Session 10 of the Future of Finance Lab tackles one of finance’s most persistent myths — Why AI Will Create More Excel, Not Less — And What That Means for Finance Professionals
In Session 10 of the Future of Finance Lab, host Lance Rubin welcomed Khaled Chowdhury — Certified Management Accountant, former FP&A Director, former Chief Data Officer, and now CEO of a data consulting firm — to challenge the idea that Excel is dying. What followed was a frank, practitioner-led conversation about how AI, Microsoft Fabric, Power BI, and Claude are reshaping the daily reality of finance work — not by replacing existing tools, but by changing what we do with them.
Fortnightly Nugget
You can test Microsoft Fabric’s Copilot capabilities for the cost of a cup of coffee. The smallest Fabric capacity (F2) at approximately $262/month includes Copilot — but with pay-as-you-go pricing, you can turn capacity on and off by the second. That means a few hours of testing costs cents, not hundreds. For finance professionals who’ve been priced out of experimenting with Fabric and AI agents, this changes the calculation entirely.
Excel Isn’t Going Anywhere — It’s Getting a Promotion
Khaled opened with a confession and a correction. His own career pivot away from finance was driven by what he called “Excel hell” — the grind of budgeting in spreadsheets that led him to Power BI, then to a Chief Data Officer role, and ultimately into consulting. But his position today is unequivocal: AI is going to create more Excel, not less.
The reasoning is practical. When you run actual-versus-budget analysis, when you need to send a deliverable to a client, when you need a human to review and adjust numbers — it lands in Excel. What changes is how that Excel file gets built. Khaled described uploading an Excel file and a contract definition into Claude, asking for an over/under analysis with detail and summary tabs. Ninety seconds later, Claude returned a formatted, formula-linked workbook that would have taken him significantly longer to build manually — and he has over a decade of Excel experience.
That single experience caused him to switch from a US$200/month ChatGPT Pro subscription to Claude. His reasoning was telling: he can teach his team to prompt effectively far faster than he can transfer a decade of spreadsheet muscle memory. The tool democratises Excel competence while rewarding those who understand what the output should look like.
The Power BI Semantic Model as an AI Foundation
The session’s most technical insight centred on why Power BI — specifically its semantic model layer — is emerging as the ideal foundation for enterprise AI agents in finance.
Traditional RAG (Retrieval-Augmented Generation) approaches require organisations to vectorise database schemas, add column descriptions, and build context layers so that AI can accurately query data. Khaled pointed out that Power BI semantic models already contain most of this infrastructure: relationships are built in, column and measure descriptions exist natively (and have since Power BI Desktop five years ago), and the in-memory columnar engine delivers the speed that production AI agents require.
On top of that, Power BI’s row-level security solves a problem that sinks many RAG deployments: ensuring that a department head only sees their own data. Without that, you cannot take an AI agent into production. Power BI handles it natively.
Microsoft has layered additional AI readiness through the “prep data for AI” feature in Power BI Desktop, which allows builders to clean schemas and add natural-language instructions directly into the model. These instructions function like onboarding notes for a new analyst — if someone asks “what is my sales?”, don’t return lifetime figures; return this year, exclude intercompany, and tell the user what assumptions were applied.
The result is what Khaled described as production-ready data agents: AI interfaces that sit on top of verified Power BI semantic models, respect security, and can answer questions that would previously have required a new report build.
Fewer Reports, More Agent Ownership
This shift redefines the role of finance professionals. Today, the bottleneck is report creation — there are only so many dashboards a team can build and maintain. Data agents remove that bottleneck by allowing users to ask questions directly. But someone still needs to own the semantic model, maintain the definitions, control audit logs, and guarantee that when the CEO asks a question, the answer is accurate.
Khaled framed this as the emergence of the “agent owner” role in finance. You’re not the person who makes the Excel file or the Power BI report anymore — you own the agent that answers from the model. The shift is from production to governance, from building to guaranteeing.
Copilot Cowork: The Best of Both Worlds
One of the session’s most practical revelations was Khaled’s demonstration of Copilot Cowork — Anthropic’s Claude Cowork deployed within Microsoft’s Copilot ecosystem. This integration gives users Claude’s reasoning capabilities with native access to Microsoft 365 data: emails, SharePoint files, Teams transcripts.
Khaled showed how he used it to draft 20 personalised emails by having Cowork read a meeting transcript, cross-reference an Excel file on SharePoint with attendee data, and generate individual drafts. He also demonstrated it performing contract over/under analysis by finding contracts on SharePoint and matching them against actual usage data — all without manual file uploads.
