How finance can start to use AI automation

Shamus Rae, founder and chief executive of the UK-based audit tech company Engine B, has a firm view on what artificial intelligence (AI) is likely to mean for accounting and finance in the coming years.

“I think a major skills and culture change is going to take place — and it’s going to happen fast,” Rae said.

Finance professionals, he said, are “going to be doing more business partnering, and they’re going to have a different set of skills.” They will, he added, be communicating with businesses, working with businesses on hypotheses and plans “and not hiding away with the numbers.”

This is because AI and associated technologies are going to automate much of finance. It’s already happening. So far, the change has affected relatively basic work. However, increasingly, technology is moving on to complex tasks. Moreover, the pace of transformation is accelerating.

So, what are some of the areas in which AI is being used? What can we expect in the years ahead? And what areas should finance professionals be looking at?

Where to start with AI automation

AI automation can improve efficiency and speed, particularly in operations in which processes have been streamlined.

“Processes which benefit from AI and finance automation are those that currently have a high level of manual input, involving large datasets and being time-critical in nature,” said Haifa al Khaifi, FCMA, CGMA, finance director of PDO (Petroleum Development Oman). “My advice before undertaking your AI or finance automation journey is to ensure you have robustly mapped all your key processes.”

By walking through a process, you will discover that there are improvement opportunities that are easy to implement, al Khaifi said. “There are good tools for this. Personally, I champion the use of lean methodologies and have had significant success with agile methodologies. Once you have simplified the processes and eliminated waste, you are in a good position to select processes for AI or automation.”

PDO has already extensively deployed automation solutions, she said. “In my department, we have implemented user query-based automation tools so that staff can self-create dashboards, drawing on multiple datasets.” Also, machine learning is being used to read extracted documents and PDO intends to implement a solution to forecast operating expenditures.

Paolo Lo Monaco, ACMA, CGMA, group CFO of Dubai-based Al Khayyat Investments (AKI), said that, in general, technology has augmented finance capabilities to generate value for the business over recent decades. That journey started with desktop automation and continued with robotic process automation (RPA) to free finance professionals from simple repetitive tasks. Desktop automation is the use of software robots to automate tasks on individual users’ workstations (such as logging in to websites or extracting data from emails). RPA is used to automate large numbers of repetitive, rules-based tasks such as invoice processing and payroll management.

“More recently, there has been a move towards intelligent automation, which combines all the basic automation with artificial intelligence and analytics,” Lo Monaco said. “This means we can develop more touchless processing and intelligent workflows to materially reduce the cost per transaction for all repetitive finance processes.” (See the sidebar, “AKI’s Digital Transformation”.)

Automating risk analysis

Over the past year, Lo Monaco added that there has been an explosion of interest in generative AI as exemplified by ChatGPT. “There are now more programmes capable of researching and interpreting large sets of data to produce valuable insights and instant responses and generate summary reports.”

AI will also be applicable to more sophisticated areas such as analysing risks. “If you are in a large or mediumsize organisation in the United States and you want to see what risks the business might face over the next six months, you could use generative AI to look at all your competitors,” Rae said. Their Form 10-K, which includes company risk factors, is publicly available on the US Securities and Exchange Commission (SEC) website, and AI will be able to look at hundreds of these, generate an overall picture, and offer insights. AI, he added, will also be hugely important in areas like spotting fraud — again, because it can parse vast amounts of information and look for patterns that humans may not be able to spot.

Staffing requirements

Not all AI will be behind the scenes. The rise of AI assistants (such as Microsoft’s Copilot) will also represent a significant change. AI assistants are software programmes that follow voice or text commands to complete tasks ranging from dictation to research to generating reports. Their capabilities are growing rapidly and, in coming years, finance professionals are likely to find themselves augmented by AI that takes over some of the more mundane parts of their jobs.

Inevitably, this will result in a change in the staffing requirements of finance departments and accountancy firms. Traditionally, junior staff have done a lot of transactional, monotonous work, Rae said. The result tends to be high staff churn. “That’s going to go — and where we used to have a pyramid-shaped staff age profile in finance, we’re going to have a diamond shape,” he said.

Strategic framework

“Finance must establish strong data and risk controls to support safe use of AI and generative AI,” al Khaifi said. “The implementation of AI and gen AI must be done in accordance with a well-defined AI risk strategy addressing ethical principles.”

Lo Monaco said that AI should not just be viewed as an add-on — if it is, it’s unlikely to deliver. “If an AI digital transformation is to succeed, it is very important to have a clear AI strategy in place which aligns with finance.” It’s necessary, he said, to map out a vision, set goals, and have clear metrics for success. “Of course, you also have to bring staff along,” he added. “It’s very important to connect your AI vision with a clear people strategy in terms of what is required [for] change management.”

There also needs to be transparency around AI and not just blind trust, Lo Monaco said. “We need to ensure the accuracy of the responses by implementing review programmes. So, it’s very important to maintain proper quality control from the finance team, making sure that we don’t get a kind of black box response from the system.”

The next few years should be a very exciting time for finance. One thing may slow the march of AI down: regulation. “I think the accounting industry will stay in its current mode for longer than it needs to because of the regulators,” Rae suggested.


AKI describes itself as a new breed of family business that works across a portfolio of industries and partnerships. Founded in Dubai in 1982, it has grown from a single pharma company into a diversified enterprise with a presence in nine countries across the Middle East and North Africa (MENA) region.

Paolo Lo Monaco, ACMA, CGMA, group CFO at AKI, said the company has identified two high-level areas for digital transformation underpinning AKI’s “Finance Vision of the Future.”

“One is what we call the ‘Finance Factory’, our shared finance service centre, which is basically our financial operations and where we think AI can support automation efforts for all the transactional processes.” Here, he said, AKI started with a review of its purchase-to-pay process delivered by the newly created finance Centre of Excellence with an end-to-end process streamlining the identification of key cost drivers, and automation efforts supported by RPA. AKI also implemented a dashboard to monitor the Finance Factory’s process performance, both in terms of cost per transaction and service-level-agreement (SLA) process performance. This approach allows AKI to deeply monitor cost per transaction across the Factory, leveraging technology to deliver material efficiencies while the group is growing in scale.

“We are now in the process of extending this approach to the other finance operations in the Factory [areas], starting from accounts receivable and then general ledger consolidation,” he said. “Next year, we will also move into treasury operations. So, the first pillar of our digital transformation is about reducing cost per transaction in finance and treasury operations. The second pillar is real-time finance augmenting the company’s financial planning and analytics capability to impact financial performance.”

“We have recently launched Qlik Sense self-service finance dashboards,” Lo Monaco added. This is an AI tool that allows both finance and nonfinance users to interrogate the system in real time and do deep dives on the financial performance of their businesses, enabling finance teams to quickly identify areas of intervention to enhance business financial performance.

He explained: “This augmented capability and focus is a key enabler in our vision to reposition the finance function as a trusted value creator for stakeholders. This does require a reskilling of the function, hence why AKI has recently worked with [AICPA & CIMA] to review its finance competency framework and set up the AKI Finance L&D Academy to enhance the finance team’s skillset for the future.”

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