Nearly every C-suite leader expects AI to lift productivity. Recent research from Kore.ai tells a different story on the ground: a majority of employees using AI say it has added to their workload, not reduced it. It’s a clear signal that workplace AI adoption is running ahead of the groundwork needed to support it. That

Autonomous Endpoint Management: Why IT Teams Are Moving Beyond Manual Fixes Most IT teams know the feeling. A device falls out of compliance. A patch gets missed. An incident sits unresolved for hours. Nobody notices until a user complains. This isn’t a resourcing problem. It’s a visibility and automation problem, and it’s exactly what autonomous

Everyone is investing in agentic AI to improve customer experience. Chatbots, virtual assistants, predictive campaigns – the ambition is genuine. So why does the experience still feel fragmented? The answer isn’t the AI. It’s what the AI has to work with. Most enterprise teams operate across a patchwork of platforms: CRM, CDP, contact centre software,

Kore.ai launched its Artemis platform in May 2026 with a ground-up redesign of how enterprises build and govern AI agents. At the centre of that redesign is Agent Blueprint Language (ABL), a compiled, declarative language that standardises how agents are defined, validated, and controlled before they ever reach production. The problem it solves Most organisations

Ivanti’s 2026 AI Maturity Report surveyed 3,900 employees across six countries and landed on a finding that should give every IT leader pause: the gap between how fast organisations are deploying AI and how well they are governing it is widening, not closing. More than half of organisations (56%) are now deploying AI broadly across