Using AI to Streamline Financial Problem Solving

I just watched 80 AI agents work simultaneously on a single spreadsheet. Each pulling different data points. Revenue figures from SEC filings.  Credit ratings from Moody's.  Current ratios from balance sheets. All happening in parallel while I grabbed coffee. Normally, this would mean opening endless browser tabs, hunting through investor relations pages, copying numbers into spreadsheets. Instead, I used AI agents to automate this entire research. Then, used Gemini in Sheets to analyze the data. Here's the real insight: Working with spreadsheets is still complete slop. We've had ChatGPT for 3 years, yet most financial analysis still happens the old way.  You ask an AI a question, get a text response, then manually structure it yourself. That doesn't make sense for research like this. Some workflows need spreadsheet agents, not chat interfaces. So, I used this agentic spreadsheet tool, Ottogrid. Here's what I did: Created a table with 10 companies. Added columns for the financial metrics I needed. Instead of researching each cell manually, I selected the entire range and hit "Run cells." Ottogrid turned every empty cell into an AI agent: ↳ Agent 1: Find Apple's FY2024 revenue ↳ Agent 2: Get Apple's credit rating ↳ Agent 3: Calculate Apple's current ratio ↳ Agent 80: Find Intel's total debt All running simultaneously. All finding exactly what I specified. 2 minutes later: Complete financial analysis ready. Then I moved everything to Google Sheets and used Gemini to create Financial Health Scores and identify red flags across all companies. All without writing or even trying to remember a single spreadsheet formula. This isn't for massive datasets.  But if you can automate one routine research task that eats 2-3 hours of your day, the ROI is obvious. The professionals using AI agents for research definitely have an unfair advantage over those still doing everything manually. If you find this useful, Repost 🔁 to share it with your friends. I share practical AI implementations for finance professionals. To get started: 📩 Subscribe to Unwind AI for AI news, tools, and tutorials: https://lnkd.in/dunsQXDS ⭐️ Star the repo for opensource AI finance agents: https://lnkd.in/db2UynaZ ✅ Follow me for more such AI tools, news, workflows, and insights.

Everyone loves talking about AI but few really understand how to apply it to FP&A effectively. Automating tasks here and there won’t cut it anymore. Actually, releasing AI features won't either. The real value comes from integrating AI into core financial workflows to help finance teams make smarter, faster decisions. That’s why at Abacum, we’ve taken an AI-native approach from Day 1 that solves real challenges FP&A teams face today: → Handle robust data across all business departments → Become the hub for data-driven decisions across the organization → Enhance modeling capacity with AI and machine learning → Democratize financial insights to make them accessible to every stakeholder In 2024, we achieved this by introducing: 1. AI Summaries: Automatic performance insights to empower data-driven decision-making. 2. AI Forecasting: Create business forecasts in seconds using historical data—covering revenue, cost projections, and headcount plans. 3. AI Classification: Automate data categorization, reducing manual work and allowing easy validation. 4. AI Anomaly Detection: Monitor data and surface edge cases in real time, ensuring no deviation goes unflagged. But we’re not stopping there. We’re doubling down on our AI-native approach. In Q1'25, you will see: 🚀 AI Syntax: Intelligent formula completion that makes modeling easy.  🚀 AI Scenarios: Auto-pilot forecasting, where AI handles all inputs, actuals refresh automatically, and you can compare versions seamlessly. 🚀 AI Workflows: End-to-end orchestration of business-critical company workflow. And this is just the beginning - we have a lot more in the works. Stay tuned. The future is about empowering FP&A teams to focus on strategy, make smarter decisions, and lead their organizations with confidence. Where else do you see AI making a big impact in FP&A?

