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In 2026, the talent gap in tech has shifted from “who can code” to “AI‑Plus” Engineers—professionals who combine traditional software engineering with AI integration, MLOps, and domain‑specific expertise.

“Women in AI” is front‑and‑centre on LinkedIn and at AI meet‑ups, with hashtags like #WomeninAI and #WomeninGenAI. Australia now has Women in AI Australia, APAC‑wide Women + AI hubs, and a growing list of “women‑to‑watch” in AI leadership, product, and investment.

Leaders keep saying they want to “redesign work for AI”, but inside most organisations the reality is still pretty messy.

AI roles are having a moment. If you scroll LinkedIn right now, it feels like every second post is a new title: AI Engineer, LLM Engineer, Director of AI, AI Strategist. Underneath the noise, there's a real shift happening in how teams think about capability, not just headcount.​

Most leaders still default to headcount: “We need to hire.” But AI, automation and shifting skills mean roles age quickly. Your real challenge is deciding when to automate, grow, rent or own talent—especially across AI, data and engineering.​

Gen AI is everywhere in companies right now—except in the numbers that matter. Tools are being rolled out, copilots are being switched on, but for most organisations it still isn’t showing up clearly in the P&L. That gap between enthusiasm and impact is what needs attention next.