Introduction
It’s a paradox of modern business: Executives expect real-time answers, yet finance teams remain bogged down in spreadsheets. To keep pace, FP&A must embrace AI-driven reporting. A KPMG study shows the shift is already underway; 72% of companies are piloting or using AI in financial reporting, a figure expected to reach nearly 99% within three years.
A good AI financial reporting tool is more than just making pretty charts; it helps spot problems before they hit your dashboard, explains what’s driving variances without you having to dig through spreadsheets, and gives executives the insights they need to make decisions.
The financial reporting solutions reviewed here incorporate advanced AI capabilities, including machine learning (ML) algorithms and natural language processing (NLP), to streamline report generation, analysis, and distribution processes. These tools will enable finance teams to move beyond traditional reporting methods and help create more dynamic, responsive financial insights that can enable them to adapt to changing business conditions.
Each platform offers unique AI-powered approaches to modernize reporting workflows and improve accuracy in financial planning.
Best AI financial reporting tools in 2025 at a glance
- Drivetrain: AI-native platform with conversational insights, automated model creation, anomaly detection, and natural-language data transformation for mid-market to enterprise businesses.
- Pigment: Enterprise planning platform with AI agents for next-step recommendations, formula writing, and trend detection with narrated insights.
- Anaplan: Enterprise planning solution with ML forecasting, conversational AI assistant, and scenario optimization capabilities.
- Mosaic: SMB to mid-market platform offering automated insights with natural language prompts and automated variance analysis.
- Planful: Mid-market financial planning platform with ensemble forecasting, anomaly detection, and conversational AI for natural-language insights.
- Cube: SMB to mid-market, spreadsheet-native tool with conversational agents, automated variance analysis, and smart forecasting capabilities.
- Workday Adaptive Planning: Enterprise planning tool with AI forecasting, scenario modeling, and conversational planning assistant integrated with the Workday ecosystem.
- Datarails: Excel-based platform for small to mid-sized businesses with conversational chat, automated insights, and narrative storyboard features.
- Vena: Mid-market, Excel-native platform with a conversational AI assistant, automated report generation, and built-in financial analysis capabilities.
- Jedox: Mid-market to enterprise solution with prebuilt planning scenario templates and NLP for data exploration.
- Prophix: Mid-market platform that automatically generates visual data summaries and leverages AI algorithms for financial projections.
| Tool | Best for | Key AI capabilities |
|---|---|---|
| Drivetrain | Mid-market to enterprise businesses | • AI Analyst (conversational interface to surface insights) • AI model generator for automated financial model creation • AI Anomaly detection across revenue, spend, and headcount • AI Transforms (natural-language data transformation) • AI BvA (write board-level commentary explaining key variances) |
| Anaplan | Enterprise businesses | • PlanIQ (ML forecasting engine) • CoPlanner (conversational AI assistant) • Predictive Insights • Optimizer for scenario optimization |
| Pigment | Enterprise businesses | • Planner Agent (next-step recommendations) • Modeler Agent (formula writing, model optimization) • Analyst Agent (trend detection, narrated insights) |
| Mosaic | SMB to Mid-market businesses | • Automated Insights with NLP prompts • Automated BvA analysis |
| Planful | Mid-market businesses | • Planful Projections Forecasting Engine (ensemble modeling) • Planful Signals for anomaly detection • Conversational AI interface for natural-language insights |
| Cube | SMB to Mid-market businesses | • Conversational agents to answer questions • Automated analysis to spot key variances • Smart forecasting • Intelligent mapping of data |
| Workday Adaptive Planning | Enterprise businesses | • AI forecasting and scenario modeling • AI-driven planning assistant (conversational interface) • Anomaly detection for revenue and expenses |
| Datarails | SMB to Mid-market businesses (spreadsheet-native) | • Chat (conversational assistant) • Insights (automated reports) • Storyboards (narrative presentations) |
| Vena | Mid-market businesses (spreadsheet-native) | • Conversational AI assistant for Excel and Teams • Automated report generation from simple prompts • Built-in financial analysis to flag trends and anomalies • Learns from user input to improve personalization |
| Jedox | Mid-market to enterprise businesses | • NLP to explore complex datasets and answer questions about the product • Prebuilt templates for various planning scenarios |
| Prophix | Mid-market businesses | • Automatically generate summaries of visual data representations • Leverage historical data and AI algorithms to project future financial outcomes • NLP based conversational AI assistant |
Drivetrain
Drivetrain, an AI-native platform, stands out as our top pick for AI-powered financial reporting tools. The platform’s Drive AI suite automates report generation, detects anomalies before they become problems, and provides conversational analytics that let you ask questions about your data in plain English. With 800+ integrations, Drivetrain connects multiple systems to provide the data foundation for real-time reporting that AI requires, automatically generating comprehensive financial reports that adapt to changing business conditions. This makes it ideal for companies that need both speed and accuracy in their financial reporting processes.
