Intuit's AI Strategy with Sasan Goodarzi

Is AI actually "intelligent," or are we just projecting? We talk about AI like it’s a sentient colleague, but the reality is often far more nuanced (and less sci-fi) than the headlines suggest. I spent some time digging into what’s happening "under the hood" and why our current definitions might be leading us astray. I’ve shared my full breakdown in my latest blog project.

💡 We wanted to share a recent post from our CEO, Alan Nagle...a perspective that really resonates with how we think about AI and risk at KYP AI can accelerate decisions, but in regulated markets continuous oversight is what makes that progress sustainable. Real scale comes from knowing your portfolio, monitoring change in real time and keeping risk aligned to policy.

AI fatigue is real. AI confusion is expensive. This week in my Forbes column: 🔹 AI models beating ChatGPT at specific tasks 🔹 LinkedIn cutting hiring time with agentic AI 🔹 Intuit doubling down on fintech integrations 🔹 Voice AI saving small businesses from lost revenue 🔹 Wealth managers rattled by AI tax automation The question isn’t “Should we use AI?” It’s: Which one — and how do we standardize without chaos? Here’s what small businesses need to know. https://lnkd.in/e9-3Mw_3 ❓ Curious — are you using one AI platform across your company or multiple? #businessowners #ai #artificialintelligence #smallbusiness #smallbusinessowner #technology Intuit Newo.ai Altruist

Is it time to panic? 📉 The recent release of Anthropic's Claude 4.6 didn’t just create a buzz; it triggered a massive sell-off in software stocks with the introduction of these new AI plugins. From what I read, there is a growing fear that after the legal practice, accounting and bookkeeping platforms are the next domino to fall in this disruption. The talk about AI isn't new. Accounting firms, especially the Big 4, are already taking the necessary steps to stay up to date and relevant, building their own agentic platforms with NVIDIA and Microsoft, etc that do much more than chat. However, smaller organisations, including the millions of SMEs (small and medium enterprises), are not expected to ride the AI bus (for now) for a couple of reasons, even if these tools are free: (a) most lack the financial resources and personnel to identify and implement the best use of the technology (b) without a human or another expert to audit the output of these new AI tools, a small error can create a massive liability in their books and operations Giving these powerful tools to someone without subject matter knowledge is like giving my 4-year-old son the keys to the family car. I might love his enthusiasm, but I wouldn’t trust him (for now again) to get us to our camping destination safe and sound. In my current role, I use, see, and experience this daily. I also noticed that a number of our partners (accountants and bookkeepers) and business owners start using AI in finding answers before reaching out to our team. I find this observation refreshing and welcoming. However, using AI isn’t just about being good at prompting. It requires a deep understanding of the why, and in my space, the core accounting features and the logic. Without subject matter expertise, outputs of AI tools may not provide added value at all to their users. Basically, you cannot blame the "agent" when things go wrong. The responsibility still lies with the user of this tool. The AI tool is an enhancement to the engine, but the human or user remains the driver. 🎤 Sources: https://lnkd.in/enutkdfT https://lnkd.in/exkdBF5c

AI has the worst PR machine ever. Great marketing, but immensely bad PR. How come, that developers out of all people - a group historically under pressure to change for the latest JS framework, newest k8s service architecture and the most recent Azure depreciation is afraid and opposed to the changes introduced by AI? (myself partly included!!) Because AI labs only talk about the negative impact it will have for everydays people, without even realizing. Great that you solved coding, but what about the Millions of people who enjoyed coding and didn't learn anything else? Great that accounting is the next to be solved within months, but what about all the millions of accountants? Congrats that soon we don't need middle management any more, but what about all the middle managers who can't do anything else? I know that there always was job displacement in the past, but it was always kinda limited to one area. According to AI labs, this time it will happen across all the population. Whitout any plan on whatsoever. Then comes the thing about infrastructure: AI datacenters are huge. Need a lot of electricity. At the same time housing prices are at an all-time high, and same will go for power soon. But great that you solved accounting for us. So, letting this thought-piece behind me, I think Anthropic seems to be the first to at least partially get their absolute lack of common sense and groundedness in reality and they just announced this 👇 It's a start I'd say.

Last week we started to pull back the curtain on PredictAP, Inc. — giving you a behind-the-scenes look at how it actually works, with our resident AI expert Dr. Mirek Riedewald. The response was incredible. So today we're going deeper. First, a little backstory on Mirek. Dr. Riedewald is a Professor of Computer Science at Northeastern University's Khoury College — one of the country's leading CS programs. He has spent years at the forefront of AI research, working on everything from scalable data systems and large language models to real-world machine learning implementation for both startups and major enterprises. He is exactly the kind of mind you want when a problem gets genuinely hard. We found each other through the State of Massachusetts AI Jumpstart Program — one of those chance encounters you don't plan for but are incredibly grateful for. We showed him what we were building. He leaned in. Because here's what Mirek told us: he had been waiting for a problem like this. On the surface, invoice coding sounds almost trivially simple. A vendor sends a bill. You code it. You pay it. But the moment you try to automate that at scale — across hundreds of real estate firms, each with their own vendor relationships, property structures, GL accounts, and years of unwritten institutional logic — the complexity explodes. Every company behaves differently. Every chart of accounts is unique. And almost none of that context ever appears on the invoice itself. For Dr. Riedewald, this wasn't a limitation. It was exactly the kind of messy, real-world problem that modern AI methods were made for — and had not yet been seriously applied to. In his latest piece, Mirek digs into the WHY. Why is this problem so much harder than it looks? Why do generic AI models fall short? And what does it actually take to build an AI system that learns the specific, evolving logic of each individual business? It is a fascinating read — whether you are in real estate, finance, or just genuinely curious about where AI meets the real world. Link to Mirek's full article in the comments. And follow Dr. Riedewald — you will want to be there for his next deep dive. https://lnkd.in/eEJTzBDy #PredictAP #AI #AccountsPayable #RealEstate #InvoiceAutomation #ThoughtLeadership #LLM #PropTech #NortheasternUniversity

