Why boards are asking the wrong question about AI strategy

Henry Ford, founder of Ford Motor Company, is credited with the observation that if he had asked people what they wanted for better transport during his time, they would have said faster horses. The remark cuts to the heart of what genuine innovation demands: not responding to what people ask for, but imagining solutions they have not yet conceived, according to Nicholle Lindner, an AI expert, futurist and FinTech director/advisor who has spent almost three decades at the intersection of financial services and technology.

Henry Ford’s observation frames the central challenge facing Australian organisations in the age of artificial intelligence. The problem, she argued, is not that businesses lack AI capability. It is that they are still asking the wrong question: not how to deploy AI at scale and build the infrastructure to support it, but simply how to get better AI.

“Think of AI as like a car,” explained Ms Lindner, who recently took up the role of Senior AI Leader & Strategic Advisor APAC at Deloitte. “The issue for our governments now is not faster or better AI. It’s actually how AI will be deployed. And are we ready for that? Are our systems and structures there? So, I’d say we’re capable, but we’re not yet mature.”

It is a pointed and well-informed observation. Ms Lindner graduated from UNSW Business School in 1996 with a Master of Commerce in Information Systems and has held management and executive roles in organisations such as NAB, Westpac, Capgemini and Gartner, building a parallel career as an adviser, mentor and keynote speaker.

When she sat down with UNSW Associate Dean (International), Professor Felix Tan, the conversation ranged from legacy infrastructure and the limits of board literacy on AI, through to FinTech revolutions in the Asia Pacific region, and a three-stage framework she uses to convince senior leadership that artificial intelligence is not merely an efficiency tool.

A career forged in disruption

Ms Lindner’s working life began in 1997, shortly before the dot-com bubble burst in 2000. The experience left a formative impression, and she recalls the amount of disruption the event caused. “If a company wanted funding at that stage, they put .com at the end of the company’s name. And I think what was really important there was to realise that disruption was going to be part of my career in financial services and in technology, and the intersection of those two,” she said.

The dot-com era was followed by the rise of the web, the arrival of social media and then, perhaps more consequentially, the smartphone. But it was the global financial crisis of 2008 that Ms Lindner described as the most significant event of her professional life.

“The GFC was not something that was driven by anything that happened in Australia. I mean, this was a truly global phenomenon caused by the subprime mortgage crisis in the US, which then spread contagion throughout the world. And it spread very, very quickly. So, for me, the GFC prepared me in a way for disruption and for looking at, potentially, the end of very, very large organisations. You saw organisations that were seemingly too big to fail, failing.”

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It was at that point that Ms Lindner began to think deliberately about building what she called a ‘portfolio career’, moving beyond narrowly defined roles within banking. At Westpac, she ran cards and payments, launching contactless payment systems and mobile wallets at a time when such technologies were genuinely novel. She later moved into consulting, working across Australia and Asia, before covid abruptly collapsed travel-intensive arrangements and pushed her, like many executives, into a fully remote working model.

Now, she observed, the financial services industry and the broader economy are living through what she described as “industrial revolution 4.0”: the age of AI. “Total displacement now of the workforce, with massive layoffs and disruption – not just in tech, but in adjacent industries. You’re looking at machines now that can create code, that can analyse and write documents.” For Ms Lindner, the lesson is straightforward: professionals who thrive in disrupted environments are those who can adapt, remain agile and keep looking forward.

Australia’s AI readiness: capable, but not yet mature

When the conversation turned to Australia’s current position in the global AI landscape, Ms Lindner offered a measured assessment. Australia has a highly skilled, well-educated workforce and is reasonably well-positioned relative to its peers. The gap, she argued, is not one of technical knowledge but of scale.

To illustrate that gap, she highlighted the role of the Industrial Revolution. Many countries were at comparable levels of engineering expertise when the motor car was being developed. What distinguished the United States was not the quality of its engineers but its capacity to scale: Henry Ford’s assembly line, the interstate highway system, and the urban planning decisions that accommodated the automobile at a population level. The lesson for Australia’s AI moment, she argued, is that execution infrastructure matters as much as technical capability.

One structural challenge that Ms Lindner pointed to is legacy technology infrastructure, particularly within Australian banks and large corporates. She noted that many of the core systems underpinning payment, settlement and clearing functions are older than the careers of the people maintaining them, and that addressing this requires a degree of institutional courage that has often been lacking.

She also pointed to Singapore as a model worth studying. Australia, she said, should not feel compelled to reinvent approaches that other jurisdictions have already validated. Singapore’s government has long treated digital infrastructure as a national priority, and the results are visible in the pace at which new financial services technologies have been adopted and regulated there. “Stand on the shoulders of giants,” Ms Lindner advised. “If people are doing it well elsewhere, we’re part of a global community.”

Treating technology as a growth engine, not a cost centre

One of the more persistent frustrations Ms Lindner has encountered across her career is the tendency of organisations, and particularly their boards, to view technology expenditure as a cost to be minimised rather than a source of competitive advantage.