AI Transforms: FP&A requires a lot of data from various systems, each of which has its own format and syntax. Finance teams spend a lot of time first combining and then transforming multiple data sets before they can even begin to use them. Integrating your systems with Drivetrain creates the automation necessary to bring the data from each system into the platform. Then, Drive AI’s Transforms feature automatically transforms each data set, making it ready for use in analysis and reporting within seconds.
AI Model Generator: Drive AI’s Model Generation tool can build baseline models using data from different business systems to automatically generate all the required metrics for the model. In addition, Drive AI leverages advanced AI algorithms to enhance predictive modeling in Drivetrain for cash flow forecasting as well as other types of forecasting to support financial reporting.
AI Analyst: The AI analyst leverages powerful NLP models to make it even easier to engage with your data in Drivetrain anywhere on the platform using natural language prompts. AI Analyst is especially useful for ad hoc reporting. While Drivetrain makes it easy to drill down into the data for deep insights, when your CEO asks for some revenue numbers on the fly, you can simply ask the AI Analyst, and in an instant, you have a detailed revenue graph ready to deliver. In a fast-paced business environment, it’s easy to see the benefit of getting fast, accurate answers when you need them.
AI Alerts: Drive AI also extends Drivetrain’s automated alerts system with AI Alerts, which provide automated anomaly detection for the data flowing into the platform from different source systems. In addition to the automated alerts that a metric has exceeded a defined threshold, AI Alerts allow users to quickly determine whether those exceedances are real or caused by a problem with the source data, before incorporating that information into reports. Users are also instantly notified when there’s a problem with the flow of data from their source systems.
AI BvA: This agent helps quickly identify the reasons behind variances and explains that in board-level commentary. Instead of spending hours digging through data to understand why actuals missed budget, the AI Analyst surfaces the key drivers automatically and provides clear, executive-ready explanations that can go straight into board presentations or management reports.
.gif)
Anaplan Intelligence is a suite of AI-powered tools that includes CoPlanner, Predictive Insights, and PlanIQ. It also includes a tool called Optimizer. While not a true AI feature, it is a mathematical optimization technique that, when combined with AI, can be useful for scenario planning and analysis.
CoPlanner: CoPlanner is an AI feature that leverages an LLM to provide a chatbot within Anaplan. It allows users to ask questions in a conversational way to explore their data and receive responses based on the context of the data and models being queried. One of the key benefits of CoPlanner for financial reporting is that users can query multiple models simultaneously.
Optimizer: The Optimizer tool helps organizations make strategic budget allocation decisions. Finance teams can set specific budgetary goals (such as reducing departmental spending or optimizing resource allocation) while accounting for various business constraints. The system then suggests optimal budget distributions based on these parameters.
Predictive Insights and PlanIQ: Anaplan’s Predictive Insights is another AI-powered tool. This one uses ML to identify trends in large data sets compiled from all the business systems users have connected to the platform and applies advanced analytics to more accurately predict outcomes. Similarly, PlanIQ employs ML techniques to generate predictions based on historical data and various business drivers. One of the benefits of PlanIQ is that, as a no-code application, it’s accessible to users without specialized technical expertise.
Pigment’s AI transforms financial reporting by combining intelligent automation with user-friendly interfaces. The platform’s three specialized agents, Analyst, Planner, and Modeler, handle everything from generating insights and creating forecasts to maintaining model accuracy, while intuitive search and visualization features let finance teams create reports and analyze data quickly, regardless of their technical background.