🧾 The Quiet Revolution in Finance: How AI Is Transforming Back-Office Workflows When people talk about AI, the spotlight often lands on flashy front-end tools—chatbots, content generators, customer service automation. But behind the scenes, in the quiet corridors of finance departments, a powerful transformation is underway. 🔄 Welcome to the age of AI-powered back-office finance. 📌 What's Actually Changing? Let’s break down some of them. ✅ 1. Invoice Processing: From Manual Chaos to Machine Precision For years, accounts payable teams have been buried under stacks of invoices—scanning, verifying, and entering data manually. It’s tedious, error-prone, and slow. But now? AI-driven tools can extract line items, match invoices with purchase orders, detect anomalies, and even route them for approval—all within seconds. This doesn't just reduce processing time by up to 80%. It also slashes errors, late payments, and friction between departments. ✅ 2. Expense Reporting: Streamlined, Automated, and Policy-Friendly Let’s be honest—expense reporting has long been one of the most hated admin tasks for employees and finance teams alike. Now, AI can: Auto-scan receipts Flag policy violations in real-time Pre-fill reports based on past patterns or travel bookings Generate complete reports without employee intervention This means finance teams spend less time chasing down receipts and more time analyzing spend trends. ✅ 3. Compliance Tracking: Constantly On, Always Up-to-Date Regulations aren’t getting any simpler. But AI is stepping in to do what spreadsheets and static checklists never could. AI tools now: Monitor financial activities in real-time Compare transactions against regulatory requirements Send alerts for discrepancies or audit risks This shift from reactive to proactive compliance not only reduces regulatory risk but can also save millions in potential penalties. ⚡ Why This Matters More Than Ever Finance teams are under pressure to: Do more with less Move faster Deliver strategic insights, not just reports And while digital transformation has touched many areas of business, back-office finance has often lagged behind—until now. AI is giving finance professionals something they rarely had before: Time. Time to analyze, plan, and lead. Instead of drowning in repetitive tasks, they can now focus on: Strategic forecasting Budget optimization Business partnering 🎯 Is This Replacing Jobs? No—It’s Redefining Them. Let’s be clear: AI in finance isn’t here to replace your team. It’s here to augment them—freeing them from grunt work and empowering them with intelligent systems that support better decisions. This is what real digital transformation looks like: Quiet, efficient, and revolutionary. 💬 Have you seen this shift in your finance team yet? Or are you still stuck in the paper-pushing days? #FinanceAutomation #AIinFinance #BackOfficeRevolution #WorkflowAutomation #DigitalTransformation

Really happy I had the opportunity to train around 100 of our #finance leaders at Kraft Heinz on how to use #AI for Finance! It was a fantastic opportunity to showcase how Generative AI can transform the way we work — from automation to analysis. We had representatives from functions like FP&A, supply chain finance, internal audit, tax, controllership and more! Some of the key topics we covered: ✅ Prompt engineering techniques ✅ Why context is everything when working with LLMs ✅ Practical tips like generating Python code for finance automation and deeper financial insights I truly believe AI can be a game-changer for Finance. Our function is uniquely positioned to champion this technology and lead its adoption across the organization. The potential benefits? 1) Faster analysis – Spend less time crunching numbers and more time interpreting them. AI accelerates data processing and helps surface key trends in seconds. 2) Smarter automation – Automate repetitive, manual tasks like reconciliations, reporting, and forecasting so teams can focus on strategic work. 3) Sharper insights – Use AI to dig deeper into financial data, spot anomalies, and uncover insights that might otherwise be missed. 4) Better decision-making – With real-time insights and predictive capabilities, Finance can help drive smarter, faster business decisions. 5) Increased efficiency – Free up valuable time and resources by integrating AI tools directly into daily workflows. Can’t wait to see how my colleagues continue to explore and innovate with these powerful technology!

Harvard Business Review just found that executives using GenAI for stock forecasts made less accurate predictions. The study found that:  • Executives consulting ChatGPT raised their stock price estimates by ~$5.  • Those who discussed with peers lowered their estimates by ~$2.  • Both groups were too optimistic overall, but the AI group performed worse. Why? Because GenAI encourages overconfidence. Executives trusted its confident tone and detail-rich analysis, even though it lacked real-time context or intuition. In contrast, peer discussions injected caution and a healthy fear of being wrong. AI is a powerful resource. It can process massive amounts of data in seconds, spot patterns we’d otherwise miss, and automate manual workflows – freeing up finance teams to focus on strategic work. I don’t think the problem is AI. It’s how we use it. As finance leaders, it’s on us to ensure ourselves, and our teams, use it responsibly. When I was a finance leader, I always asked for the financial model alongside the board slides. It was important to dig in and review the work, understand key drivers and assumptions before sending the slides to the board. My advice is the same for finance leaders integrating AI into their day-to-day: lead with transparency and accountability. 𝟭/ 𝗔𝗜 𝘀𝗵𝗼𝘂𝗹𝗱 𝗯𝗲 𝗮 𝘀𝘂𝗽𝗲𝗿𝗽𝗼𝘄𝗲𝗿, 𝗻𝗼𝘁 𝗮𝗻 𝗼𝗿𝗮𝗰𝗹𝗲. AI should help you organize your thoughts and analyze data, not replace your reasoning. Ask it why it predicts what it does – and how it might be wrong. 𝟮/ 𝗖𝗼𝗺𝗯𝗶𝗻𝗲 𝗔𝗜 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝘄𝗶𝘁𝗵 𝗵𝘂𝗺𝗮𝗻 𝗱𝗶𝘀𝗰𝘂𝘀𝘀𝗶𝗼𝗻. AI is fast and thorough. Peers bring critical thinking, lived experience, and institutional knowledge. Use both to avoid blindspots. 𝟯/ 𝗧𝗿𝘂𝘀𝘁, 𝗯𝘂𝘁 𝘃𝗲𝗿𝗶𝗳𝘆. Treat AI like a member of your team. Have it create a first draft, but always check its work, add your own conclusions, and never delegate final judgment. 𝟰/ 𝗥𝗲𝘃𝗲𝗿𝘀𝗲 𝗿𝗼𝗹𝗲𝘀 - 𝘂𝘀𝗲 𝗶𝘁 𝘁𝗼 𝗰𝗵𝗲𝗰𝗸 𝘆𝗼𝘂𝗿 𝘄𝗼𝗿𝗸. Use AI for what it does best: challenging assumptions, spotting patterns, and stress-testing your own conclusions – not dictating them. We provide extensive AI within Campfire – for automations and reporting, and in our conversational interface, Ember. But we believe that AI should amplify human judgment, not override it. That’s why in everything we build, you can see the underlying data and logic behind AI outputs. Trust comes from transparency, and from knowing final judgment always rests with you. How are you integrating AI into your finance workflows? Where has it helped vs where has it fallen short? Would love to hear in the comments 👇