“For my whole working career, it has been seen very much as a cost centre. There have been pockets of innovation, but generally it’s been seen as just a very, very large line on the P&L,” she said.

Her prescription is to approach AI investment with a clear-eyed view of what returns it can generate, and to ensure the foundational conditions for those returns are in place. That means retiring legacy platforms, ensuring data is governed and maintained to a standard that makes it genuinely useful, treating cybersecurity as a competitive differentiator rather than a compliance obligation, and positioning real-time data as a driver of new business rather than merely an operational record.

She also suggested that technology functions need to be elevated from their traditional role as an execution arm of the business, and brought into strategic conversations about cloud, intelligent process automation, and emerging technologies such as quantum computing. "Organisations should be having those sorts of conversations with IT, rather than, ‘How can we do this same thing we’re doing for a bit cheaper?’ That’s AI,” she said.

A three-stage framework for winning board support

A practical takeaway from the conversation with Prof. Tan was Ms Lindner’s explanation of how she approaches the challenge of convincing boards and senior leadership teams to embrace AI not as an efficiency tool, but as a driver of growth and, ultimately, business model transformation.

She described what she called the “false trichotomy”: the mistaken belief, common among boards without technology backgrounds, that AI is simply an efficiency mechanism. Boards, she observed, tend to be composed of people who are not deeply comfortable with technical detail, and who are primarily concerned with managing uncertainty on behalf of employees, shareholders and customers. The task, therefore, is not to overwhelm them with a technical argument, but to present a structured narrative they can follow.

Her three-stage framework begins with what she termed “table stakes”: the operational efficiency gains that AI can deliver, and that most boards are already comfortable discussing. Reducing productivity drag by 20-40% is a tangible, measurable outcome that directly addresses the concerns of a board focused on cost and risk.

The second stage is what she described as the growth catalyst: using AI to accelerate time-to-market, create new products and services, and build new customer relationships. “It may be as simple as cutting the time to deliver a product down from 12 months to 12 days,” she said. “Now, if you can get that first mover advantage in a market that you would previously have not been able to access, that’s a win for the company.”

The third stage is business model disruption, which is most consequential for financial services, according to Ms Lindner. Neo banks and fintech disruptors have already demonstrated that the traditional advantages of incumbent banks, including their systems, compliance frameworks and balance sheet depth, can be eroded by agile, technology-native competitors. AI, she argued, has accelerated that process by levelling the playing field in ways previously impossible.

“For me, that is: how do you disrupt yourself?” she asked. “How do you look at partnerships with your vendors? How do you go into proper joint ventures with technology companies? How do you bring them in early, not at the last stage, when your strategy is done, and you’re looking for a vendor or a piece of software to implement it?”

Her advice to executives navigating board conversations was to resist the temptation to lead with disruption. The more productive sequence is to establish credibility on efficiency, build the case for growth, and then open the question of transformation.

Open banking, compliance and the trust deficit

The conversation with Prof. Tan turned to open banking and the tension between regulatory compliance and the pursuit of new digital revenue streams. For Ms Lindner, this is one of the defining strategic tensions in contemporary banking: organisations that operate within a framework of public trust must prioritise compliance, but doing so exclusively leaves them vulnerable to competitors who are freer to innovate.

Learn more: Regulating AI in Australia: Challenges and opportunities

Australia’s Consumer Data Right framework is, in her view, relatively mature, and there is no fundamental legal or regulatory impediment to open banking. The slower variable is consumer behaviour: people tend to remain with financial institutions where they have established trust, and persuading them to switch to a new bank requires a compelling value proposition. 

For organisations seeking to build that proposition, Ms Lindner’s recommendation is to lead with a robust compliance posture, a clear data protection strategy, and a demonstrated capacity to operate within the existing banking ecosystem – before differentiating through personalised lending and credit products.

Building a resilient career in the age of AI

For students and early-career professionals, Ms Lindner’s most important message was that the linear career path, the notion of ascending a single ladder within a single organisation over decades, has effectively ceased to exist. She observed that over the course of her own career, she held roles across traditional banking, technology-intensive operations, management consulting and executive advisory work, with a significant pivot in 2014 from one domain to the other.

“The most important qualities for building a durable career are resilience, self-awareness and a willingness to take risks. Understanding your value requires sustained self-reflection, and that value must be actively managed rather than passively accumulated,” explained Ms Lindner, who added that continuous learning, involvement with universities and professional communities, mentoring, and the maintenance of a trusted personal sounding board are all key to her own sustained career growth.

Her advice to a graduating class of 2026 (which she was preparing to address on the evening of the interview with Prof. Tan) distilled the lesson of three decades into a single instruction: “Do not think of yourself as either a technical or a non-technical person, because the ability to translate between those two worlds is now among the most valuable capabilities the market can reward,” she said. “You’ve got to interact in both worlds now, and you’ve got to be able to translate between the two.”