Planner agent: Planner transforms insights into forecast-aware recommendations. Automates report-ready forecast updates, enabling real-time planning adjustments.
Analyst agent: Pigment’s Analyst acts as a proactive co-pilot for reporting and analysis. It uncovers trends and detects anomalies in internal and external data sets and presents insights in dashboards and slide decks.
Modeler agent: The Modeler automatically builds and updates underlying models used in reporting to ensure data accuracy, detect formula inefficiencies, and streamline workflows.
Arc AI by Mosaic includes an integrated chat feature that lets users query their financial data and request specific insights using everyday language, making complex data analysis as simple as having a conversation with the platform.
Automated insights: Like other AI-chat-enabled solutions, ArcAI uses NLP to interpret queries and provide accurate responses. This makes it easier for finance teams to more quickly access the information they need and for non-finance users to get answers to their questions without requiring deep technical knowledge of the system.
Automated report generation: Arc AI also streamlines report creation by allowing users to ask for the insights and data they want to include to enhance the value of their financial reports. The AI then gathers the relevant data from various sources and analyzes it to produce customized reports based on user preferences.
Planful’s AI enhances reporting through automated insights, tailored recommendations, and proactive issue detection. The Analyst Assistant allows users to query data in plain English, while AI Signals automatically identify potential problems before they impact results. The AI Help assistant simplifies report navigation and discovery, collectively streamlining reporting workflows and enabling finance teams to spend more time on strategic analysis rather than manual report creation.
Signals: Planful’s Signals feature automatically scans reports and applies anomaly detection to identify outliers, unusual trends, and errors, such as broken formulas or unexpected variances. It also generates explainable alerts with risk categorization and customizable sensitivity thresholds, ensuring accuracy and audit readiness.
Projections: The platform’s Projections feature speeds up reporting by auto-generating ML-based forecasts and seeding reports with accurate baselines. It applies guardrails to remove bias, highlights key variances for quicker analysis, and reduces manual input, helping finance teams build reports faster, improve accuracy, and focus on insight-driven decision-making.
Help Assistant: Users can ask the in-app, chat-based assistant questions in plain English and get answers quickly.
Workday Adaptive Planning uses AI and ML to streamline reporting workflows for finance teams. The platform combines automated processes, forecasting capabilities, and clear explanations of data trends to accelerate reporting cycles and deliver consistent, understandable insights that support better business decisions.
Intelligent planning: This feature compares user-generated reports with AI-driven predictions, highlighting anomalies or deviations from expected results. This ensures reports remain accurate and consistent with historical benchmarks, improving reliability and enabling proactive adjustments.
Assistant: Workday’s Assistant is a conversational AI tool that integrates with Slack and Microsoft Teams. It lets users query financial results, generate reports, and surface insights using natural language, simplifying collaboration and making reporting accessible to non-finance stakeholders.
Anomaly detection: The platform’s anomaly detection capabilities leverage ML to scan reports for inconsistencies or outliers in reported data. This helps to ensure financial integrity, reduces reporting errors, and helps FP&A teams maintain stakeholder confidence with accurate, validated results.
Cube has incorporated AI features such as conversational interfaces, automatic variance detection, and intelligent baseline forecasting to simplify financial reporting. The platform consolidates data from various sources, automates report production, and improves clarity by providing easy-to-understand AI-generated explanations of financial trends and changes.
Conversational agents: Integrated with Slack and Microsoft Teams, Cube’s conversational AI allows users to query reported data in natural language. For example: “What were the expenses for marketing in Q1 2025?” or “How did revenue compare to our last plan?”
Automated analysis: Instantly identifies key variances in reports and provides contextual explanations. This helps FP&A teams quickly understand the ‘why’ behind reported results without combing through spreadsheets.
Smart forecasting: AI generates baselines that can be fed into reports, ensuring consistency and accuracy when comparing actuals against expectations. This accelerates report generation and makes narratives more meaningful.
Datarails Genius improves financial reporting by merging AI-powered analytics with Excel’s familiar interface. The platform automates data gathering from multiple sources, creates reports with detailed explanations, and delivers customized insights that help finance teams convert raw data into meaningful, decision-ready reports.
