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The skills you need to work with AI
The rapid rise of AI from the stuff or science fiction to a staple of the workplace has created a defining moment for accountancy and the individuals working within it.
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Level up your numbers
The rapid rise of AI from the stuff or science fiction to a staple of the workplace has created a defining moment for accountancy and the individuals working within it. As such, embracing AI is no longer an option but a necessity for accounting students.
AI is revolutionizing the way financial data is processed, analysed, and interpreted, generating new opportunities for accountants by automating routine tasks, reducing errors, generating insights, and enhancing decision-making.
According to Mark McDonald, senior director at technology research and advisory firm Gartner, things are going to change more in the next 10 years than they have at any other time in history of accounting and finance.
James Osborn, chief digital officer at KPMG UK, bills generative AI – deep learning models like ChatGPT that can generate original and realistic text, images, or other media from prompts – as “transformative technology”.
Even in the form of a lowly mobile app for iOS or Android, AI can immediately boost personal productivity by at least 20%. It’s as easy as using Google and a lot more powerful.
“I think it will infuse everything we do over the course of the coming years.” Osborn said. “The winners in this will be those with the richest internal data sets and the most employees who are willing to change the way they work.”
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An AI 101
Before delving into the application of AI in accounting, it's essential to grasp the fundamentals. In accounting, AI is used for automating routine processes, analysing large datasets, and making predictions based on patterns.
But to become proficient in AI, accounting students should familiarize themselves with the tools and software commonly used in the industry. QuickBooks, Xero, and Sage already incorporate AI elements, streamlining tasks such as data entry, reconciliation, and financial reporting.
The main pathway for mid-sized accounting firms or finance teams to get started with AI is through off-the-shelf solutions. The advice from experts is to begin experimenting with low risk, high impact areas like content generation or marketing where there are no data privacy issues.
Second, it’s wise to get employees to work in peer groups so they can swap learnings, spot risks, and establish sensible boundaries. Understanding how to leverage these tools can significantly enhance efficiency.
The best thing accountants can do is be tech savvy about how AI is going to be used in the profession, Vsu Subramanian, who heads up Avalara’s AI initiatives, said.
“It is good to have an AI 101 and demystify what AI is. Once you do that it will start to make sense, you will be a more informed and more valuable accountant to the future of the profession because it is going to transform and you want to be part of the transformation,” he said.
"To become proficient in AI, accounting students should familiarize themselves with the tools and software commonly used"
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Critical thinking and evaluation skills
Human judgment is still an indispensable part of the job. Practitioners see AI as a sidekick to humans, but not a replacement.
“We see it applying to all our audit, tax, advisory and our internal uses pretty extensively,” Osborn at KPMG said. “The practitioner becomes the co-pilot with the generative AI that is on your data, and they can prune and check and ensure that the model is good,
There are also major concerns around ‘hallucinations’, which are confidently stated untruths, which can often go undetected until it is too late. AI algorithms can also inadvertently reflect biases in the data they were trained on, leading to discriminatory outcomes or unfair treatment.
Critical thinking is key. Adam Williamson, AAT's Head of Professional Standards, said one of the problems with generative AI is the risk that “if you ask slightly the wrong question and you get an answer that looks like it could be realistic but is wrong”.
Indeed, while AI may replace the boring, repetitive, and tedious tasks, it will not replace the human factor of relationship development, and the accountant’s role as a trusted business adviser.
“That is where you need assurance. You still must do that critical thinking. The actual use of the tool is not the issue, it is the outcome, it is what you do with the information that you are being given,” Williamson said.
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Ethical considerations of AI in accounting
While the increasing adoption of generative AI tools by accountants does not herald the onset of AI Armageddon, its use poses several commercial and ethical risks that practitioners will need to grapple with.
For instance, if you get an unexpected – and convincingly justified - answer using generative AI to advise a client, how far should you consider whether accepting that answer is ethical?
“I think the answer is as it always was: I ask myself ‘do I honestly believe that this is the right answer?’ If I do, then I can proceed, if I don’t then I either ask for a second opinion from someone I trust or I simply don’t proceed,” former ICAEW president Paul Aplin said. “Over the years I’ve found that the ‘does it feel right?’ test is pretty reliable.”
One of the biggest challenges is the rights of content owners. AI systems may collect and process large amounts of personal data, raising concerns about privacy and the security of that data and the legality of its use. There are also concerns over employees uploading sensitive data.
Data protection is critical,” Rob Hackney, tax manager at DSG Chartered Accountants, said. “There are fewer limitations on what we can do with company data but with individuals you need to make sure you have proper consent for any processing done on it.”
Data analysis and interpretation skills
While not all accounting students need to become expert programmers, having a basic understanding of programming languages like Python can be advantageous. Many AI applications in accounting are built using Python, and knowing how to work with code allows for greater customization and adaptability.
AI is not just about automating existing processes; it also enables accountants to make more informed decisions through predictive analytics. Accounting students should explore how AI can be used to analyse historical data, identify trends, and make predictions about future financial outcomes.
AI platforms can analyse historical data and provide predictive insights on trends, cash flow forecasts, and other relevant metrics that facilitate decision making.
In this new AI-driven environment accountants will be expected to use machine learning and data science techniques to analyse information and understand what is happening, why it happened and what is going to happen in the future.
“That is not something that arithmetic helps us with. That is something the field of data science is better suited for,” McDonald said. “The financial professional of the future will need to have skills that combine accounting and finance knowledge with statistics and programming.”
KPMG’s Osborn believes accountants will need to develop the art of ‘prompt engineering’ – feeding the right information and questions into the model in order to get meaningful or accurate results.
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