Thinking about applying AI within your finance function? Heres three high-return areas to consider: ⚙ Automating Financial Close: AI can accelerate month-end and year-end closing by automating data extraction, reconciliation, and anomaly detection. This can halve closing timelines and reduce manual workloads by up to 70%, allowing teams to focus on strategic analysis rather than repetitive tasks. 📈 Enhancing Forecast Accuracy: Predictive AI models use historical and external data to provide more precise scenario analyses. They improve over time, boosting forecast accuracy by up to 60% and supporting faster, data-driven decisions 💡 Generating Strategic Insights: AI can analyse large volumes of structured and unstructured data, from social media to IoT sources, to reveal hidden risks and opportunities, aiding strategic planning Providers like BlackLine, Anaplan 'IBM Watson' deliver these solutions. However, beware - lots of AI features are rebranded versions of old tech. Automated reconciliations and advanced analytics, for example, are now marketed as “AI-powered” despite existing for years. True AI brings adaptive, real-time learning capabilities, so it’s crucial to assess whether solutions offer genuine innovation or just marketing hype What AI strategies have worked for your team? Please share your thoughts!

Today we released a complete guide to the best AI tools for finance teams A growing trend of modern finance teams are implementing AI native tools to improve the efficiency of their teams and work -- leading to better results, faster growth, and better operations But most of time the question I get asked is: "How can I get started using AI for my work" Some finance professionals have already tried using generic AI tools and seen performance issues combined with an inability to automate real processes. Others just don't quite yet know where to start. This guide will help. To create this guide we gathered data from our conversations with 100s of finance leaders who are using AI today in their finance teams and grouped them according to workflows they help automate -- specifically * AI FP&A Tools * AI FP&A tools enable strategic finance leaders to choose more automation without losing flexibility when reporting and analyzing financial data through AI. We highlight Concourse as the leading AI FP&A tool * AI Accounting Tools * AI accounting tools are helping reduce reconciliation work through automating the close process to reduce human errors and free up time for more strategic tasks. We highlight Numeric, Truewind, and Rillet as leading tools * AI Accounts Receivable Tools * AI AR tools analyze customer payment history to predict potential delinquencies and prioritize collection efforts in addition to helping teams track and invoice contract terms seamlessly. We highlight Maxio, Sequence, and JustPaid as leading tools * AI Accounts Payable Tools * AI AP tools are changing how businesses manage their invoices and payment flows through the automation of manual tasks like receipt capture, policy enforcement, and rich payment controls. We highlight Brex, Ramp, and Jeeves as leading tools * AI Treasury Tools * AI treasury tools leverage LLMs to analyze market liquidity trends, predict cash flow, and optimize financial management to help treasury teams stay on top of liquidity and capital needs. We highlight Nilus, and Finley as leading tools Full guide in the comments with use cases, customers, funding and more for every tool we highlight I hope this guide is a great starting point for finance teams who are looking to modernize their stack and tools that have native AI capabilities Happy to personally help make introductions to any of the companies listed in the guide as they have all built amazing products and companies If automating reporting and analysis of financial data with AI agents is top of mind please reach out to me or Concourse and we would love to give you a demo. All feedback is welcomed!