His usage pattern was striking: 90% of his AI time in the previous week was spent in Copilot Cowork rather than Claude directly, purely because of the Microsoft 365 data access. He even trained Claude Cowork to write his SOWs, exported the skill to SharePoint as markdown, and then had Copilot Cowork consume that markdown to maintain consistency across both environments.
Expert Amplification vs Vibe Coding
Both Lance and Khaled converged on a critical distinction: AI tools are exceptional at tasks but cannot deliver projects. Claude can build a formatted Excel workbook in 90 seconds. It cannot build your three-statement financial model end-to-end with all the contextual business logic, exceptions, and judgement that a seasoned modeller applies.
This means experts become superhuman — they use AI to eliminate grunt work and focus on judgement, architecture, and quality assurance. Meanwhile, those who attempt to “vibe code” their way through complex deliverables without understanding the underlying domain will produce work that fails in production.
Khaled put it directly: in the hands of people who know what’s happening, these tools are dangerously powerful. The corollary is equally true — in the hands of people who don’t, they’re just dangerous.
Applied Knowledge Is Power
The session closed with what may be the most important principle to emerge from the Future of Finance Lab so far. Khaled’s philosophy — “knowledge is not power; application of knowledge is” — captures the thread that runs through every session in this series.
Learning Claude, Power BI, Fabric, or any tool in isolation is insufficient. The value comes from applying those tools to problems you already understand deeply. Build a skill for something you’re passionate about. Use AI to do your actual job better, not to learn a tool abstractly. The finance professionals who internalise this will outperform those who collect certifications but never ship.
What’s Next
Session 10 marks another milestone in the Future of Finance Lab — but the series continues. Across ten sessions so far, the Lab has explored the full spectrum of AI-augmented finance: from Excel and Claude foundations through to production-ready data agents on Microsoft Fabric. The consistent message has been that the tools are evolving rapidly, but the fundamentals — data literacy, domain expertise, process understanding, and critical thinking — matter more than ever. There’s plenty more to cover, and we’ll keep bringing practitioners like Khaled to share what’s actually working in the field.
Ready to go deeper? The AI-Powered Accountant programme covers eight weeks of hands-on training across Excel, Claude, Power BI, workflow automation, and capstone skill building. Visit modelcitzn.com to learn more, or explore all Future of Finance Lab sessions on the YouTube channel.
Call to Action
Curious to see how AI is reshaping finance, model by model?
Explore the full Future of Finance Lab series for in-depth discussions, real-world experiments, and practical strategies to future-proof your finance function. Stay tuned for more sessions in 2026 as we continue to chart the evolving landscape of technology and finance.
For the full session recording, downloadable models, and additional resources, visit our Knowledge Hub or connect with us on LinkedIn and YouTube.
Ready to future-proof your finance skills?
Looking Ahead
The Future of Finance Lab is more than a webinar — it’s an interactive community dedicated to learning, sharing, and growing together. We invite you to join our next session and become part of this exciting journey as we explore what’s possible when finance meets AI.finance meets AI.
For resources, recordings, and more, visit our Knowledge Hub and stay tuned for further updates!
You can find more content on Eloquens, including the FREE slides, Excel workbooks and Power BI Setup user guide from Claude.
The session was also recorded and is available to be viewed on YouTube.
Want to discuss how AI can transform your finance function? Get in touch with Model Citizn to learn more about our approach to AI-powered financial modelling and strategic implementation.
Friday’s Future of Finance Lab
Join our fortnightly community where finance professionals share insights, solve real challenges, and stay ahead of the AI revolution (max 50 attendees).
Key Benefits:
✅ Live Problem Solving – Bring work challenges
✅ Expert Insights – Practitioners not trainers
✅ AI Integration – Leverage AI in finance
✅ Networking – like-minded professionals
✅ Zero Cost – Completely free, always
What You’ll Get:
✅ – Fortnightly Focus Areas in the following areas
✅ – Financial Modeling Deep Dives
✅ – Data Analysis & Power BI Techniques
✅ – AI Applications in Finance
✅ – Open Forum & Case Studies Exclusive Resources
✅ – Meeting recordings and AI-generated summaries
✅ – Templates and tools shared during sessions
✅ – Resource library access
Who Should Attend:
✅ – Finance professionals wanting to upskill
✅ – Data analysts working with financial data
✅ – Anyone curious about AI in finance
✅ – Business leaders seeking data-driven insights
Buckle up and look forward to seeing you there!
AI Accounting Finance #CFO #FinancialModeling #AIAdoption #FutureOfWork