AI and Accounting: How Will It Change the Industry?

With the ability to automate repetitive tasks and enhance data analysis capabilities, artificial intelligence (AI) is being adopted by accountants for the purposes of performing accurate financial planning for their clients. 

Here, we’ll look at how AI in accounting is improving the industry, and how it will continue to impact financial processes in the future. 

What is AI in accounting?

Artificial intelligence (AI) uses machines to simulate human intelligence, performing tasks that typically require human input like problem solving and decision making. In accounting, AI systems can analyse large data sets, recognise patterns, and make informed predictions that enhance efficiency and accuracy for businesses.

Intuit is at the forefront of accounting and AI, with over 730 million AI-driven customer interactions per year, leading to 58 billion machine learning predictions each day. Intuit has even built its own Generative AI Operating System (GenOS), which leverages custom-trained financial large language models specialising in tax, accounting, cash flow, and more.

Examples of AI in accounting and finance

Using AI for finance and accounting offers an array of advantages that are already changing the execution and management of financial procedures for the better.

In the tax, accounting, and audit industry, AI is already making a noticeable impact. Evidence of this can be found in the 2025 Generative AI in Professional Services Report, which was conducted by the Thomson Reuters Institute. This report showed that in 2023, just over half (52%) of professionals at tax firms thought AI should be applied to tax tasks. Fast forward a year, and that figure has jumped nearly 20 points to 71%. The shift is even stronger inside corporate tax departments, where three out of four professionals (75%) now believe AI has a place in their daily work.

The table below summarises the ways you can use accounting AI to transform your business:

Let’s now take a closer look at how accounting AI can streamline administrative tasks, enhance accuracy, and save time:

Automation of routine tasks

Traditionally, accountants have spent considerable time on repetitive tasks such as data entry, transaction categorisation, and invoice processing. These tasks are essential but can be time-consuming and prone to errors. These processes don’t necessarily require accountants' unique skills and expertise. This is where AI can step in to help ease the burden.

What might have taken hours for a human accountant can now be completed in a fraction of the time, freeing up professionals to focus on more value-added tasks.

Enhanced data analysis

By harnessing the power of AI-driven tools, accountants can now process large amounts of data at unprecedented speeds. This empowers them to analyse datasets and extract insights efficiently.

One of the strengths of AI algorithms lies in their ability to identify patterns and trends within data. This proficiency empowers accountants to unearth insights from financial datasets that may have otherwise remained hidden through conventional analysis.

Improved fraud detection

AI in finance and accounting has the potential to improve how we identify, prevent, and address fraudulent activities within financial processes.

AI algorithms are incredibly effective in recognising patterns and outliers across datasets. This plays a role in detecting any financial transactions or behaviours that might indicate fraud is occurring.

Thanks to AI-enabled fraud detection systems, financial transactions can now be monitored quickly. This allows for the identification of any fraudulent activities as they happen.

By identifying changes in regular transaction behaviours, AI can promptly notify accountants about potential fraud at an early stage. This proactive approach helps prevent losses from escalating.

Personalised financial advice

Accountants and financial professionals can leverage AI-driven algorithms and data analysis to provide recommendations and insights catering to individuals' and businesses' financial circumstances and goals.

By analysing volumes of data, including income, expenses, investments and market trends, AI enables a data-driven approach to offer customised advice. This technology considers an individual's or business's financial goals, risk tolerance levels and preferences to provide advice that aligns with their objectives.

AI can evaluate risk profiles and market trends to suggest investment strategies that offer returns while considering an individual's appetite for risk.

Benefits and drawbacks

AI in accounting also comes with some limitations that businesses should consider. In the table below, we’ve offset some of the key benefits against potential drawbacks:

Benefits of AI in accounting

The advantages of AI in accounting are multitudinous—which is why this technology has largely been embraced by the finance industry. Here, we’ll take an in-depth look at its key benefits together with industry-relevant examples:

Improved efficiency and time savings

AI can handle time-consuming accounting tasks such as data entry, invoice matching, and bank reconciliations in a fraction of the time it would take manually. By automating these processes, businesses free up valuable time to focus on higher-value activities like strategy, growth, and client relationships.

Example in practice:

A small business using AI-powered accounting software can automatically categorise expenses from bank feeds and generate draft reports. Instead of spending hours manually sorting transactions each week, the business owner can review the AI’s work in minutes and redirect their time towards managing operations and customers.

Error reduction in data-heavy tasks

Accounting often involves processing large volumes of numbers, receipts, and transactions—making it easy for manual mistakes to slip through. AI reduces this risk by consistently applying rules, cross-checking data, and flagging anomalies that might otherwise go unnoticed. This leads to cleaner records and more reliable financial reporting.

Example in practice:

When reconciling thousands of monthly transactions, AI tools can automatically match payments to invoices with high accuracy. Instead of a staff member accidentally duplicating or misallocating a payment, the AI highlights discrepancies and ensures data is recorded correctly the first time.

Scalable insights for advisory work

AI doesn’t just process numbers—it can analyse financial data at scale and identify patterns, trends, and opportunities that would take much longer to uncover manually. This gives accountants and business owners the ability to provide more strategic advice without significantly increasing workload.

Example in practice:

An accountant using AI-driven forecasting tools can quickly generate cash flow projections for multiple clients. Instead of manually crunching data for each business, the AI provides instant insights into future trends, allowing the accountant to spend more time advising clients on growth strategies and risk management.

