The telecommunications industry is moving beyond being a traditional connectivity provider.

Projects seldom go as planned, leaving project managers with any number of small fires to put out. Here are the most common issues projects encounter and how to get things back on track.

7 out of 10 C-suite cats reckon software category's best days are behind it, but can't agree what's next

The ability to simply get your email into the recipient's inbox instead of the spam folder is known as email deliverability. Everything depends on this because if people cannot see your messages, then they cannot open them, click anything inside them, or simply convert.

In 2026, businesses that want to succeed can no longer send 'one-size-fits-all' email campaigns to their entire contact list or segment consumers by simple demographics such as gender, age, or location. In fact, data shows that 71% of consumers expect businesses to deliver personalized interactions.

AI was meant to lighten the load on contact centers by automating routine tasks, speeding up resolutions, and freeing agents to focus on empathy. In reality, automation often reduces overall contact volume but increases task complexity, leaving human agents to handle only the most difficult, emotionally charged interactions.

While vector databases still have many valid use cases, organizations including OpenAI are leaning on PostgreSQL to get things done. In a blog post on Thursday, OpenAI disclosed how it is using the open-source PostgreSQL database.

Choosing a database is no longer a background decision in web development. It shapes how fast an application runs, how well it scales, and how securely it handles data.

As databases grow, it's only natural that the infrastructure sustaining them needs to be able to support this expansion. Servers act as the foundation of modern databases, and so they must provide enough power and speed for fast query handling and transaction processing.

Data centers are shifting from NTP to PTP for precise time synchronization, enabling real-time workloads but requiring complex hardware and network upgrades.

The rise of AI is transforming data center design, demanding agility, scalability, and sustainability to meet evolving workloads, writes Joe Reele.

What Are AI Certifications?: AI certifications are structured learning credentials that validate foundational and practical skills in artificial intelligence, machine learning, data handling, and real-world problem-solving.

Building a career development strategy in your organization retains talent and boosts productivity. And it starts with one simple act.

There is a shortage of AI talent. Companies are not able to close the AI skills gap. These are familiar headlines from job market outlook reports over the last year or so. Many companies think that this is a supply or talent problem.

AI keeps popping up in every corner of work life, and it's becoming the skill people use to run circles around everyone else. You don't need to be a coder or a tech diehard to get value out of it, but you do need to understand how it fits into the way you solve problems. The ones who pick it up early usually land the faster workflows, the better ideas, and, often, the better roles.

Enterprises today are grappling with an unprecedented surge in data creation. Every interaction from video and images to logs, sensor outputs, and (AI-)generated content is contributing to an exponential rise in what businesses must store and analyze.

CNCF's 2025 Annual Survey shows Kubernetes has become the open source backbone for production AI, with enterprises standardising on cloud-native platforms as AI moves cautiously into scale.

Despite lots of hype, "voice AI" has so far largely been a euphemism for a request-response loop. You speak, a cloud server transcribes your words, a language model thinks, and a robotic voice reads the text back. Functional, but not really conversational.