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When we were working out who to approach for the first in our “That Won’t Pass Audit” interview series with finance leaders, Chris Petzoldt’s name quickly rose to the top. That’s because few people have had a closer view of how finance, strategy and growth are converging than Chris.
His 25-year consultancy career has given him a perspective that’s sought after enough to earn Chris the position as guest speaker at the 2026 APAC Chief Strategy Officer Conference this September. As Founder and Partner of Pretian Squared, he’s also putting his expertise to work as a venture partner and angel investor.
What does that expertise tell him about the current state of the market? Some is paradoxical. Over the past few years, Chris says, digitalisation and automation have been made faster and more consistent due to the implementation of cloud-based systems and automated tools, yet many organisations are still playing catch-up. “In theory, finance should actively support organisational growth, long-term strategy and value creation,” he explains. “In practice, however, many organisations have struggled to fully make this transition.”
Chris believes that many finance teams are still weighed down by manual processes that should have disappeared years ago, leaving them to do unnecessary manual work rather than focus on some of the modern initiatives that are more deserving of their limited attention. “Most finance teams remain organised around compliance, budgeting and periodic reporting, yet they are increasingly expected to guide investment decisions and strategic growth initiatives,” he said.
For Chris, the path forward for finance leaders means saying no to AI as a quick fix. In his view, too many companies view AI as merely a standalone, isolated solution, rather than using it as Chris advises: as “a capability that should be embedded across the broader operating model”.
With Chris’ hope for the future clear, we began our conversation with the present. That’s why we started by asking him what exactly has changed for the role of the finance function in recent years, and what that might mean for the future he foresees.
Over the last few years, the finance function has increasingly been expected to move beyond a narrow focus on historical results and compliance reporting toward a more forward-looking role that helps shape future decisions. In theory, finance should actively support organisational growth, long-term strategy and value creation, rather than concentrating solely on cost control and retrospective analysis. In practice, however, many organisations have struggled to fully make this transition, often due to legacy systems, skills gaps or competing regulatory demands.
Many commentators point to technology as the primary driver of change within accounting and finance over the past five years. This is accurate to the extent that digitalisation and increased reporting expectations have made the adoption of technology unavoidable. Automation tools, cloud-based systems and advanced analytics have changed how financial data is processed and presented, enabling faster and more consistent reporting.
At the same time, regulatory authorities worldwide have shifted away from narrowly defined, rules-based compliance toward a broader emphasis on outcomes, ethics and integrated risk management. Areas such as data privacy, financial stability, cybersecurity and environmental, social and governance considerations now form part of the compliance landscape. This expanded responsibility has placed additional pressure on corporate finance teams, which must deliver accurate regulatory data while also providing meaningful insights for risk assessment and strategic decision-making. As a result, the use of technology to enhance efficiency, transparency and analytical capability is no longer optional but essential.
In many organisations, core activities such as reconciliations, journal entries, management reporting, budgeting and forecasting still rely heavily on spreadsheets and manual intervention. While these processes are familiar and perceived as controllable, they are time-consuming, prone to error and difficult to scale.
Pretian Squared works with many technology service providers that support businesses in leveraging digital tools to improve operational effectiveness. Our experience shows that the biggest obstacle to automation is not the lack of available technology, but legacy constraints. These constraints extend beyond outdated IT systems to include entrenched operating models, historical role definitions and long-standing processes that were designed for a different business environment.
Over recent years, the finance function has been expected to evolve from primarily analysing past performance to actively shaping future decisions. In principle, finance should support growth, strategic planning and value creation, rather than focusing solely on reporting and cost control. In practice, many organisations have not yet realigned their structures, skills or incentives to enable this shift.
Most finance teams remain organised around compliance, budgeting and periodic reporting, yet they are increasingly expected to guide investment decisions and strategic growth initiatives. This mismatch creates frustration for both finance professionals and business leaders. What is often underestimated is how central finance has become in translating operational activity into measurable value, making automation a critical enabler of that role.
To date, AI has delivered tangible but largely incremental improvements in finance functions. It has enhanced efficiency by automating reconciliations, accelerating close processes, improving forecast accuracy and enabling faster, more consistent reporting. These gains are meaningful in day-to-day operations, but they tend to optimise existing processes rather than fundamentally redesign them.