Insights: The insights feature in Datarails delivers AI-generated summaries and visualizations directly within reports. Teams can configure exactly what metrics appear, when they’re delivered, and who receives them, ensuring stakeholders get timely, relevant insights.
Storyboards: This feature converts dashboards and results into ready-to-present narratives. Reports can be turned into polished presentations with AI-generated commentary, streamlining communication and consistency across reporting cycles.
Chats: A natural language chatbot enables conversational interaction with reports. FP&A teams can ask questions like “What caused the variance in operating expenses last month?” and get instant, data-driven explanations from a single source of truth.
Vena
Vena Copilot is an AI reporting assistant that uses intelligent automation to handle variance analysis, create customized reports, and deliver up-to-date insights. The tool helps finance teams produce accurate, compelling reports more quickly while improving collaboration throughout the organization.
Analytics agent: This feature in Vena’s Copilot analyzes reported data, identifies trends, and explains variances. It provides narrative context around report results, making it easier to understand performance drivers and highlight key insights for stakeholders.
Reporting agent: The reporting agent transforms natural-language prompts into fully formatted reports in Excel. This reduces manual reporting work, enabling finance teams to quickly generate, customize, and share reports that are consistent and audit-ready.
Jedox
Jedox incorporates AI features into its reporting platform to help FP&A teams automate insight generation, simplify dashboard creation, and minimize manual report building. These AI capabilities enhance report accuracy and flexibility while making complex financial data more accessible and easier to understand for finance teams.
AIssisted™ Planning Wizards: This feature provides guided setup for reporting scenarios through different wizards that help generate prebuilt report structures with upper and lower benchmarks. This helps ensure that reports are meaningful and aligned with business goals.
JedoxAI: JedoxAI uses natural language to interact with reporting data. Finance professionals can ask questions like “Which were our top-performing regions last quarter?” and receive immediate, clear answers in their reports.
AI Search: A built-in assistant for report creation, AI Search guides users step-by-step in building dashboards, generating reports, and managing data integrations, thereby reducing reporting complexity and empowering self-service.
Prophix
Prophix One Intelligence transforms reporting by using AI to automatically generate insights, identify patterns, and enhance narrative explanations. The platform converts traditional financial reports into interactive, story-driven communication tools that help stakeholders understand data faster and make informed decisions.
Prophix Copilot: Conversational AI enables users to generate and query reports in plain language. It explains results, variances, and trends directly within reports, making insights accessible to both finance and non-finance teams.
Predictive forecasting: With this capability, users can quickly generate forward-looking baselines that can be directly embedded into reports. This ensures reports are not just backward-looking but include predictive context for better decisions.
Chart insights: Charts and report visuals can be translated into plain-language narratives automatically. Using AI to explain variances and trends in simple terms improves clarity and ensures stakeholders can act on the insights quickly.
.webp){kind=avatar}
A week of work done in minutes.
Report better with Drivetrain.
Features to look for in an AI financial reporting tool
It shouldn’t come as a surprise that not all AI reporting tools are created equal, and the hype around AI can make it tempting to choose based on flashy demos rather than practical capabilities. The best tool is one that fundamentally improves how your team creates, analyzes, and shares financial insights.
A strong AI reporting platform should accelerate report creation while maintaining accuracy, enable seamless collaboration across departments, and provide executives with clear, actionable insights that drive better business decisions. Here are the essential features that separate truly effective AI reporting tools from the rest.
Native integrations
Inconsistent numbers across departments create confusion and undermine trust in financial reporting. When different teams pull data from various systems manually, version conflicts become inevitable. Native integrations solve this by ensuring all reports pull from the same governed dataset, eliminating the ‘which number is right?’ conversations that plague finance teams.
The best AI financial reporting tools connect directly to your ERP, CRM, HRIS, and other core business systems without requiring complex middleware or custom APIs. This gives stakeholders confidence that they’re working with consistent, accurate information across the organization.
Conversational assistants and natural language queries
Stakeholders are constantly bombarding finance teams with repetitive data requests that pull analysts away from strategic work. Conversational assistants and natural language queries transform this exact dynamic by allowing business users to ask questions like “What was Q2 ARR growth in EMEA?” and get instant answers without involving the FP&A team.