Competitive advantage for early adopters

Businesses that embrace AI in accounting early can position themselves ahead of competitors. By streamlining operations, delivering faster reporting, and offering deeper insights, they not only improve their own efficiency but can also deliver greater value to clients and stakeholders. Over time, this can set them apart in a crowded market.

Example in practice:

A mid-sized accounting firm that integrates AI into its workflows can provide clients with real-time dashboards and proactive financial advice. While competitors may still be focused on manual reporting, this firm can attract and retain more clients by offering smarter and more forward-looking services.

Drawbacks of AI in accounting

While AI offers many advantages, it’s important to also recognise the potential challenges and limitations that come with adopting this technology. In this section, we’ll provide more detail about some of the possible downsides. 

Data security and privacy concerns

AI in accounting relies on handling large volumes of sensitive financial data. While this enables powerful automation and insights, it also raises concerns about data security and privacy. Businesses must ensure that their AI tools comply with strict data protection standards to avoid breaches or unauthorised access.

Example in practice:

If a bookkeeping firm uses accounting AI software that stores client financial information in the cloud, a cyberattack or weak security protocol could expose confidential records. This risk means firms need to choose reputable providers with strong encryption and compliance measures in place.

Over reliance on incorrect outputs

AI is powerful, but it’s not infallible. If the system is fed incomplete or inaccurate data, the outputs can be misleading. Relying solely on AI without human oversight can result in flawed financial reporting or poor decision-making, as the technology may not always account for unusual transactions or context-specific nuances.

Example in practice:

A business owner might rely on AI-generated cash flow forecasts to make investment decisions. If the system misclassifies certain irregular expenses, the forecast could paint an overly optimistic picture, leading the owner to overspend or take on unnecessary financial risk.

Lack of context in generative tools

Generative AI can produce useful summaries, reports, or even draft communications, but it may lack the deeper business context that a human accountant or advisor brings. Without understanding industry-specific nuances, client relationships, or unique circumstances, the outputs might be technically correct but practically unhelpful or even misleading.

Example in practice:

An accountant using a generative AI tool to draft a client email about tax deductions might receive a well-written message. However, if the AI overlooks that the client works in a specialised industry with unique deduction rules, the advice could be incomplete or inaccurate—potentially causing compliance issues.

Costs of implementation and change management

Adopting AI in accounting often requires significant investment in new software, staff training, and workflow adjustments. Beyond financial costs, there can also be resistance to change, with employees needing time to adapt to new systems. For some small and medium-sized businesses, these hurdles may slow down adoption.

Example in practice:

A growing accounting firm decides to implement an AI-powered platform for client reporting. While the software itself is effective, the firm spends additional months and resources on staff training, data migration, and updating internal processes. During this transition period, productivity temporarily drops before the long-term benefits are realised.

4 useful AI tools for accountants and bookkeepers

There are several AI tools that accountants and bookkeepers can leverage. The table below compares the four most useful tools:

Will AI replace accountants?

While accounting and finance AI is transforming the industry, it is best viewed as a tool to augment human work rather than replace it. Accountants and bookkeepers bring critical judgment, context, and strategic thinking that AI cannot replicate.

The World Economic Forum Future of Jobs Report 2025 states: “Globally, the expected reduction in the proportion of work tasks performed by humans is driven primarily by increased automation. Of the nearly 15 percentage point reduction in the proportion of total work tasks delivered by humans in 2030 versus 2025, nearly 82% is attributable to advancing automation, while 19% is projected to derive from expanded human-machine collaboration.”

This highlights that while AI will take over repetitive and data-heavy tasks, it will also enable accountants to focus on higher-value activities such as advisory services, strategy, and client relationships—strengthening their role rather than eliminating it.

What is the future AI impact on accounting? 

AI is expected to bring about changes to the accounting field. It could transform how accounting processes are carried out, how financial data is analysed, and how accountants provide value to their clients and organisations.

Jared Brintz, Senior Marketing Manager at Intuit QuickBooks, sees AI as something that can support professional development:

As for the future of accounting and AI, it’s expected that AI systems will handle tasks that require cognitive abilities. For instance, natural language processing (NLP) will enable accountants to effectively use AI systems to understand documents, contracts, and regulatory texts. This advancement in NLP will allow accountants to interact with AI systems using language. It will make it easier for them to access information, generate reports, and ask questions.

As a result of these advancements, the role of accountants will evolve. They will focus more on decision making, interpreting insights generated by AI systems, and providing expert oversight to ensure data accuracy and ethical considerations are upheld.

QuickBooks Online is an Intuit software that uses AI to help automate repetitive tasks for accountants and advisors. These tasks can include data entry, invoice processing, and even financial reporting.

Unlock the power of AI with Intuit's AI accounting software

Intuit is leading the way with artificial intelligence and accounting, integrating cutting-edge technology into its software. Now is the time to leverage the potential of AI for your accounting requirements.

Imagine a world where tasks like entering data, categorising transactions, and processing invoices are automated, giving you time to focus on decision making. Intuit's AI-powered solutions aim to streamline these tasks, reduce errors and enhance efficiency.

That's not all. With AI, your ability to analyse data will reach new heights. AI algorithms can uncover hidden patterns, identify trends, and provide insights that could help your planning. Thanks to the power of AI-generated insights, making informed decisions will be easier than before.

Sign up for Quickbooks Online today and unlock the power of AI technology for your accounting processes.