%20(1).png){kind=logo}
Real-world applications across audit, tax, advisory, and financial reporting
Colleen Knuff, CPA-CGA, CITP
Brent Pruim, Director of Innovation & Change Management, Rehmann
accountingaiplaybook.com
2025
AI has become an important tool across core areas of the accounting profession. From audit to advisory, firms are using AI to automate low-value tasks, uncover insights, and enhance the quality of work. While the applications vary by discipline, the result is the same: faster workflows, smarter analysis, and more time for judgment and client service.
Unlike other chapters in this Playbook, we are not focusing on barriers and best practices here. Instead, we are taking a different approach: giving you a clear and practical look at how AI is already being used in the most popular fields of accounting. This chapter highlights the real-world use cases and tools making a tangible impact today, helping you identify exactly where AI can add value to your work.
Traditional risk scoping often relies on small samples and professional judgment, which can miss hidden risks. AI tools like MindBridge analyze 100 percent of journal entries, assigning risk scores and flagging anomalies across an entire dataset. This allows auditors to focus testing on the highest-risk areas right from the start.
Platforms like this identify unusual transactions using machine learning and pattern recognition. Round-dollar entries, weekend postings, and entries that bypass standard approvals are all flagged for review. The AI surfaces patterns that would be difficult or impossible to detect manually, giving firms broader and more defensible audit coverage.
By automating this process, auditors can prioritize where to dig deeper and allocate time more effectively. Firms using AI for risk assessment often report fewer missed issues, stronger documentation, and a more efficient audit approach that adapts to the actual risks in the data.
.png)
Auditors have long relied on limited sampling due to time and resource constraints. With AI, tools like Fieldguide allow firms to analyze entire ledgers and run audit procedures across full populations of transactions. This means testing is no longer based on a random subset but on actual risk indicators found in the data
AI can suggest which transactions to sample, generate audit test plans, and even summarize testing results. Tools like DataSnipper and CCH TeamMate Document Linker use computer vision to automate the vouching process by extracting supporting details from documents and linking them directly to workpapers, cutting hours of manual work.
Full-population analysis gives auditors a clearer picture of financial activity and allows them to tailor their procedures more precisely. Instead of spending time selecting and testing random samples, audit teams can focus on transactions that truly matter.
Audit documentation often requires reviewing large volumes of source materials, which can slow down engagements. Tools like DataSnipper and Fieldguide use natural language processing to extract key data from documents like contracts, invoices, and confirmations. The AI then auto-fills workpapers with this information, significantly reducing manual input.
These tools also organize and format audit evidence, linking each figure back to its source and creating a clean audit trail. This streamlines the reviewer's job and improves the consistency of documentation across engagements.
Instead of spending time on formatting and file management, auditors can focus on analyzing results and resolving issues. Workpaper automation turns documentation from a bottleneck into a strength, helping teams maintain quality without burning hours on clerical tasks.
Drafting financial statement disclosures requires both technical accuracy and consistency with regulatory language. Tools like Tellen's FootNoteAI help automate the first draft of disclosures by using trial balance data and referencing a large database of historical footnotes.
The AI generates language tailored to the client's financials and the relevant reporting framework. This gives firms a strong starting point that can be quickly reviewed and finalized. The result is more consistent language across clients and reduced risk of missing required disclosures.
By removing the blank-page problem, firms can produce disclosures faster and with fewer errors. This saves time during busy season and helps ensure financial statements meet both firm standards and compliance requirements.
.png)
Tax research is notoriously time-consuming, requiring deep dives into the IRC, Treasury regulations, IRS guidance, and court rulings. AI-powered platforms like blueJ, Checkpoint Edge, and CCH AnswerConnect are changing that by allowing practitioners to ask tax questions in plain English and receive instant, sourced answers.
These tools leverage natural language processing and vast legal databases to pull relevant authorities in seconds. Rather than sifting through PDFs, a tax pro can ask, "Is this deduction allowed under §162?" and get an answer with proper citations. This streamlines the research process and helps practitioners validate their position with greater speed and confidence.
Beyond just finding answers, these tools assist in drafting memos or position papers by generating clear explanations and suggested language. For firms juggling deadlines and complexity, AI Q&A tools eliminate bottlenecks and reduce research time from hours to minutes — without sacrificing accuracy.
Planning for optimal tax outcomes often requires evaluating complex "what if" scenarios, from entity structure changes to timing strategies and deductions. Tools like blueJ use predictive modeling to forecast how tax authorities might rule on a particular issue, giving firms a clearer picture of risks and likely outcomes.
These AI tools simulate the logic used in prior rulings and court decisions, producing probability scores based on similar historical cases. This helps practitioners tailor advice to client needs while managing compliance risks. Instead of guessing how an issue will be treated, tax professionals can cite AI-backed probabilities and precedent.