This feature eliminates ad-hoc reporting bottlenecks that often consume hours of analyst time each week. Instead of building custom reports for every stakeholder request, finance teams can focus on high-value analysis while business users get the specific insights they need through simple, everyday language queries that the AI can interpret and respond to automatically.
AI-powered anomaly detection and variance analysis
Identifying anomalies or risks manually is reactive and time-consuming, and often results in problems being discovered after they’ve impacted financial results. AI-powered anomaly detection automatically highlights unusual trends or outliers as they occur, helping finance teams spot risks early and provide proactive insights to leadership.
A system with AI-powered anomaly detection continuously monitors financial data across all metrics, flagging deviations from expected patterns before they become major issues. Instead of waiting for month-end reviews to uncover problems, finance teams receive real-time alerts about unusual variances, enabling them to investigate root causes immediately and take corrective action while there's still time to minimize business impact.
Role-based access for collaboration
Customizing reports and sharing them across teams is often inefficient and creates security risks when access to sensitive financial data isn’t properly controlled. Role-based access solves this by allowing finance teams to grant appropriate permissions for different stakeholders at a granular level, based on their role and responsibilities.
This feature improves collaboration while maintaining data integrity by ensuring executives see high-level summaries, department heads can access their relevant metrics, and analysts are able to work with detailed datasets, all within the same system. Instead of creating multiple report versions or worrying about who has access to what information, teams can collaborate seamlessly while keeping sensitive financial data protected.
Enterprise-grade security
Financial data is sensitive and needs strong controls to protect against breaches and ensure regulatory compliance. Enterprise-grade security features protect reports with role-based access controls, encryption, and comprehensive audit trails that track who accessed what information and when.
This level of security is essential for board and investor reporting, where data integrity and confidentiality are critical. Advanced security measures include single sign-on integration, multi-factor authentication, and compliance certifications that meet industry standards. With these measures in place, finance teams can confidently share reports across the organization and with external stakeholders, knowing that sensitive information remains protected while still enabling the collaboration necessary for effective financial reporting and decision-making.
Explainable AI
Executives sometimes struggle when trying to understand complex financial data, especially when AI-generated insights lack clear explanations of how conclusions were reached. Explainable AI translates financial metrics into plain-English insights, providing clear narratives that improve clarity and storytelling in financial reports. It also builds trust in AI-driven recommendations by showing the reasoning behind each insight, rather than presenting black-box results that executives can’t validate.
Explainable AI allows finance teams to confidently present AI-generated analyses to leadership in a way that ensures that stakeholders can understand not only what happened, but why it happened and what factors contributed to the results.
Drivetrain vs. the field
For mid-market and enterprise companies, Drivetrain consistently stands out as the most comprehensive AI-native financial reporting platform. While many solutions have added AI capabilities over time, Drivetrain was built from the ground up with an architecture designed for AI.
This foundational approach ensures seamless integration between AI features and reporting workflows, delivering cohesive automation rather than disconnected tools that require manual coordination between different functions.
Get all your data in with 800+ integrations
Drivetrain recognizes that reliable reporting depends on quality data from across your business systems. The platform provides over 800 native integrations spanning ERP, HRIS, billing, and CRM platforms, going beyond simple connectivity to intelligently map data from different sources into a unified reporting model.
The AI learns your data structures and automatically handles custom fields, making integrations more intelligent over time. This eliminates the typical data consolidation headaches that plague finance teams, no more manual reconciliation between systems or scrambling to merge spreadsheets before important meetings. Instead, your team works from a single, trusted dataset that updates automatically as information flows in from connected systems.
Advanced AI capabilities
Drivetrain’s AI supports FP&A teams throughout the entire budgeting and reporting process with intelligent automation at each step. The platform detects data anomalies before they appear as variances in reports, allowing teams to address issues proactively rather than reactively.
Users can transform complex datasets using simple natural language prompts, eliminating hours of manual data manipulation. The AI generates baseline financial models in seconds rather than days, while also creating complete reports from scratch, including budget-versus-actual commentary and strategic insights. This comprehensive AI support means finance teams spend less time on repetitive tasks and more time providing strategic guidance to leadership and stakeholders.
