Technology executives used Worldwide AI Appreciation Day to detail how artificial intelligence is moving into customer service and leadership roles, with a shift from isolated experiments to targeted operational projects. Their comments, spanning networking, observability and insurance, point to rapid adoption tempered by a strategic focus on governance, data quality and practical business outcomes.
AI enters customer-facing channels
Australian small business insurer BizCover now lets customers request insurance quotes through ChatGPT, using natural language to simplify the process. The company also applies AI across compliance, risk and technology functions. A 2025 survey of 965 Australian small business owners found that 80% were already using AI or planned to adopt it.
"Quoting insurance through ChatGPT is just the start. At BizCover, AI strengthens our compliance and risk management, elevates customer service, powers what we build in tech and makes our teams more efficient," said Dino Tius, Chief Information Officer at BizCover. "It's proven one thing to us: if you can imagine it, AI can help get you there."
For support teams evaluating similar tools, ChatGPT Courses provide a way to build practical skills. The move to conversational AI in customer interactions is no longer a future concept - it is already handling real quotes for small businesses.
Leadership and the push for operational trust
At Dynatrace, Vice President of Global Solutions Engineering Philippe Deblois said many large organisations have launched agentic AI initiatives but remain cautious about scaling. Internal research shows about half of these projects are still in proof-of-concept or pilot stages.
"AI Appreciation Day is a chance to recognise the progress organisations have made, but also to be realistic about what's next," Deblois said. "The conversation has also matured. It's no longer centred on what AI could do, but on where it can solve genuine operational challenges and support better, faster decision-making. As these systems take on more responsibility, trust becomes less of a nice-to-have and more of an operational requirement."
He added that organisations aiming for higher automation levels need stronger data foundations and clearer success metrics. "Success depends on a strong foundation of high-quality data, clearly defined objectives and a focus on measurable business outcomes."
Extreme Networks CTO EMEA Markus Nispel described how AI now underpins his workflow from research to execution. "It helps me identify risks, keep initiatives on track and, when used correctly, accelerate the journey from an idea to a demonstrable prototype," he said. "It doesn't just answer questions, but challenges assumptions, connects ideas and helps turn early thinking into something worth building."
Nispel said AI is also reshaping leadership expectations by giving leaders better data and deeper insight, though accountability remains human. "While AI can inform decisions, it can't own them. Leadership will always be about judgment, accountability and the courage to make the final call." He noted that experienced teams are already using AI to lift productivity in software development, improving both quality and speed. "The greatest opportunity isn't replacing human expertise; it's amplifying it."
For customer support teams, this shift from repetitive tasks to higher-value work is already evident. AI for Customer Support Courses can help professionals adapt to these changing roles by building skills in automation and AI-augmented decision-making.
Why this matters for customer support professionals
AI is no longer confined to backend analytics. It is interacting directly with customers, handling quotes and freeing agents from time-consuming administrative work. Support professionals who understand how to configure, monitor and refine these tools will be better positioned as companies move from pilots to full production. The executives' caution about trust and governance also signals that human oversight in customer interactions remains critical - not to replace people, but to ensure AI works reliably and fairly when it speaks to customers.
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