At The Fintech Times, we have discussed whether the hype around artificial intelligence (AI) is justified or not. Supporting the case that it definitely is, paytech Equals Money has published research revealing that 95 per cent of financial leaders are using, or considering using AI in their processes.
When it comes to experimentation, the research found that 77 per cent 400 UK financial decision-makers are actively testing the technology. In fact, a further 18 per cent of respondents are looking to adopt AI tools in the near future in a bid to boost efficiency, improve decision-making and streamline tasks.
This comes as the research reveals on average UK employees spend 65 minutes a day on automatable tasks, totting up to a whopping 38 days a year.
Financial processes were shown to be a key area for automation, with 59 per cent of businesses having automated receiving payments, issuing payments (52 per cent) and generating invoices (57 per cent).
Top processes businesses want to automate:
- Buying or spending in foreign currency (46 per cent)
- Receiving market analysis (45 per cent)
- Tracking expenses (45 per cent)
- Inventory management (50 per cent)
- Regulatory compliance (50 per cent)
- IT Operations (46 per cent)
Steve Paul, deputy CFO at Equals Money comments: “The foundation of finance is reconciliation, comparing one number to another and whether it matches. AI is very good at following rules, and if you can design, implement, and then automate those rules, then it’s clear to see the huge part AI will play within finance. This will then allow finance teams to be truly analytical and provide greater value for their organisations.”
In terms of the effect, AI is having on employees, 85 per cent of businesses that have already adopted AI tools found it to have impacted the workload, with almost half (46 per cent) claiming it has freed up employee capacity by reducing or eliminating certain tasks. However, 39 per cent felt that some job roles were at risk of being made redundant due to automation.
Is automation necessary?
Among the top barriers to adoption, concerns surrounding job security were cited by a third (33 per cent) of respondents. Additionally the cost of investment (42 per cent), worries about security (48 per cent), doubts over accuracy (41 per cent) and lack of understanding (36 per cent) were also noted.
Top processes businesses believe should not be automated:
- Answering calls (34 per cent)
- Developing relationships with suppliers and clients (34 per cent) – Booking travel and accommodation (31 per cent)
- Buying or spending in foreign currency (30 per cent)
- HR services (27 per cent)
James Poulter, innovation strategist and AI keynote speaker, comments: “While many have concerns about AI making certain roles redundant, with increased adoption AI will actually create a number of specialist jobs to oversee its operation. Similarly, when correctly implemented, AI can be used to help junior team members learn and develop so there is real scope for it to improve at all levels going forward.”
Benefits of automation
Countering these challenges, almost half of respondents cited cost savings (49 per cent) and improved accuracy and standardised work output (33 per cent) to be the top benefits of AI adoption.
Other key benefits included improved efficiency and time savings (51 per cent), greater access to insights, analytics and up-to-date reporting (32 per cent), as well as faster payment processes (25 per cent.)
Recognising these benefits, businesses are investing significantly in AI, with a mean spend of £74,297,52 per business in 2024 alone.
Paul added: “Embracing AI automation is crucial for finance leaders to gain a competitive edge. We must be receptive to change and treat AI adoption like any other transformative project. The real risk lies in being slow to adopt, allowing competitors to pass us by.
“Get AI right, and we boost decision-making, efficiency, and free up time for strategic work.
“That’s not to say we should let AI run unchecked – it’s our job as decision-makers to ensure the correct level of oversight is applied to AI processes and that they are effectively managed. Not all processes should be automated. Therefore, it’s key to understand which tasks can be given to AI, and which should be left to the experts.”
