The landscape of financial consolidation and accounting has transformed over the past decades. As organizations grow more complex and data volumes expand, the tools and softwares used to manage financial processes have evolved to meet these changing demands.
Key Players
Excel in Accounting
Microsoft Excel has been the backbone of accounting operations for decades. As a flexible spreadsheet tool, it provides:
- Custom formula creation for calculations
- Data organization and manipulation capabilities
- Macro functionality for simple automation
- Familiar interface for finance and accounting professionals
- Compatibility with other systems
However, as organizations grow, Excel's limitations become increasingly apparent. Manual data entry introduces risks and human errors. Version control challenges and limited multi-user collaboration create extreme inefficiencies. Not to mention, scalability constraints and complex maintenance requirements make it difficult to manage accounting operations effectively.
Enterprise Resource Planning (ERP) Systems
ERP systems are comprehensive business management platforms introduced to centralize financial data. Common ERP providers include: NetSuite, Microsoft Dynamics, SAP, Sage Intacct, and many other.
ERP systems offer users:
- Integrated financial management modules
- Built-in accounting operation capabilities - consolidation, close management, etc.
- Cross-department data integration
- Standardized reporting tools
ERP systems often come with challenges, including long implementation timelines of 6-12 months, high costs for setup and maintenance, and complex configuration requirements. Their rigid structures and modules require extensive training and heavy reliance on external consultants, which add additional complexity and expense.
Robotic Process Automation (RPA)
RPA emerged as a solution to automate repetitive tasks in Excel and other applications. It provides:
- Rule-based automation for repetitive tasks
- Scheduled execution of predefined processes
- Integration capabilities across multiple systems (when available)
With the correct setup, RPA tools operate by:
- Following strict programming rules
- Executing tasks in a predefined sequence
- Handling structured data inputs
- Performing repetitive operations consistently
Any changes in data or operations within the predefined process can cause the command chain to break in RPA, leading to high ongoing maintenance costs and technical demands. For growing organizations, each acquired entity, reorganization, team turnover, or process change can disrupt the system, requiring additional setup.
AI Agents in Agentic AI Accounting
AI Agents represent the next evolution in accounting automation.
- Solutions that can turn complex, unstructured data into structured datasets
- Intelligent software platforms that understand and embed accounting concepts
- AI agents that can process natural language instructions (in English)
- Systems that can learn and adapt to existing and new operations
How AI Agents differ from traditional automation:
- Adaptive responses to changing conditions, such as data discrepancies, error detection, and operational changes
- Natural language processing capabilities—able to process commands in English and engage in conversation
- Predictive and analytical capabilities
- The ability to understand business context and execute automated tasks
The Evolution of Accounting Tools
Pure Excel Era (Pre-2000s)
- Manual data entry and formula management
- Prone to human error
- Time-consuming version control
- Limited team collaboration capabilities
- Heavy reliance on individual accountant’s expertise
- Complex macro development needs (coding needed)
The Excel-Based Accounting Process:
- Manual data collection from multiple data sources
- Pre-programmed calculations with macro
- Preset worksheets or templates
- Manual reconciliation and reviews
- Extensive Formula maintenance and version control
- Time-consuming error checking every step of the way
ERP Systems with RPA Integration (2000s-2010s)
Enterprise Resource Planning (ERP) systems were presented as comprehensive business management platforms, with automation capabilities often integrated or offered as complementary solutions. ERP and automation combination aimed to streamline financial processes.
ERP Core Functions:
- Centralized business data management
- Standardized accounting processes
- Built-in financial reporting
- Cross-department integration
RPA (Automation) Expands ERP Capabilities By Providing:
- Automated data extraction and entry
- Scheduled report generation
- Cross-system integration
- Repetitive task automation
Implementation Requirements:
- Extensive system configuration
- Complex mapping processes during and post implementation
- Significant IT infrastructure and specialized staff training
- Detailed workflow documentation
Operational Limitations From Previous Generations of Accounting Tools:
Excel, ERP, and RPA remain powerful players in accounting workflows, but all three systems face significant operational and cost-related challenges. Strict workflows leave little room for flexibility, and any changes to source data require extensive customization. Maintenance is costly and resource-intensive, requiring frequent automation script updates and ongoing monitoring. The high dependency on technical expertise further complicates transitions, especially when key personnel leave. Additionally, integration with other systems is not always possible, particularly with legacy setups, adding further complexity to scaling organizations.
Rigid Structure:
- Predefined workflows must be followed - any break in workflows will result in errors
- Limited flexibility for process or data changes
- Complex customization requirements
Maintenance Challenges:
- Regular automation script updates needed
- System breaks when source data changes
- High dependency on technical expertise
Change Management Issues & High Cost:
- Ongoing and costly system maintenance fees
- Any change in data or formats require additional setup
- Process modifications need reprogramming
- Team turnover impacts system stability
Integration Constraints:
- Not all systems can be integrated
- Legacy systems may be incompatible
- Complex multi-entity scenarios
AI Agent-Powered Platforms (Current)
AI Agents represent a transformative shift from both pure Excel-based processes and RPA-enhanced Excel workflows. With AI agent-powered platforms like Nominal, all data within the general ledger, accounts, and processes are replicated inside the platform, and all data is directly integrated. This enables the system to automatically map the chart of accounts and detect unmapped accounts.
Key Improvements:
- Minimum reliance on underlying Excel architecture
- Intelligent handling of exceptions and changes - adaptive to change in data and operations
- Adaptive learning eliminates script maintenance - no more coding
- Natural language processing (ie, English commands) replaces complex formulas
- Real-time processing versus batch automation
Difference Between Automation vs AI Agents
The combined power of ERP and RPA represents the first-gen of automation in accounting, using software robots to perform repetitive, rule-based tasks. These "bots" follow strictly defined instructions to interact with applications and systems. However, this type of automation requires explicit coding and programming for each process variation. Therefore, any change in upstream data or operations can cause errors in the results.
Most organizations struggle to consistently monitor, update, and create new code to accommodate changes. When errors occur, it can take days, weeks, or even months to investigate and identify the source of the data discrepancy - not to mention the high costs associated with external consultants or internal tech support.
ERP + RPA excels at executing predefined tasks, and AI Agents represent a new shift in automation capability.
- Natural Language Processing: RPA needs coded instructions while AI Agents can understand and execute tasks described in plain English
- Adaptive Learning: AI Agents adapt into existing operations while create improvements
- Contextual Understanding: AI-powered platforms can handle variations and exceptions without requiring reprogramming
- End-to-End Process Understanding: AI Agents already embrace and comprehend the context of financial operations.
The shift from Excel-based processes to AI Agents represents more than just an upgrade in technology—it’s a fundamental transformation in how accounting operation is performed. While excel, rule-based automation, and traditional ERP solutions remain essential in the market, platforms that leverage AI Agents offer a more flexible, intelligent, and efficient approach to managing complex financial processes. The ability to process logic and execute tasks in English makes AI Agents the next evolution in accounting automation.
.png)
.png)