Every AI project hits the same wall: The model works. The predictions are good. Then someone says “Let’s just put it in a spreadsheet” That works. Until it doesn’t. The real failure isn’t the AI. It’s the brittle glue holding everything together. AI is moving from prediction to execution. And execution needs infrastructure, not improvisation. Big thanks to Elia Freedman for the inspiration for this blog post. This is where the hard software problems actually live. If you’re thinking about what comes after spreadsheets, check out TrueMath where deterministic calculation logic meets AI. https://lnkd.in/ghUSayaE

You don't need to go all in on AI. You just need to stop ignoring it. I talk to small business owners every week. The ones struggling with AI all say the same thing: "There are too many tools." "I don't know where to start." "I don't have time to figure it out." I get it. But here's what I'm also seeing: The businesses that started small with AI 6 months ago? They're saving 10+ hours a week. They're cutting costs they didn't even know they had. They're making faster decisions with better data. And the ones still waiting for the "right time"? They're falling behind quietly, and then all at once. Here's the thing nobody tells you about AI adoption: You don't need to overhaul your business. You need one tool that fits one workflow that solves one real problem. That's it. That's your starting point. Maybe it's automating your client follow-ups. Maybe it's using AI to clean up your bookkeeping process. Maybe it's getting a first draft of that proposal done in 10 minutes instead of 2 hours. One tool. One win. Then build from there. The businesses that fail with AI aren't the ones that started too small. They're the ones who either tried to do everything at once or did nothing at all. Here's the honest truth about AI for small businesses right now: → It's not about replacing your team. It's about making them faster. → It's not about chasing every new tool. It's about finding the right one. → It's not about being an expert. It's about being willing to start. → It's not about spending more money. It's about seeing a real return on the money you do spend. The gap between AI-ready businesses and everyone else is getting wider every month. But the barrier to entry? It's never been lower. You don't need a tech team. You don't need a massive budget. You need a clear starting point, a plan that fits how you actually work, and someone who can connect the dots between AI and your bottom line. That's exactly what we built The AI-Ready Business for: practical AI guidance paired with real financial strategy, so every move makes sense for your business, not just in theory, but in your P&L. If you've been on the fence, stop waiting. Start with one thing this week. Your future self and your margins will thank you. What's the one task in your business you wish AI could handle for you? Drop it below; you might be closer to a solution than you think. 🔗 https://lnkd.in/e8G_U-58

Lucid + PwC + AWS helped make finance AI-native—cutting forecasting & scenario modeling from weeks to <1 minute and scaling 14 AI use cases in 10 weeks. A strong blueprint for faster insights, better decisions, and truly AI-enabled operations.

🚨 A stealth AI startup just raised $75M to completely transform accounting—and the results are already mind-blowing. Meet Accrual, the company that emerged from the shadows this week with General Catalyst leading their massive funding round. Here's what's got the entire accounting industry talking: ✅ 85% reduction in tax preparation time ✅ 60% faster review processes ✅ AI agents that read complex documents like seasoned CPAs ✅ Already working with major firms like H&R Block and Armanino But here's the game-changer: Their AI doesn't just speed things up—it produces "manager-review quality" work straight out of the gate. We're talking about AI that can handle messy K-1s, multi-hundred-page statements, and complex client data with the precision of a senior accountant. The math is staggering: Every 50 complex returns processed effectively adds the capacity of one full accountant without increasing headcount. This isn't just automation—it's augmentation. While some CPAs are worried about being replaced, the smart ones are already figuring out how to leverage this technology to serve more clients, tackle higher-value work, and scale their practices like never before. The firms that adapt first will dominate. The ones that wait will struggle to compete. Here's my prediction: Within 3 years, every major accounting firm will either be using AI-native platforms like Accrual or scrambling to catch up. The question isn't whether AI will transform accounting—it's whether you'll be leading the transformation or watching from the sidelines. For accounting professionals reading this: This is your moment to get ahead of the curve. Start learning about AI tools in your field. Experiment with automation in your current workflows. Position yourself as someone who embraces innovation, not someone who fears it. The future of accounting isn't about replacing humans—it's about making humans incredibly more powerful. What's your take on AI in accounting? Are you excited about the possibilities or concerned about the disruption? #AccountingAI #FutureOfWork #AITransformation