Scenario modeling tools also help visualize the tax impact of different strategies. AI enables firms to rapidly calculate the effects of various deductions, structures, or transaction timings, delivering data-driven recommendations with confidence and speed.
One of the most tedious and error-prone tasks in tax is entering data from client documents into software. AI tools like AutoEntry and Filed.com automate this process by extracting data from scanned forms like W-2s, 1099s, and receipts, then auto-populating tax return fields.
These platforms learn from prior classifications and improve accuracy over time. They reduce manual keying errors, speed up reconciliation, and free up staff for more meaningful review work. For high-volume or deadline-driven firms, this automation can drastically cut prep time.
The result is not just faster returns. It also means cleaner data, fewer errors, and more bandwidth for client-facing work. As AI tools continue to improve, they are moving closer to generating first-draft returns, leaving preparers to review rather than build from scratch.
Tax compliance requires continuous oversight, especially in high-volume areas like sales and use tax. AI tools now provide real-time monitoring by comparing filings to historical data, industry norms, and client-specific patterns to spot anomalies before returns are submitted.
If something looks off, such as a dramatic dip in sales tax for a high-revenue month, the system flags it for review. These alerts allow firms to correct errors or investigate potential fraud before they become audit risks.
By automating this layer of oversight, firms reduce exposure, improve filing accuracy, and protect clients from regulatory surprises. For firms handling thousands of line items per return, AI acts as a safeguard that runs continuously.
Forecasting is essential to client advisory services. Traditionally, building models requires hours of manual spreadsheet work. Tools like Jirav and Cube now use AI to generate projections based on historical data, allowing firms to bypass many of the repetitive tasks involved in financial modeling.
These tools analyze past performance, detect seasonal patterns, and generate forward-looking scenarios with minimal setup. Advisors can adjust assumptions and instantly see the impact on revenue, cash flow, and margins. This real-time responsiveness allows firms to create multiple "what if" forecasts during a single client meeting.
By reducing the need for manual data entry and formula building, AI empowers firms to scale their advisory services. It also improves accuracy by factoring in more data than a typical spreadsheet model, helping clients make faster, more informed decisions.
Clients rely on their advisors to interpret financial data and provide clear guidance. AI-enabled platforms like Chata.ai and Power BI with Copilot let advisors query financial data in plain language and receive narrative explanations or visual summaries.
Instead of writing formulas or running reports manually, advisors can ask simple questions like, "Which product had the highest margin last quarter?" and receive a clear answer or chart. This makes data easier to access and improves engagement during meetings, especially with non-financial stakeholders. Instead of taking notes and following up with answers later, advisors can respond to client's follow-up questions on the spot, exploring new angles and uncovering insights in real time. By reducing the need to revisit spreadsheets after the meeting, these tools allow advisors to be more responsive and strategic in the moment.
AI can also surface trends and anomalies that may not be obvious. Advisors can spend less time pulling numbers and more time helping clients understand what the data means and what actions to take next.
Advisory work often requires delivering client-ready reports. AI-powered tools like Spotlight Reporting and Clockwork AI can create draft financial reports, dashboards, and summaries using client data pulled directly from accounting systems.
These platforms generate visuals and written commentary, highlighting performance metrics, trends, and KPIs. Instead of spending hours building decks or drafting commentary, advisors start with a polished draft that can be quickly customized and reviewed. Tools like Gamma can also take reports produced by other applications and turn them into visually stimulating presentations that add finesse to your client deliverables with only a few minutes of your time.
This shift reduces manual workload and supports consistency across engagements. Advisors can focus on insights and strategy, not formatting or copywriting, which helps firms deliver higher value to more clients with less time.
Preparing financial statements is a time-consuming task that often requires extensive formatting and mapping from the trial balance. AI tools like Fieldguide can now automate much of this work by pulling in trial balance data and generating draft financial statements with firm-standard templates.
These tools group accounts, apply formatting rules, and create comparative statements automatically. Paired with disclosure drafting tools like Tellen's FootNoteAI, firms can generate both numbers and notes in a fraction of the time it used to take. The AI references thousands of compliant examples to produce consistent and accurate output. Tellen's Consistency Check AI flags mismatches between footnotes and core financials as well as taking care of cross-reference validations.
Accountants can then review and finalize these drafts, focusing on interpretation and completeness rather than mechanics. This speeds up the close and reduces errors tied to manual entry or formatting.
Month-end and year-end close processes often stall because of manual reconciliations. Platforms like BlackLine and Trintech automate this process by matching transactions and flagging only those that require human review.
AI helps identify recurring patterns, suggests journal entries, and auto-certifies low-risk accounts. When firms implement these tools, they typically shorten their close cycle, freeing up time for analysis and review.
