Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI is transforming how organizations operate, from automating workflows to fueling innovation and competitive advantage. It’s the backbone of the modern enterprise. But while the opportunities AI presents are enormous, they come with new risks: models can be stolen, cloud workloads can be hijacked, and data can be poisoned. Every layer of the AI stack — from GPUs and training data to inference pipelines and SaaS apps — is a new target.

The healthcare industry, despite being highly regulated, is one of the most targeted for breaches, necessitating tight measures. While these measures are necessary, they often restrict the free flow of information, critical for analysing patient outcomes and improving internal operations. Tokenization has long been a reliable method for masking protected health information (PHI). But not all tokenization is created equal.

Financial cybersecurity has never been a static discipline. Over two decades in this industry, I’ve seen it transform from a compliance checkbox to a cornerstone of business resilience—usually after a painful lesson. Today, we’re heading into the most significant paradigm shift for financial security since online banking: the convergence of artificial intelligence and machine identity governance.

As billions of connected devices come online across industries and various sectors such as smart cities, consumer electronics, and healthcare, organisations face increasing pressure to comply with global IoT security regulations. Cyber threats are no longer isolated incidents; they are systemic risks that can disrupt healthcare, transportation, energy, and manufacturing.

The Internet of Things (IoT) ecosystem is expanding rapidly, connecting billions of devices across industries. While this connectivity drives efficiency and innovation, it also introduces massive cyber risks. The IoT ecosystem is an interconnected environment of devices, systems, and technologies, making security especially complex. Attackers are increasingly using automation and artificial intelligence (AI) to launch sophisticated attacks at scale.