On a crisp winter morning at the Sheraton Grand London Park Lane, finance leaders packed the hotel’s sumptuous Tudor Rose Room to discuss an issue that will shape the future of organisations across all industries. The topic of debate over breakfast was financial excellence in the age of AI, with a specific focus on building an AI strategy for accounting and finance that would yield real long-term value.
To unearth what an effective strategy might look like, FDE, alongside event partners Workday and Deloitte, brought together speakers with very different takes on the implementation of AI, showing clearly where the promise of AI and real-world experience converge and, crucially, where they differ.
Providing the invaluable perspective of the end user was Kirsten Baggaley, Finance Director at Railpen, which manages, amongst others, the UK’s Railways Pension Scheme. Railpen’s brief is to oversee investments in the region of £34bn on behalf of 350,00 members, and to administer the payment of their benefits. Railpen Finance is in the process of laying the foundations to ensure that AI initiatives succeed in three key areas – data, processes and people.
Joining Kirsten was Fionntainn O’Hagan, UK Practice Lead at Deloitte, who focuses on leveraging technology to provide industry accelerators that can enhance business efficiency and insights for clients. He has taken an in-depth look at where and how AI can have the biggest impact in finance and accounting, particularly the solutions in development at Workday, the provider of enterprise cloud applications used by more than 10,000 organizations around the world.
Marion Carr, Product Marketing Director at Workday, was also on hand to explain how those solutions are built around AI and machine learning, and how they are positioned to optimise finance and accounting processes to deliver maximum efficiency and ROI.
Promised potential
The session began with a brief introduction to Workday Illuminate, a next-generation AI platform operating across the human resources (HR) and finance cloud that uses vast datasets to power intelligent agents and automate complex tasks, transforming processes like hiring, planning, and financial close into more efficient, strategic workflows for businesses. The solution goes beyond simple AI to provide deeper contextual understanding, proactive insights, and automated agents that work alongside employees to handle repetitive tasks, leaving skilled employees to focus on high-value work.
Examining the use cases for such solutions, O’Hagan explained that the best approach is to look not only at what an organisation needs now, but what it might need three-to-five years in the future. Sophisticated AI platforms are transformative in nature, and their potential to reshape the way a business performs is so great that it should not be limited by short-term models. Focusing on the core elements, notably the quality and accessibility of datasets, is the highest priority and serves as the key to unlocking the potential of a platform such as Illuminate.
“Data is the engine room,” he remarked. “Having it right just at the point you migrate to new systems is not going to cut it. Also, your underlying data model should be personal and reflective of the business you aspire to. It needs to be at the forefront of your thinking from data capture to data use.”
For Railpen, data quality has been a huge challenge. Baggaley explained that the organisation – currently on a 1999 GL augmented by bespoke applications – is in transition, and the lines between finance and operations are blurred. In implementing Workday solutions, knowing what data it has and how to improve its quality have been key priorities. The goal is clarity, drawing clear lines between operational and financial data.
Beyond data, process standardisation has also been at the top of the agenda.
“AI works best on standardised data,” Baggaley remarked. “Right now, we are far from that, but doing the ERP implementation has given us an opportunity to standardise and map processes. We have a lot of complexity in our billing processes, which involved a lot of data sources, and we didn’t have a clear definition of who the customer was. We have built a lot of rules-based processing into Workday, and that sets us up to be able to look at where AI can build on and improve this.”
Focus on the future
As Baggaley explained Railpen’s journey it became clear that the organisation is ahead of the curve in addressing some of the big challenges of AI and starting to see some benefit. After all, a recent report by MIT, cited by O’Hagan, revealed that 95% of organisations are reporting zero measurable impact on P&L from the implementation of generative AI.
One reason is the enormous number of potential use cases – a challenge faced head-on by Railpen – which requires an intense focus on where real value can be generated. As MIT revealed, on average 50% of GenAI budgets are going to customer-facing top line functions such as sales and marketing, despite the fact that back-office automation, including AP/AR automation, often yields a better ROI.
“Agentic AI is where I see some really big value but that is a future piece, but there is massive potential here in terms of both reducing human time spend and increasing control,” Baggaley remarked.
In the fascinating debate that followed, fuelled by many questions from audience members across a range of business from data security specialists to the legal sector, the panel addressed everything from transition management and data quality to the training and technical skills needed to ensure that the human element is able to get the best of the AI-based tools at their disposal.
What emerged was an illustration of how well understood it is that AI will ultimately change almost every aspect of business, not least in the finance and accounting space – yet there still remains little in-depth understanding of where and how to start on the road to building confidence and trust in the rapidly developing suite of tools that is available, and where to start maximising ROI.
The experience of trailblazers like Railpen will certainly go a long way to overcoming those challenges, as will the efforts of solution providers such as Workday, which is itself working hard to ensure that as its toolkit becomes more sophisticated it remains transparent and explainable.
That level of control and clarity will be crucial in ensuring that AI delivers on its enormous potential, particularly in the finance and accounting arena. Listening to the opinions and experiences expressed by both panel and audience, it is clear that organisations of all kinds are starting to wake up to the potential of generating ROI from AI by moving their attention to back-office functions such as finance, rather than sales and marketing, and that the right strategy, alongside the increasingly sophisticated set of tools available, could start to pay dividends as part of a coherent long-term strategy.
While the event may have generated as many questions as answers, there is no doubt that it has helped those in attendance to see a little further down the road to building an AI strategy for accounting and finance that would yield real value in the long term.
