Payal Kapoor is Practice Lead – Complex Business & Finance Advisory at Anchor Excellence, where she works with aged care organisations on financial sustainability, strategy, performance improvement, transformation and business challenges. A qualified Chartered Accountant, Payal brings 25 years of experience across aged care, public health and professional services, with expertise in financial turnarounds, CFO advisory, business structuring and translating complex information into practical decisions. She works with Boards and executives across residential aged care and Support at Home, helping organisations strengthen performance, navigate reform and build sustainable operating models. Her advisory work increasingly includes artificial intelligence strategy, governance, readiness, capability and implementation, with an evidence-based and innovation-focused approach that preserves human judgement, accountability and care. Payal has completed MIT Sloan’s Artificial Intelligence: Implications for Business Strategy program and is embarking on an intensive six-month AI program to strengthen the strategic, evidence-led and practical approach she brings to aged care.
Six Questions Before You Approve an AI Use Case
Challenge
AI use cases can move from enthusiasm to implementation quickly, yet the most important questions are often left until late in the process. Boards and executives need a fast, practical way to test whether a proposed use case is sufficiently understood before investment, risk or operational reliance increases.
Approach
Drawing on emerging AI governance and implementation work in aged care, this 10-minute Spotlight will apply six questions to an illustrative use case:
The session will show how these questions expose weaknesses in an apparently attractive use case before significant investment or risk is committed. Particular emphasis will be placed on WHAT IF, because failure testing is not simply a governance exercise; it is also a test of whether the organisation genuinely understands the business case, workflow and consequences.
What Delegates Will Learn and Apply
The aim is to make AI governance practical, proportionate and enabling – supporting worthwhile innovation while challenging poorly defined or insufficiently controlled use cases.