How well is AI really working for you? This session helps you make sure AI is helping, not just happening. With all the noise and hype, it’s easy to confuse activity with meaningful contribution.

You’ll understand how to move from activity to impact - not just tracking dollars and dashboards, but connecting data to strategic objectives and performance.

You’ll learn what to measure, when to measure it and have a clear outline to map to your organisational goals.

Resources will be available to download during the course.

This webinar is for people in leadership roles

• Team leaders, GMs, senior managers, project directors
• Accountable for budgets, and teams
• Not technology, data or AI compliance specialists

Who

• Feel pressure to show that AI is delivering value - but can’t yet prove it
• Are seeing plenty of activity, but not enough evidence of impact or results
• Want to focus their team’s time and energy on what’s working
• Need a simple, credible way to measure and communicate AI’s contribution to people and performance
• Are curious and capable - but short on time, and done with hype, jargon, and endless pilots

This is number three of a series of three. You can complete it as a stand-alone session, but chances are you’ll want more. If you sign up to all three webinars at once, you'll receive our special combo price of $500+GST.

After completing this course you’ll be:

• Clear on why measuring AI matters, and how it protects focus, credibility, and value
• Confident about what to measure, connecting AI activity to people, performance, and business outcomes in the long and short term
• Equipped with simple, credible ways to measure impact, without slowing progress
• Able to turn insights into action so that they can decide what to scale, fix, or stop
• Ready to tell a clear, evidence-based story about AI’s contribution to performance and results
• A complete measurement map to use straight away

Part One: Why Measure - from activity to impact

Most organisations are tracking AI usage, not outcomes. This section is about measuring the impact and contribution of AI on your people, your performance, and your results.

We’ll explore:

• Why measuring matters - and what’s lost when you don’t
• The difference between using AI and AI that delivers value
• Common traps: counting log-ins, licences, and activity instead of outcomes

Part Two: What to Measure - and what to do with it

Introducing the Return on Intelligence - Measurement Map.

This section unpacks what great AI measurement really looks like - not just tracking dollars and dashboards, but connecting data to meaning and momentum.

We’ll explore:

·         Key measures that matter

o   Quantitative - the hard numbers linking AI use to productivity gains, and cost savings

o   Qualitative - the human outcomes like trust, confidence, innovation, wellbeing, and ethics

o   Strategic - the longer-term indicators that show the impact of AI on strategy, data quality, governance and scalability

Real-world storiesof how smart measurement has driven better decisions, culture shifts, and commercial results.

Part Three: How to Measure - quick, credible, and collaborative

Not everything needs a dashboard. Some results you can see straight away - others need a closer look with your tech or analytics partners.

We’ll explore:

• Simple measures you can use to see progress and impact
• When a deeper dive with your tech or analytics partners adds value
• Combining data points with human insight
• What to do with the data - using results to refine systems, strengthen machine learning, and improve business outcomes
• Real-world examples of quick wins and deeper insights that shaped better outcomes