While these back-office investments are necessary to boost productivity and streamline internal workflows, Fillmann underscores the potential downside of an overly narrow approach.
“Taking full advantage for the greatest returns requires an equally keen eye towards front line applications.”
Balancing productivity with customer experience
One of the biggest challenges business leaders face is achieving the right balance between cost-cutting and enhancing customer experience.
“A lot of companies are asking: how do we boost productivity without compromising customer experience?” says Fillmann. “Stripping out costs, saving time, giving customers the best possible experience with your company – these all help the bottom line.”
ANZ general manager of Salesforce, Frank Fillmann.
Fillmann says that recent advances in AI have largely solved this challenge by enabling productivity and customer experience to go hand in hand.
“Where the technology is now, particularly with the introduction of AI agents, productivity and customer experience no longer have to be trade-offs,” he says.
The introduction of the company ‘s Agentforce, he says, allows companies to deploy autonomous AI agents that support employees, effectively acting as an extension of the team. “Agents help reduce the cognitive load on employees, allowing them to focus on the more nuanced and human aspects of their work.”
Navigating misconceptions
AI adoption can be a daunting task, and executives are feeling pressure from both internal and external stakeholders to move quickly.
“There’s pressure from the board to hurry up and get going, and of course deliver value; and pressure from customers to bring the ‘magic’ of public AI models to their experiences with companies,” Fillmann says.
Part of this pressure falls on technical leaders, who often delegate AI decisions upward, seeking guidance from the CEO.
He warns against over-complicating AI implementation by focusing on the technology itself rather than the business outcomes it can support.
“Companies are spending too much time deciding which UI or model to choose, or even trying to build their own LLM,” he says.
“The fastest, safest, and most sustainable path forward is abandoning DIY efforts that start with the AI, and instead identifying the most urgent, high-impact use cases that will deliver business value, fast.”
Data quality and privacy remain critical obstacles
For AI to succeed, Fillmann stresses, companies need robust, well-managed data infrastructures that address quality and privacy concerns.
“Almost every organisation tells us their data is fragmented, trapped in disconnected systems, and not ready to ensure AI investments are effective,” he says.
As a result, many organisations are spending considerably more on data infrastructure than on AI itself.
“Our global study found CIOs are spending four times more on data infrastructure and management as they are on AI,” Fillmann says.
Without the right data foundation and secure connections to daily business operations, AI cannot transition from a mere novelty to a powerful tool for decision-making and strategy.
The company’s Data Cloud aims to solve this issue by creating a secure, unified data foundation. “Data Cloud has been designed to tackle these very issues. It’s the foundation for every AI transformation and the core of Agentforce,” Fillmann says.
For business leaders, the challenge lies not only in managing data quality, privacy, and training but in cultivating a holistic AI strategy that aligns with their strategic goals.
Customer experience must be flawless
Fisher & Paykel is leveraging AI on the front line to enhance its technology-driven customer service and maintain a competitive edge.
The household appliance leader is exploring the integration of generative AI to streamline support processes and enhance user experience.
Chief digital officer, Rudi Khoury, sees customer service as an ideal entry point for generative AI applications, thanks to its high volume of manual, repetitive tasks.
These AI tools could help boost efficiencies while enabling customers to resolve issues quickly and independently.
Fisher & Paykel is using AI bots to triage customer needs, directing them to appropriate resources and self-service options via tools like Salesforce’s Einstein Bot.
This innovation, Khoury says, has already yielded positive feedback, with around a third of users choosing to self-serve after interacting with the bot, reducing wait times and improving response rates. However, he stresses that these tools don’t replace the human touch entirely, particularly when it comes to quality control and delivering nuanced support.
Fisher & Paykel chief digital officer, Rudi Khoury.
Khoury acknowledges that while AI has significant promise, it also presents challenges, particularly in terms of reliability and data accuracy. “If you’re putting generative AI in a customer-facing role, it has to be flawless,” he says, adding that any AI-induced errors could harm customer trust, which is paramount in their approach to support.
“We don’t want any savings to come at the expense of customer experience,” says Khoury.
To avoid pitfalls, Fisher & Paykel is implementing governance structures and careful oversight to ensure information presented to customers is as accurate as possible.
Internally, the AI tools offer productivity boosts, enabling staff to complete tasks more efficiently and focus on higher-level problem-solving. This controlled deployment provides another layer of quality assurance, with humans ensuring AI-generated information is appropriate before it reaches customers.
As for data, Khoury describes it as the “oil that fuels AI”, stressing the importance of structured, labelled, and consolidated data systems. Fisher & Paykel has invested heavily in data platforms to streamline this infrastructure, understanding that cohesive data sources are fundamental to AI’s effectiveness.
Rather than feeling pressured to deploy AI in every facet of the business, Khoury says the focus remains on aligning AI solutions with core business goals. For Fisher & Paykel, that means prioritising tools that enhance, rather than replace, the human-centre d service approach they are known for.
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