The growing capability of AI to automate routine and analytical tasks has understandably raised concerns about its impact on roles and workforce structures. There is a perception that technology will increasingly assume responsibility for core finance activities, leading to operational restructuring or, in some cases, job reductions. Few functions experience this tension as acutely as accounting and finance, which have historically been associated with cost control, performance monitoring and, in some organisations, aggressive cost-cutting mandates.
However, the near-term reality points to an expansion rather than a contraction of the finance role. Generative AI is enabling real-time operational monitoring, more integrated governance and compliance processes, and increasingly sophisticated forecasting and scenario modelling. These capabilities allow finance teams to move closer to the centre of decision-making. Rather than functioning primarily as a cost centre, finance and accounting become value-adding partners that help organisations optimise performance, manage risk and shape strategic direction. In this context, the most realistic near-term value of AI lies in augmenting human judgment, improving insight quality and freeing finance professionals to focus on higher-impact work.
Many organisations underestimate how central finance has become in translating operational and commercial activity into measurable value. As businesses shift toward digital products, usage- or outcome-based pricing models related to AI-driven services, traditional approaches to revenue recognition, cost allocation and profitability analysis are increasingly inadequate. These changes require finance systems to integrate seamlessly with product, sales and operational platforms, yet in many cases those systems remain fragmented.
Legacy enterprise resource planning systems often struggle to connect with modern data sources such as product analytics, customer usage data and AI cost drivers. As a result, finance teams rely on manual workarounds, reconciliations and offline models to bridge gaps between systems. This fragmentation undermines data accuracy, slows decision-making and limits the organisation’s ability to respond quickly to changing market conditions. It also makes it difficult to produce a single, trusted view of performance across functions.
This challenge is particularly evident in the context of AI investment. Research from Pretian Squared’s AI Monetization Pulse Report shows that organisations are investing heavily to address both the opportunities and risks associated with AI. However, when finance is not integrated into discussions about how value is captured, these investments often fail to generate sustainable returns. Finance should be at the table when answering fundamental questions around pricing, value drivers and long-term monetisation. The shift required is not about finance doing more work, but about engaging earlier, working differently and operating much closer to commercial decision-making.
A common mistake is to begin the digitisation journey by selecting new tools before clearly defining the business outcomes they are meant to support. When digitisation initiatives are not anchored to a clear goal and value proposition, they often become expensive, politically sensitive and difficult to justify, which quickly erodes stakeholder support.
Many organisations also approach AI as a standalone solution designed to optimise isolated processes, rather than as a capability that should be embedded across the broader operating model. Treating AI as a simple add-on to an existing technology stack limits its impact and increases the risk of duplication, integration issues and inconsistent data governance. Research has shown that the largest ROI is generated by compounding use of AI across several tasks and functions. Finance leaders need to frame AI and digitisation as enablers of better decision-making, improved insight and long-term value creation, rather than as purely technical upgrades.
Pretian Squared was established to help organisations evaluate value creation in a more holistic and strategic way. Experience shows that fragmented, piecemeal changes rarely deliver a meaningful return on operational spending. Instead, successful transformation requires a coordinated approach that aligns technology, processes and people around shared objectives. For companies seeking to adopt AI, this means building an infrastructure grounded in clear business value, designed to scale with the organisation and governed by measurable, well-defined standards. By focusing on outcomes rather than tools, finance leaders can build credibility, secure buy-in and make progress even with limited internal resources.
Knowledge is power and data the new moats. As the stewards of an organisation’s financial and operational metrics and data, finance and accounting teams hold a uniquely strategic position. Historically, performance has been judged largely on accuracy, timeliness and compliance. While these measures will remain important, they will no longer be sufficient on their own.
Increasingly, organisations will evaluate whether finance has actively contributed to improving pricing decisions, helping to defend the companies positioning, deepening the understanding of customer value and guiding smarter choices around investment, talent and organisational development. This shift requires finance to be embedded much earlier in strategic discussions, influencing decisions before outcomes are realised rather than simply analysing results after the fact.
The future measurement of finance performance will focus less on outputs and more on impact. Leaders will ask to what extent finance has shaped operational development, supported business model evolution and enabled sustainable value creation. With the help of AI this includes the ability to translate complex data into actionable insight, align financial metrics with strategic objectives and support faster, more confident decision-making across the organisation.
Finance teams that embrace AI in a more holistic way will be best positioned to meet these expectations. By integrating advanced analytics, real-time insight and predictive capabilities into everyday workflows, finance can expand its influence and relevance. Those that make this shift will help define not only the future of the finance profession, but also the long-term success of the businesses they support.
