There's no shortage of anxiety surrounding the future of work. It's an unfortunate fact surrounding the younger generation that's slowly entering the workforce. From whispers of automation-fueled job losses to the growing complexity of hybrid collaboration, fear is becoming more common than clarity. But amidst all the change headed our way in 2026 and beyond, it's not all unpredictable. As I've long taught through my Hard Trend Methodology, the key to reducing fear is .
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The result is an explosion of AI capabilities across the SaaS stack, a phenomenon of AI sprawl where AI tools proliferate without centralized oversight. For security teams, this represents a shift. As these AI copilots scale up in use, they are changing how data moves through SaaS. An AI agent can connect multiple apps and automate tasks across them, effectively creating new integration pathways on the fly.
With 27,000 employees and major infrastructure projects across the UK, Balfour Beatty is no stranger to complexity. But as its chief information officer (CIO) Jon Ozanne explains, complexity often carries inefficiency - and inefficiency carries risk. "We know that rework has a cost: it takes time, it takes money, and it carries health and safety implications," Ozanne says. "This is about how we make sure we build things right the first time."
"the moment you try to breach that boundary of language, you start to run into problems, and that's what people are running into now," says Rohan Kodialam, a former data scientist at Citadel. "If you try to use [generative AI] on a real business application where it's not just about saying stuff but about doing stuff, all of a sudden you are now in a much more difficult spot."
The Model Context Protocol (MCP) enhances AI copilots by providing structured tools and context that enable effective task execution, beyond simple prompts.