Your competitors are building AI into their operations. Are you?

I help C-suite leaders in the Sydney market turn AI from a boardroom talking point into a measurable driver of enterprise value. My clients are mid-market firms (300–2,000 employees) and Private Equity portfolios who need more than a slide deck — they need a partner who embeds in their execution and stays until the numbers prove it worked.

As a Certified AI Coach through AIcoaches.com, I bring the battle-tested frameworks from Untangling AI (Wiley, 2026) — the strategic playbook for enterprise AI adoption — and apply them through the Agentic Equity Model, a proprietary methodology I developed for the Australian mid-market.

The result? Not another AI initiative that fizzles after the launch meeting. A disciplined, measured programme that creates tangible ROI — the measurable value of autonomous AI workflows that compounds into permanent value.

The Agentic Equity Model

"The question investors will ask is not 'Do you use AI?' but 'How deeply is AI integrated into your operations, data, people, and decision-making?'"

— Untangling AI (Wiley, 2026)

Traditional hiring took 45+ days per role, with top candidates lost to competitors during lengthy screening. HR team overwhelmed by volume, unable to interview every applicant.

AI-powered interview system handling position descriptions, question generation, candidate screening, IELTS language analysis, and automated ranking — ensuring every applicant was assessed.

Customer service department required hundreds of staff for routine queries. Response times lagged, costs escalated, and strategic work was crowded out by volume.

AI agents integrated into customer service workflows, automating processes previously requiring large teams. Staff reallocated to complex cases and strategic initiatives.

Knowledge workers fragmented across meetings, notifications, and context-switching. Deep work on AI initiatives crowded out by operational noise.

Power Hour methodology — structured 50–120 minute deep work blocks designed around neurochemistry and flow state activation. Six-month phased rollout aligned with habit formation.

AI sales tool estimated at 4–6 months of traditional development. Market window closing. Internal team lacked AI-specific product development experience.

Scientific Method applied to AI development: rapid hypothesis testing, compressed build cycles, and cross-functional sprint team. Agentic workflows accelerated each iteration.