In the mid-1990s, business process reengineering (BPR) became a popular method for improving organizational workflows. The aim was to deconstruct fundamental processes, identify inefficiencies, and rebuild systems to enhance reliability, speed, and quality. Many will remember the days of boardroom walls covered in brown paper and sticky notes.
Today, we have technological advantages that make process improvement faster, easier, and more effective than BPR pioneers could have imagined. Two of the most impactful innovations are robotic process automation (RPA) and artificial intelligence (AI).
Robotic Process Automation (RPA) and Intelligent Automation (IA)
RPA originated in the automated testing world, using software “bots” to manage everything from routine, repetitive tasks to complex business functions. Properly implemented, RPA delivers speed – robots can work 10 – 15 times faster than humans-and offers a high degree of reliability and auditability.
RPA can streamline tax processes like submitting validated materials, collecting and inputting data, and downloading reports. Any tax preparation task that is repetitive and consistent is a candidate for automation. Yet, human oversight remains essential for ensuring quality and reliability.
Effective automation decreases manual effort, increases capacity in labor-constrained environments, and enables employees to focus on higher-value, knowledge-based work. The ultimate goal: move people beyond “data entry” to more impactful analytical roles.
RPA’s true value emerges when combined with AI, forming intelligent automation (IA). IA leverages the structured data gathered by RPA and adds AI’s reasoning power, dramatically boosting productivity.
Artificial Intelligence in Tax Functions
AI excels with access to large datasets, quickly analyzing and identifying complex associations. When automation feeds AI a constant flow of data, organizations can expect fewer manual data entry tasks and more actionable insights.
Well-supported AI can:
- Corroborate or validate siloed data
- Analyze historical performance
- Model tax strategies
- Generate step-by-step instructions for new finance practices
- Create reports and analysis from datasets
By supporting analytical efforts, AI helps organizations explore tax opportunities, validate strategies, evaluate performance, and more. The result is more robust tax analysis, increased time for strategic decisions, and greater operational efficiency.
However, to realize AI’s full potential, automation (whether RPA or another data transfer method) is necessary for ongoing data integration. While AI capabilities are advancing rapidly, successful enterprise adoption requires careful planning, steady process improvement, and ongoing refinement. Waiting until tax season to incorporate change increases the pressure these technologies are designed to alleviate.
Process Improvement in Tax: A Prime Opportunity
Tax is especially well-suited for process improvement through RPA and AI. The function features high task repetition, clear process flow, a need for sophisticated scenario analysis, and complex regulations spanning multiple jurisdictions. Beyond shortening tax preparation timelines or improving accuracy, automation and AI offer creative applications before, during, and after tax season – potentially transforming the entire tax function.
For example, AI-enabled systems can automatically classify expenses and flag unusual transactions, greatly reducing the hours spent reconciling accounts ahead of tax season. Automation tools can gather and pre-validate client tax documents, minimizing the back-and-forth with clients and improving the completeness and accuracy of filings. During tax season, intelligent assistants can proactively alert teams to regulatory changes that impact specific filings, helping to ensure compliance across various jurisdictions. After tax season, machine learning models can help organizations analyze outcomes and identify new opportunities for tax credits or risk mitigation in future cycles.
By thoughtfully incorporating automation and AI, organizations can spend tax season focusing on quality analysis and strategic guidance, rather than manual data entry. These tools reduce repetitive work, free up employee time, and position tax departments for better outcomes – making tax season less stressful, more insightful, and ultimately more valuable for both professionals and clients.
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