Artificial Intelligence in Accounting

AI in accounting uses the machine learning tool to identify data patterns in order to produce detailed financial analysis. Its natural language processing recognition, automates repetitive tasks such as data entry to significantly reduce labour hours spent on mundane tasks.

AI's ability to automate these routine manual tasks will revolutionise how accounts payable and receivable will operate in the future both in time taken plus in error and omission reduction.

Adopting AI is not designed to replace accountants or their staff, it's aim is to augment their capabilities, allowing them to handle more clients, increase financial analysis and improve service quality.

Some accounting roles as we know them today will disappear. Those staff will upskills to more interesting AI supervisory and analytical financial roles.

Moving forward, predictive analytics will become standard in business decisions generating improved financial stability and better growth.

Whilst higher value work roles are emerging through AI, the human touch remains essential in accounting.

Skills such as judgment, ethics, and communication are irreplaceable, and human interaction continues to be a vital component of the profession even as AI automates routine tasks.

What is AI in Accounting - How is it Different from Automation, RPA, and Generative AI

Whilst AI, automation, RPA and generative AI in accounts undertake repetitive data entry tasks, each method completes the tasks differently and with varying degrees of complexity; whether through an AI tool that delivers robotic actions or through human brain simulation.

AI's machine learning ability to process unstructured data, automate routine tasks, and provide immediate insights is transforming the way accounting professionals work.

These technologies streamline workflows such as the processing of invoices, financial reporting, compliance, and audit preparation, leading to greater efficiency and a reduction in human error.

What is Artificial Intelligence in Accounting:

How is Artificial Intelligence Different to Automation

Generative AI in Accounting

Comparisons can be seen in the table below

Will AI Replace Accountants or Replace the Repetitive Tasks

The good news is human accountants are here to stay. Roles will become analytical through the changing AI information empowering accountants to deliver higher level advice. Accounting assistant job security will remain, but in an AI support and supervisory way.

Companies will be able to work with and make decisions from financial reports and analytics that were never possible before.

While AI can automate many processes, accountants bring professional scepticism, ethical decision-making, and the ability to interpret insights from data, which are qualities essential for complex decision-making and maintaining trust.

Many accounting professionals are still learning how to leverage the depths of AI effectively. In the future, they will be expected to give advice on strategic planning and risk assessment to a depth that wasn’t available in the past.

Clients, as they too become proficient in AI, will expect higher-levels of efficiency and deeper insight from their accountants. However various research concludes, 62% of accountants have expressed concern about AI-generated errors, and 37% are concerned about job stability due to AI.

Myths About AI

How is AI Used in Accounting Today?

AI is changing the face of accountancy today. It is no longer a back dated single transaction process. AI analysis has allowed it to become a forward-facing advisory service for clients and customers.

The adoption of AI in accounting is expected to grow significantly, with many firms recognising its potential to improve efficiency, maintain competitiveness and drive decision-making.

What AI Does to Accounting Firms

AI Changes Hours Charged to Clients

In the accounting industry automating routine tasks like data entry, invoicing and reconciliations will significantly reduce the hours charged to a client for those tasks. AI tools also boost efficiency by improving overall productivity and reducing errors in these processes.

• 1 - From the clients perspective The savings made means their accounts budget can be redirected towards new growth advisory services.

• 2 - From the accountancy firms perspective, staff hours for routine processes will be significantly cut allowing those hours to be re-allocated to analysing data for higher earning advisory services. Accounting jobs will stay, but change in format.

AI Changes the Traditional Face of Accounting Firms

• 3 - Routines in modern accounting firms will remain as client services. It is the speed and accuracy to which they are produced that will change with accounting AI.

  AI streamlines workflows such as invoice processing, financial reporting, compliance, and audit groundwork, leading to greater efficiency and accuracy.

• 4 - Faster month-end closing experts are predicting AI tools can complete month-end procedures up to 7-working days earlier than current manual accounting software automation.

  Re-training staff in AI can save firms significant time, with some firms reporting up to 7 weeks saved per employee annually.

• 5 - Predictive insight firms will soon be able to use the historical data prepared in monthly and annual accounts to offer additional financial foresight to their clients.

  This will identify future risks and predict future cash flow trends. Future planning for cash flow allows clients to negotiate better terms on borrowing or investment opportunities.

Invoice Processing and Accounts Payable

A business is reliant on a strong cash flow to support operational needs. Cash flow is managed by ensuring customers pay us on time and suppliers are paid when the debt falls due.

AI matches documents such as purchase orders, invoices, and receipts, and automates transaction categorisation to streamline bookkeeping and improve accuracy.

When discrepancies or matches are found, AI captures key details such as vendor names, amounts, and dates to ensure effective automation and accuracy.

It can also detect potential fraud by flagging suspicious transactions. AI identifies unusual patterns, such as duplicate invoices, with up to 98% accuracy.

Transformation of accounts payable

Automating task in accounts payable will transform its operations by reducing manual work hours on mundane processes.

AI can extract the data from invoices, match to corresponding documents and real-time enter it into the accounting system. Discrepancies are identified and complete matches will automatically be passed through for payment approval.

