Bankwest is using AI inside its digital contact centre to answer routine questions and support human colleagues when a conversation becomes complex. Its assistant, Bee, handles enquiries such as resetting a password or locking a stolen card. When it cannot resolve an issue or detects a need for human help, Microsoft Dynamics 365 Contact Centre transfers the conversation with context and a summary.

The case study also describes sentiment cues and Copilot-assisted drafting that can turn mortgage terminology into simpler language for a customer. Bankwest says staff contributed more than 30 ideas to the platform, including push notifications and masking rules for Australian tax file numbers. This makes the implementation a useful change-management story: frontline workers shaped the handover, security and usability details rather than receiving a finished system.

The evidence comes from Microsoft and Bankwest, and no independent performance data is provided. Sentiment analysis can also misread language, culture or distress, so an icon should remain a prompt for attention rather than a decision about the customer. The stronger principle is continuity of responsibility. AI can condense history and suggest wording, but a named colleague still owns the response. For regulated service teams, the relevant measures are resolution quality, complaint outcomes, vulnerable-customer handling, escalation accuracy and whether staff can see and correct what the system inferred.


AI for Leaders: Governance, Risk & Why Strategy Must Come First
Is your organisation adopting AI without a defined strategy or governance? If so, you're not alone — and the consequences range from data breaches to reputational damage to safeguarding failures. AI is a strategic risk, not a silver bullet, and definitely not a magic data fairy. Without clear ownership, rules, and accountability, AI can proliferate across your organisation in ways that cost more — in time, money, and trust — than not using it at all. Speakers: Craig Clark, Director at Clark & Company Information Governance Services, and Stewart Tinson, Project Director, AI-360. You'll learn: Why "understand your why" must precede any AI rollout Which risks senior leaders most commonly overlook — from data leakage to safeguarding How to measure AI value through outcomes, not adoption metrics Why accountability for AI governance sits with the C-suite, not IT or compliance Key topics: AI strategy • Risk appetite • Data protection • Bias & fairness • Safeguarding • AI literacy • Governance models • Return on investment • Executive accountability • AI use case tiering For CISOs, CIOs, and senior leaders who need to govern AI responsibly — before it governs them.
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