Cross-function reporting, made simple
Drivetrain balances finance team oversight with organization-wide accessibility through role-based customization and granular permission controls. Users receive personalized views appropriate to their responsibilities while maintaining data security for sensitive financial information.
Department leaders can independently input forecasts, access relevant dashboards, and generate reports without requiring finance team intervention for routine tasks. Integrated workflows and commentary features maintain transparency and keep collaborative planning processes organized. The platform’s conversational assistant provides immediate answers to stakeholder questions, reducing bottlenecks and enabling seamless collaboration across departments, while preserving the finance team’s strategic focus and data governance responsibilities.
Built for security, compliance, and transparency
Drivetrain maintains enterprise-grade security with SOC 1 Type II, SOC 2 Type II, ISO, and GDPR certifications, ensuring your financial data meets the highest compliance standards. The platform provides data masking capabilities and dimensional-level access controls that protect sensitive information while enabling appropriate visibility across roles.
Transparency is built into every AI interaction; all responses include source references so users can trace insights back to original data. Users can validate AI-generated calculations and recommendations, building trust in automated analysis. This combination of robust security infrastructure and transparent, explainable AI gives finance teams confidence that their reporting processes meet both regulatory requirements and internal governance standards.
FAQs
Traditional BI software focuses on data aggregation and manual analysis, showing what happened through dashboards and reports. AI reporting tools go further by automatically generating insights, explanations, and predictions without manual intervention.
AI reporting tools replace manual effort with automation, complex queries with natural language interaction, and provide proactive anomaly detection and predictive analytics to forecast future outcomes in a fraction of the time forecasting normally takes. AI tools also integrate directly into collaboration platforms like Slack and Teams, making insights accessible to non-technical users.
Essentially, BI reports the past while AI reporting explains it, predicts the future, and delivers insights in real-time.
The top AI software platforms for enterprise financial reporting include Drivetrain, Pigment, Anaplan, Workday Adaptive Planning, and Jedox. These solutions excel at handling the scale and complexity that large organizations require.
These platforms distinguish themselves through their ability to manage massive data volumes, complex organizational structures, and multi-entity reporting requirements. They provide enterprise-grade security controls, regulatory compliance features, and robust governance frameworks essential for protecting sensitive financial information. Additionally, they offer advanced capabilities like predictive analytics, sophisticated scenario modeling, and AI-driven forecasting that enable large organizations to optimize their reporting processes and support strategic decision-making across multiple business units and geographic regions.
Yes, AI reporting tools continuously monitor financial data to automatically identify errors, anomalies, and inconsistencies before they appear in final reports. These systems use machine learning algorithms to establish what normal patterns look like and flag deviations in real-time.
AI can also detect data quality issues like missing entries, unusual spikes, or values that fall outside expected ranges. It can identify inconsistencies across different data sources and flag potential reconciliation problems.
The proactive approach made possible by AI helps finance teams catch and correct issues early, maintaining data integrity and preventing embarrassing discoveries during board meetings or stakeholder presentations.
Integrations with existing financial systems enhance AI reporting tools by ensuring seamless data flow from platforms like ERP, CRM, and HRIS. This eliminates manual data entry and reduces errors while providing AI algorithms with real-time, accurate information for analysis.
By consolidating financial data across multiple systems, integrations create a comprehensive view that improves forecasting accuracy and decision-making capabilities. They also ensure AI tools work with familiar financial models and existing workflows, making adoption easier for finance teams while enabling more effective, data-driven reporting processes that leverage the full breadth of organizational data.
Drivetrain’s Drive AI suite offers comprehensive automation across the entire financial reporting process. Key capabilities include AI Analyst for conversational insights and variance explanations, AI Model Generator that creates complete financial models automatically, AI Anomaly Detection that monitors live data for unusual patterns, and AI Transforms for natural-language data manipulation.
The platform also features AI BvA that generates board-level commentary explaining key variances automatically. These capabilities work together seamlessly, enabling finance teams to move from manual report building to strategic analysis while maintaining accuracy and providing clear explanations for all AI-generated insights.
Related AI Reporting Modeling tool guides
We have even more information on AI financial reporting-related software and tools. Check them out.
.svg)
