becoming a Cloud Security Vector Not all cyberattacks begin with sophisticated code or advanced intrusion techniques. Increasingly, some of the most effective breaches originate from something far simpler which is human error. Recent threat intelligence has highlighted campaigns, including those linked to China-based actors, that exploit minor

Cybersecurity Is Emerging as the Core Investment Priority  The consulting market across the Gulf region has remained stable despite ongoing geopolitical tensions, but the nature of demand is shifting significantly. According to Gartner, global spending on cybersecurity is expected to exceed $215 billion in 2024, with the Middle East among the fastest-growing

In 2026, delay is becoming expensive. A logistics company can lose millions in a single quarter because rerouting decisions came too late. A financial firm can miss revenue in seconds because a risk alert sat untouched in a dashboard. A retailer can lose customers simply because demand signals were analyzed

Healthcare Is the Most Targeted Critical Sector Healthcare has become one of the most targeted industries in global cybercrime. According to IBM’s 2024 Cost of a Data Breach Report, healthcare organizations face the highest average breach cost of any sector, reaching approximately $10.93 million per incident for the thirteenth consecutive

A Cyber Incident That Became an Economic Event The recent cyber disruption affecting Jaguar Land Rover was not merely an IT failure. It escalated into an economic event with national consequences. Production slowdowns and supply chain interruptions rippled across suppliers, logistics partners, and export channels, with estimates suggesting the broader

AI Is Accelerating Cybercrime at Scale Artificial intelligence is no longer just transforming enterprise productivity. It is transforming cyberattacks. Recent industry reporting shows that generative AI has significantly increased the scale and sophistication of phishing, malware development, and automated vulnerability discovery. According to IBM’s 2024 Cost of a Data Breach

Why Confidential Computing, Integrated AI Security, and Governance Are Now Non-Negotiable? In 2025, a quiet but alarming incident sent ripples through the AI industry. Scale AI, one of the world’s largest AI data-labeling companies, was found to have hundreds of “confidential” documents publicly accessible via Google Docs. These files reportedly

Artificial intelligence is no longer a side experiment in financial services. By 2026, it is becoming a core driver of competitiveness, cost efficiency, risk management, and customer experience across banking, financial services, and insurance. What began as scattered pilots like chatbots, automation scripts, and analytics tools is now evolving into

Artificial intelligence is rapidly becoming core enterprise infrastructure, but the dominant risk facing organizations today is no longer model accuracy or compute performance. The true exposure lies in how data is collected, stored, governed, and protected before it ever reaches a model.  As enterprises deploy generative AI, machine learning pipelines, and automated