The automation will identify suspicious anomalies such as duplicate invoices to increase fraud detections. AI can detect and predict the correct general ledger coding reducing error in month and year-end financial reporting.

Reconciliation and Month-End Close

AI-powered tools can monitor transactions in real time to detect irregular or fraudulent activity, providing an additional layer of security and risk management.

Reconciliation

Month-end Close

Routine Reporting and Compliance Support

All companies are legally required to produce annual reports for compliance with IFRS and GAAP’s accounting standards. Whilst some routine reporting is for internal use only, any reporting that contributes to the legal reporting must be compliance led.

AI tools can process and summarise large datasets of survey responses to uncover insights and trends for compliance reporting. This makes it easier for organisations to meet regulatory demands.

With AI, the frequency of reporting can be increased and managed more proactively. AI also enhances financial reporting by generating customised reports and visualisations based on large datasets.

Summarisation, document checking, consistency

Regulatory demands grow year on year meaning the AI powered tool is becoming a necessity for most companies.

Typical research reports, that AI automated document checking and routine data entry reduced compliance costs by 40-50%.

General research concludes that AI heightened accuracy and as it operates through recognising patterns, account preparation consistency increased, which naturally met higher levels of compliance.

Summarised, consistent reporting and increased frequency is changing management thinking to a proactive rather than reactive approach.

Client Communications and Faster Responses

AI is fundamentally changing client communications and response times by changing the process from a slow-reactive investigation support to an instant, personalised service that could potentially be available 24/7.

Typically businesses are reporting reducing response times by up to 97%.

AI chatbots or virtual assistants are available for instant access day or night. AI can help accountants improve client communication by summarising conversations and drafting email responses, making interactions more efficient and tailored.

Forecasting, budgeting and decision support

After implementing AI, accountants can leverage advanced tools to manage cash flow by analysing financial data and providing insights into spending patterns, which supports more effective financial planning and risk management.

Forecasting

Budgeting

Decision Making

Benefits of AI in Accounting (What to Measure, not just What to Hope For)

AI has a positive effect on a company’s return on investment (ROI) through improved efficiencies, which in turn drives down costs.

Recent research by an assistant professor of accounting has shown that performance gains from AI integration are most significant for senior accountants, who experience greater improvements in efficiency and accuracy compared to junior staff.

Challenges and Risks (and the Controls that Reduce Them)

With all new automated efficiencies in accounting comes the challenges of increased risk if transparency, human supervision and human intervention isn't present at all times.

Risk: Data quality

AI offers significant risk to the quality, confidentiality and security of the data. AI acts as an accelerator for both good and bad data meaning it can skew the quality amplifying existing problems.

If the quality of the data going in is outdated or poor, the AI system will produce flawed data.

Control:

Maintain clean and accurate data by adopting and implementing strict data governance through a strategy of rigorous data validation at all entry points.

This can be achieved through:

• Defined data quality standards of accuracy - completeness - consistency - timeliness
• Track data provenance and lineage
• Data supervision - assign roles responsible for validating input and cleaning data for AI usage

Risk: Hallucinations/errors

Reducing the risks of hallucinations and errors caused by AI requires a control framework that needs human intervention as well as AI automation.

Controls:

Can be achieved through:

• A human mandatory review process that is implemented to monitor all AI produced results.
• Set up automated validation checks that compares AI output with known and reliable facts.
• Automated notifications for anomalies in unmatched invoices and transactions that are outside of the AI generated pattern.
• Segregation of duties - ensure the person who sets the AI parameters is not the person who authorises the transactions.

Risk: Privacy/confidentiality

Maintaining both privacy and confidentiality requires a multi-level approach to technical security and governance policies.

Redaction procedures should be in place to ensure removal, obscuring or masking of sensitive data.

In addition, regular update training for staff to highlight the importance of the affects of any security breaches

Controls:

Can be achieved through:

• Establishing an AI security policy defining which AI powered tools are approved and which are prohibited.
• Identify clear guidelines on what data can never be entered into the AI system.
• Keep the data entered to a minimum to reduce overall risk exposure to data security.
• Make it mandatory that all financial data that influences decisions or taxation positions is reviewed and approved by a qualified accounting professional.

Risk: No audit trail

To remove the risk of no audit trail a company should move from a manual periodic review system to an automated and continuous system that ensures clarity in the actions or transactions undertaken.

Humans must at all times supervise any automation to ensure validation remains in place.

Controls:

Can be achieved through:

• Create a system that automatically logs every action and AI decision. This includes input and output actions having a time stamp. The logs once recorded must be read only thereafter.
• Ensure AI captures end-to end data to ensure no breaks occur in the audit trail.
• Ensure evidence is embedded in all transaction by AI linking all documentation involved in the automated decision.
• Implement 24/7 monitoring that detects all AI pattern anomalies.

Risk: Adoption resistance

Employees are by nature resistant to change particularly if they feel their jobs are at risk or if they fear the level of training required is above them.

This requires a sensitive and structured change management where staff are kept informed from the outset and at each key milestone.

