When AI Exposed a Leadership Problem

When the Commonwealth Bank of Australia (CBA) — one of the country’s largest retail bank — announced plans to automate forty-five customer-service roles earlier this year, the move was framed as part of a broader efficiency push. The idea was straightforward: deploy AI-powered voice bots to handle basic inquiries and free human agents for complex cases.

Within days, however, the plan was paused. Rising call volumes, mounting overtime, and growing concern among staff prompted CBA to reconsider. The decision wasn’t a rejection of technology, but a reflection of how even the most established institutions are still learning to integrate artificial intelligence responsibly — balancing automation’s promise with human expectation.

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The illusion of progress

Across industries, automation has become the reflex answer to rising costs and shrinking margins. A 2024 industry survey found that over 80% of service organisations plan to deploy generative AI tools by 2025, convinced that automation will define their competitive edge. Yet customers remain unconvinced. According to KPMG’s 2025 Global Trust in AI Report, nearly 60% of consumers still do not trust AI to handle sensitive interactions.

The same story plays out across markets. In a U.S. survey, 93% of respondents said they prefer speaking to a human over an AI bot, while 78% believe companies should always offer a human option. Adoption, clearly, has outpaced comfort.

In my experience building customer experience operations , the issue rarely lies in the technology itself—it lies in how it’s introduced. Too often, leaders communicate the what before the why. They announce automation but forget to anchor it in a narrative of empowerment and purpose. Employees fear displacement. Customers feel unseen. And what began as an innovation project quickly turns into a trust problem.

The Australian case followed that pattern closely. The new AI-driven voice system failed to reduce call volumes as expected. Instead, overtime rose and team leads were pulled back into frontline work. It wasn’t the software that faltered—it was alignment.

As Salesforce CEO Marc Benioff recently observed, “The speed of AI innovation is far exceeding the speed of customer adoption.” Progress, it seems, has outrun communication.

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The new mandate for leadership

AI is neutral. It reflects intent. Used wisely, it frees employees to focus on empathy, creativity, and complex problem-solving—the areas where human intelligence still reigns. Used poorly, it becomes a wedge between people and the brands they once trusted.

Modern leaders now face a simple but defining test: to ensure technology amplifies humanity rather than replaces it. That means introducing automation with transparency, explaining its role clearly, and ensuring employees remain at the heart of the customer experience. The most advanced systems in the world mean little if customers walk away feeling less understood.

In this new era, leadership requires fluency in both data and emotion. It’s no longer enough to measure cost-per-contact or handle time; leaders must also measure sentiment, trust, and belonging.

AI can optimise efficiency. Only leadership can preserve meaning.

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If there’s one thing to take away from this, let it be this

The future of experience will belong to leaders who can do two things at once: automate with intelligence and lead with empathy. Progress doesn’t start with better code; it starts with better communication.

AI didn’t fail. Leadership is simply learning to catch up. And if transformation is to mean anything, it must move at the speed of adoption — not ambition.

Because in the end, the future of customer experience isn’t human or AI. It’s human through AI.

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