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Oracle’s Q2 FY26 results showed NetSuite Cloud ERP revenue reaching $1.0B, up 13% year over year—outpacing Oracle’s broader SaaS growth. This steady performance comes as Oracle’s stock has pulled back sharply from its September peak, highlighting the contrast between market volatility and NetSuite’s consistent execution as a core cloud ERP platform.

LPT and Tipalti have announced a strategic partnership combining payment orchestration with global AP automation—signaling a broader shift toward unified, end-to-end money-movement systems. As cross-border complexity grows, pairing revenue data with payouts highlights a key truth: AI is only as strong as the data connectivity behind it.

AI is reshaping compliance, and ComplyControl is one of the companies leading that shift. In this Q&A, founder Roman Eloshvili explains how his AI-native platform delivers real-time risk intelligence, unifies fragmented data, and was recently recognized as a technology leader in the Generative AI in Risk and Compliance.

AI security is a massive concern. That’s why we’re interviewing cyber expert Yoav Crombie about the state of the market and his new AI security product, Pragatix—an enterprise solution that includes a fully private, on-prem AI designed to keep sensitive data protected and under full organizational control.

NetSuite was named a Leader in two 2025 Gartner Magic Quadrants — a meaningful recognition at a time when AI is reshaping finance and ERP. Gartner evaluates vendors on Completeness of Vision and Ability to Execute, and NetSuite’s strength comes from its unified, all-in-one architecture. As I argue in this piece, AI only delivers real insight when data is normalized, consistent, and connected — something NetSuite enforces by design. With embedded AI, open model integration, an

The AI Trial Balance Trial: Chat GPT low effort failure, Gemini won't even try and Claude tried hard but failed harder. The results were clear: general-purpose AI still can’t handle even basic accounting reporting reliably.

When your CEO “chats with the data” and celebrates a great quarter that never happened, you’ve got a data problem — not an AI problem. AI doesn’t fix bad data; it amplifies it. This article explores what good data actually looks like, and why deliberate, consistent data design is the real foundation for AI-ready finance.

Tipalti’s new Global Finance Outlook report, based on a survey of 2,300 finance professionals, reveals that only 7% have fully automated AP operations, while 83% report higher workloads and 66% more manual work. Despite strong belief in AI’s potential, adoption remains slow — a reminder that before AI can transform finance, teams must first build structured, unified data foundations.

The real power of finance data, and the AI built on top of it, starts from the bottom up. A strong data foundation begins with uniform naming, structured onboarding, and disciplined entry at the transactional level. Companies that build from clean, consistent inputs will unlock faster closes, better insights, and true AI leverage. Those that don’t will spend their time fixing what better design could have prevented.

In this review, I test DealSage.io, an AI-powered platform for managing M&A deal pipelines. Built by former JP Morgan and Palantir execs, it streamlines due diligence, financial analysis, and deal tracking with smart data extraction and intuitive workflows. In my test, it handled messy PDFs, flagged errors, and saved hours of manual work, a sleek upgrade from Excel for dealmakers.

NetSuite has unveiled NetSuite Next, a major AI-driven evolution of its ERP platform that embeds conversational AI, agentic workflows, and natural language search directly into the suite. Building on three earlier AI showcases we’ve covered at TheCFOai.com, this release marks NetSuite’s transition from incremental feature updates to a robust AI-native ERP experience, one powered by standardized, governed data that delivers more accurate and context-aware insights than multi-m

AI cannot currently scale to meet the demands of high-volume, low-error-tolerance business processes. Despite the Agentic AI and automation, foundational limitations remain: AI’s probabilistic nature inherently produces variance, which compounds across complex workflows. From payroll to compliance, enterprise use cases demand precision, not educated guesses. Until models overcome these structural issues, AI will remain most valuable in low-volume use cases.

Tipalti has raised $200M and rolled out new AI features, from natural language reporting to predictive bill approvers. While these enhancements make the platform easier to use, they feel more incremental than transformative. For CFOs, Tipalti remains a strong payables tool. But there's only so much you can do as an AP module.

Google’s new BigQuery natural language feature for querying is a leap forward. These tools let users explore complex data relationships and now, you can do it using plain English instead of SQL.

A review of OpenAI’s recent paper on AI hallucinations, which argues that benchmark and evaluation incentives are the root cause effectively blaming the “test” for the model’s guessing behavior. While the explanation is elegant, it's a copout. I suggest the field needs deeper exploration into “IDK models”. If hallucinations can't be eliminated can AI companies design a sustainable, trustworthy tradeoff between confidence and hallucination?

NetSuite’s $1B milestone highlights more than just Oracle’s momentum it spotlights a critical tension in today’s AI-driven enterprise tech: the tradeoff between data quality and feature specialization. While standalone tools often race ahead with the flashiest AI features, they leave companies juggling fragmented data and integration headaches. NetSuite and ERP platforms like it offer a different path: unified, structured data across business functions that can power strategi

QuickBooks AI Agents: Smart Enhancements, Not a Full Virtual Team As a longtime QB user, I was eager to explore Intuit’s newly announced AI agents. These tools are meant to automate core business workflows like invoicing, transaction categorization, financial analysis, and customer engagement. The marketing describes them as a “virtual team” — but after watching a few hands-on reviews and testing some of the features myself, I’d describe them more as smart enhancements than a

AI tools like ChatGPT and Gemini can sound confident — even when they’re wrong. One time, ChatGPT told me July 1, 2025 was a Monday (it was actually a Tuesday). These so-called “hallucinations” can be far more subtle in finance, from misquoting accounting rules to fabricating data. For CFOs, the takeaway is clear: AI outputs are a useful draft — but they always require verification.

Elkar, a new AI add-on for Excel, exceeded my expectations where other AI tools fell short. From handling consolidations correctly to reformatting a 200+ row P&L, it showed real accounting nuance. Elkar proves how AI can save finance teams time inside their most familiar tool.

NetSuite’s new AI Connector Service is more than just another feature — it’s an architectural shift. By supporting the Model Context Protocol (MCP), NetSuite is giving customers the flexibility to bring their own AI models into ERP while keeping governance and structure intact. As I’ve written before, AI is only as good as the data you feed it. That’s why this move plays to NetSuite’s greatest strength: clean, connected, normalized data across finance, operations, CRM, and HR