Controls:

Can be achieved through:

• Transparency in explaining the function of the AI role. Alleviate fears regarding job loses by explaining that AI is meant to augment and not replace human input.
• Create AI accounting champions to bridge the gap between IT and the accounting team.
• Allow staff to take ownership of their role within the AI implementation. Embracing ownership will reduce job fears.
• Redefining accounting career progression to accounting career progression in AI. Demonstrating that AI increases their value and allows them to move into strategic advisory roles.

How to Implement AI in an Accounting Team (A simple 5-Step Plan)

The most effective way to implement AI systems is to take a phased approach that the team will accept.

As part of the rollout, consider how AI can assist in creating standard operating procedures (SOPs) by generating drafts based on existing templates or guidelines, making it easier to document and standardise new processes.

Follow this with introducing user friendly AI tools ensuring ethic and compliances are met at all times.

Action Plan - How to Implement AI in an Accounting Firm

Phase 1: Prepare and strategise AI implementation - ( 1 to 2 months)

• Choose a single high-volume, low judgement workflow process that is time consuming, requires accounts reconciliation and the generation of numerous reports.
• A good example would be accounts receivable customer invoicing.
• Ensure data is in order, cleansed and made ready for input. Set a control checklist to ensure compliance and governance is met.
• If possible plan to run a pilot first to ensure any implementation gremlins are removed before full roll-out.

Phase 2: Speak to the customers involved - ( 1 month)

• Let the customer know they're in the pilot. This will create understanding and a willingness to help.
• Talking to the customer gains feedback not normally seen from a suppliers perspective.
• Ensure change management is effective by speaking to the staff. Give them assurance that their jobs are safe. Where possible, involve them in decisions that have a direct impact on them.
• Set goals so you don't stray from what you are trying to achieve

Phase 3: Pilot Implementation - (4-5 months)

• Choose the right AI tools. Select and integrate appropriate tools for the area of implementation.
• Upskill the team for their new accounting workflow, again this is easier during the pilot phase whilst pressure through volume is removed.
• Establish Ethic and Governance rules. It is essential to cover data protection, bias and accountability early in the process.

Phase 4: Scale - (5-6 months)

• Implement final changes and controls based on customer feedback and experience to date.
• Expand and adopt the AI role across the full accounts receivable process and team.

Phase 5: Scale & Innovate - (6+ months)

• Expand and adopt AI automation across the accounts department and full team.
• Maintain continuous learning as most skill requirements are identified once operational.
• Shift business focus to offer innovative services that are higher-value and strategic advisory by nature.
• Review the impact of AI and collect information and feedback. Explore new AI opportunities.

How Should Accountants Upskill for AI

While AI can automate routine tasks, the human touch remains vital. Accountants bring professional scepticism, ethical decision-making, and the ability to interpret insights from data, which are essential for complex decision-making and maintaining trust.

• By 30 days- Decide and plan how your knowledge and role can shift from manual data processing to understanding, managing and advising on technology-enabled insights.

  Learn about the basic benefits of introducing the AI function into the workplace.

• By 60 days -Undergo in-house training to develop your workflow template for the AI models used.

  Make sure you understand the various AI technologies tools that you will be using.

  Familiarise yourself by gaining hands-on experience.

  Experiment with the different AI tools in your daily workflow.

• By 90 days -Shift your role towards an advisory and strategic role.

  Focus on high-value tasks and develop the skills to offer strategic guidance and scenario planning.

  Use CPD hours to study specialised AI training courses.

AI Tools Accountants Should Know

AI accounting tools are a rapidly growing market with new innovations hitting the market daily.

The following are some of the current AI tools in accounting.

• 1. AI powered accounting and bookkeeping hybrid models. Some of the models assist with audit groundwork by maintaining accurate audit trails.
• 2. Invoice and accounts payable automation tools help automate accounting workflows and can analyse and audit expense reports to improve accuracy, compliance, and uncover spending patterns.
• 3. Generative AI for research and writing tools.
• 4. Tax compliance and audit tools support audit by ensuring compliance and maintaining detailed audit trails.

Conclusion - What the Future Looks Like

As AI continues to evolve and identify patterns, its integration into the accounting profession will only deepen. It will reduce human error for greater efficiency, but it will not replace accountants.

Automation of labour intensive task will improve an accountants work life balance and the shift to high-value strategic advisory roles will increase earning opportunity through more clients.

This means AI accounting needs for high level analytical skills require the right level of human accountant training to embrace the performance gains of AI.

It is expected by 2030 that AI will have revolutionised the industry through continuous, real time financial audits and the elimination of monthly-end procedures.

Agentic AI, that can independently manage multi-step workflows to boost efficiency, is expected to rise and be the dominant AI tool in accountancy.

AI's impact on the accounting profession brings both opportunities—such as increased efficiency, improved quality assurance and new strategic roles—and challenges, including concerns about job security and the need for ongoing upskilling.

What is assured is human expertise will remain in AI supervisory roles. Plus human expertise is always required for strategic advice.

Frequently Asked Questions