By removing the bottlenecks of spreadsheet-based workflows, AI-powered reconciliation tools create a smoother, more predictable close process. This means faster financial reporting and greater confidence in the numbers.
Maintaining internal controls and preventing fraud is a constant challenge in financial reporting. AI platforms like MindBridge and SMACC monitor transactions continuously and flag anomalies that deviate from expected patterns.
These tools detect issues such as unusual posting times, duplicate transactions, or entries that fall outside approval thresholds. Because the AI reviews all transactions, not just samples, firms gain broader coverage and faster issue detection.
Embedding this type of monitoring into everyday workflows strengthens control environments and reduces the risk of financial misstatements. It also supports documentation and audit readiness. Combining both AI capabilities and agentic workflows, it is possible that within a few years firms will be actively involved in activities like continuous monitoring for advisory services and continuous auditing for audit services.
Use this checklist to identify tasks in your firm that can be streamlined or improved with AI. Each item represents a practical opportunity to reduce manual effort, improve accuracy, or free up time for higher-value work.
Extract data from scanned documents
Use AI tools to pull key data from invoices, receipts, tax forms, and bank statements automatically.
Auto-populate accounting and tax software
Let AI feed extracted trial balance and general ledger data directly into your audit or tax platform to eliminate manual input.
Categorize transactions
Use AI to classify income and expenses based on historical patterns, improving bookkeeping speed and consistency.
.png)
Automate bank reconciliations
Match transactions across bank statements and ledgers automatically, flagging only unmatched items.
Suggest recurring journal entries
Let AI identify and propose entries like depreciation, accruals, or prepaid adjustments based on past activity.
Track close checklist progress
Use workflow AI to monitor which month-end tasks are complete, late, or at risk.
Track close checklist progress
Use workflow AI to monitor which month-end tasks are complete, late, or at risk.
.png)
Analyze full ledger data for anomalies
Replace sampling with 100 percent analysis to surface outliers and unusual transactions.
Select audit samples intelligently
Let AI flag the riskiest transactions for testing instead of relying on random sampling.
Verify supporting documents automatically
Use AI to link figures in workpapers to invoices, contracts, or bank statements with one click.
Auto-fill tax returns from source documents
Pull data from W-2s, 1099s, and other forms directly into tax software.
Research tax questions with natural language
Ask tax questions in plain English and get AI-generated responses with citations.
Model tax planning scenarios
Use AI to simulate different filing positions or structure changes and predict likely outcomes.
Generate cash flow forecasts
Use historical data to project future performance automatically.
Create "what if" financial scenarios
Instantly adjust assumptions like revenue growth or cost margins and see the financial impact.
Produce KPI dashboards
Build visual dashboards with AI-generated charts and performance summaries.
Draft management reports or executive summaries
Turn financial data into readable commentary for clients or leadership.
Write footnotes for financial statements
Use AI to generate first drafts of disclosures based on the trial balance and reporting standards.
Summarize long documents
Condense contracts, SOC reports, or internal memos into bullet-point takeaways.
Respond to common client or staff questions
Set up AI assistants to answer FAQs, draft emails, or pull data on request.
Schedule meetings or coordinate tasks
Use AI tools to automate calendar management and team reminders.
Transcribe and summarize meetings
Record calls or internal discussions and get auto-generated notes and action items.
Not all AI projects are created equal. Use this matrix to evaluate potential AI use cases based on two simple criteria:
Use the categories below to prioritize what to tackle first.
Quick Wins — Start Here
These projects deliver strong resultswith minimal technical lift. Ideal starting points to build momentum andinternal buy-in.
Strategic Projects — Plan Carefully
These projects require cross-team coordination, data readiness, or vendor integration. Worth pursuing, but success depends on thoughtful planning and rollout.
Low-Hanging Fruit — Do If Time Allows
These tools are easy to test and require little change management, but may have limited ROI. Use them to support staff productivity, not core processes.
Avoid or Defer — Not Worth It Now
These projects tend to consume time and resources without a clear return. Revisit only if tied to larger strategic changes or future efficiency goals.
This chapter showcases how AI is already transforming core areas of accounting, from audits and tax to advisory and financial reporting. Instead of focusing on barriers or abstract potential, it highlights specific, real-world use cases where AI is delivering measurable value. Readers will see how tools like MindBridge, Blue J Tax, DataSnipper, and Jirav are being used to automate risk assessments, streamline tax research, generate forecasts, accelerate close processes, and more. The chapter includes practical examples, actionable checklists, and a prioritization matrix to help firms identify which AI opportunities are worth pursuing now. Whether you're optimizing audits or expanding client advisory services, this chapter helps you pinpoint exactly where AI can enhance your workflows.