The finance department, often deemed as one of the more mundane areas, is undergoing a remarkable transformation with the advent of AI technology. While initially met with skepticism, AI has now become a pivotal force in revolutionizing financial processes. AI-driven solutions are revolutionizing the field by enhancing speed, precision, and strategic insights. Here are some compelling real-world applications: - **Automated Reconciliation & Close**: Previously, tasks like reconciling transactions were laborious. Now, AI engines streamline this process by automatically matching transactions from the ERP, reducing manual effort significantly. Deloitte's research indicates that AI-driven reconciliation can slash manual processing by up to 80%, leading to substantial cost savings for large enterprises. - **Intelligent Invoice Processing and OCR**: Handling a high volume of invoices manually is daunting for many businesses. AI-powered OCR tools now facilitate swift and accurate invoice processing, enabling real-time expense categorization and cross-verification with purchase orders. Organizations leveraging AI-enabled OCR reportedly process invoices 2.4 times faster and at a 60% lower cost, as per APQC. - **Smart Vendor & Customer Management**: AI aids in managing suppliers and customers efficiently. By automating tasks like matching supplier invoices to internal records and predicting late payments for accounts receivable, AI enhances operational efficiency. Research by Gartner reveals that automated AR collections can reduce Days Sales Outstanding (DSO) by 10-20%, optimizing working capital utilization. The integration of AI in finance is reshaping traditional practices, offering unprecedented opportunities for improvement and innovation. It's truly a transformative era for the financial landscape! #AI #FinanceTransformation NAKAD Sambhav Jain Avinash Uttav Chinmaya Gawde Bikash Ranjan Mishra Akash Kejriwal Arun Yadav Raman S.

Enterprise AI spend is surging, with adoption among large businesses nearly doubling in the past year. We can all feel it. Finance, however, is moving cautiously. Per survey date, only 9% of finance professionals report actively using GenAI today, and 8% are only in the early stages of adoption. This tracks with the conversations I have, but it drives me nuts because Finance & Accounting is perfect positioned. Our data is highly structured, 99% of all transactions are repetitive, & Accounting is governed by US GAAP & the tax code, providing applicable guidance as context. So lets talk about how some Finance leaders are using AI today: - Hex uses an AI assistant to write SQL and Python for reporting, giving operators instant insights without relying on data teams. - Sierra leverages an AI agent to pull bills from Ramp and analyze budget variances in seconds. - Notion and Quora automate most expense approvals with Ramp AI agents, cutting hours of manual review. - Poshmark applies AI-powered OCR in Ramp to pay bills more efficiently and reduce errors. - Snapdocs saves time on compliance workflows with AI-powered record-keeping. Obviously, its not about using AI for AI’s sake. But there are real problems that AI can solve for. Let's keep sharing & learning from each other. Read the full report here: https://lnkd.in/eG36rCb6

Finance teams are using AI automation to lead, not chase. Here's how to cut 30% of manual work with smart prompts. Smart finance teams are already slashing hours of manual effort with AI Agents + Purposeful Prompting. Repetitive reporting, reconciliations, or digging through data takes up a lot of time. That’s where AI steps in—automating routine tasks, reducing human error, and delivering insights in seconds, not days. Here’s what finance teams are getting with AI promts: → 30% less manual work across reporting, planning, and analysis → Fewer errors from copy-paste fatigue and spreadsheet overload → Instant summaries, variance explanations, and cash flow insights   → Faster decision cycles for FP&A, audits, and strategic pivots But the key to AI success is not just using AI—it’s knowing how to prompt it right. The best teams tailor Generic chat tools don’t cut it. Start by asking: - What’s draining the most time each month? - Where are accuracy or consistency issues costing us? - Which insights are always late or incomplete? Then bring in AI Agents trained, domain-specific, secure, and able to speak your business language. Caution: Not every AI solution is plug-and-play. Poorly designed prompts waste more time than they save. And security is a non-negotiable. Choose solutions built for finance-grade data protection. If you're leading a finance team and not already using AI Agents + strategic prompting, you’re loosing time, insights, and a competitive edge. Here are 7 examples of basic AI prompts for finance teams. _______________ Please share your thoughts in the comments. Follow me, Beverly Davisfor more finance insights. #Finance #Efficiency #FinanceTransformation #AI #AIAgents #PromptEngineering #FinanceLeadership #FinTech #OperationalExcellence #FinancialOperations #FinanceAutomation