Interview with Adrian Grossenbacher - CFO Accelleron

Deloitte: How is AI transformation different from previous waves of technology change in finance?

Adrian Grossenbacher: Finance has undergone significant transformation over the past decades through standardisation and digitalisation, making processes more efficient. What is different now is that the change is both broader and faster. AI is accelerating expectations around speed and insights in ways we have not seen before.

For Accelleron specifically, we are in a strong demand environment where the priority is ramping up production, scaling delivery and meeting customer needs reliably. My team works closely with the divisions and supply chain to ensure we are not just reporting on performance but actively enabling it.

The key insight here is a fundamental shift in how we think about finance’s role. We are moving from reporting performance to enabling performance. In the past, we were drowning in data, looking in the rear mirror too much. With modern technology, we aim to spend less time extracting insights and more time discussing them with the business to drive decisions.

Deloitte: How will AI transform finance over the next three years?

Adrian Grossenbacher: Over the next three to five years, I believe AI will increasingly remove transactional efforts from finance. We will see faster reconciliations, automated variance explanations, and improved forecasting - which is super important as a co-pilot steering through an uncertain, volatile and demanding world. Better scenario modelling will also become standard.

But the real transformation is in how we work. AI agents will support repeatable, transactional work, while people focus more on judgment, risk assessment, business partnering, and stakeholder management. By doing so we will shift from transaction-focused to insight and decision support-focused roles. We will approach this transformation pragmatically – introducing AI step by step, testing and validating outputs carefully, and scaling only once we are confident in the quality and robustness of the results.

This is a long-awaited shift enabled by modern technology. But here is what is crucial: accountability ultimately remains with the human. AI supports as the co-pilot, but governance and judgment stay with the finance team. That is essential.

Deloitte: What are the talent implications of AI adoption?

Adrian Grossenbacher: This is where mindset becomes critical. Finance needs to be even more commercial and business-driven, connecting operational reality with financial outcomes. This requires data literacy and the confidence to challenge and interpret insights, not just produce reports.

When it comes to talent, we focus on three things: First, recruit for digital fluency. Second, upscale our existing teams through programs like our citizen programs, where we take finance colleagues and enable them with modern technology to build bridges between classical finance and AI/IT experts. Third, run change in phases to protect day-to-day delivery, which is still our license to operate.

The citizen program approach is particularly important. Without domain knowledge, AI tools give you 80-90% good insights, but to get closer to perfection, the human needs to do the final refinement. These citizen programs create that linkage. They help the entire finance function become more fluent in AI literacy, which is essential because AI is a technology we will all use tomorrow.

Motivation improves when people see AI as removing transactional tasks and elevating roles into decision support and value creation.

Deloitte: How do you balance AI investment with financial discipline?

Adrian Grossenbacher: Financial discipline means scaling AI investments progressively based on evidence. We use pilots to validate ROI before full deployment. But the critical point is that, once deployed, the solution must be embedded in day‑to‑day operations and actually used.

I have seen too many cases where we make a wonderful investment in technology but do not invest in people to use it properly. We have a responsibility to make best use of our investments because they really can increase productivity and free up time for value-added work.

AI investments should have a break-even of one to two years at most. But equally important is maximizing the value of what we already have. We have invested in IT trainers. That is often overlooked but incredibly important.

Deloitte: What does the future of finance look like in three years?

Adrian Grossenbacher: You want finance operations to be as efficient and effective as possible, asking what is driving business performance, and where can we improve.

IT and software investments are key drivers for making finance more efficient and freeing it up to create real value. Value is still created between people—internally and towards customers. AI is here to act like a big radar, screening for risks and opportunities. Finance looks at this radar and links it to the business.

The balance is critical: technology and automation on one side, human in the loop on the other. We are empowering colleagues to navigate a rapidly changing world. Ultimately, adaptability and resilience are the essence.