• Opener: Keeping Sensitive Data Away From AI

• Digital Diligence: Upgrade Your Cash Forecasting 

• Product & Company News: Workday, Gusto, AccountsIQ 

• People News: Procurify, UKG, M-Files 

• FATEdex: Our Public Company Tracker

• Upcoming Events/Subscribe & Share

Editor's Note—Welcome to the latest Finance & Accounting Technology Briefing.

CFO Leadership, the publisher of this newsletter, has some valuable webinars and Tech Spotlights on the calendar for autumn. Check the CFO Leadership Council online events page for more information.

With Labor Day over, this year’s Finance and Accounting Technology Expo—bigger, better and more informative—hits New York in less than two months. Don’t forget to register!.

Finally, remember to send your cool, refreshing news on the industry's products, people and companies to vince@cfolc.com.

—Vincent Ryan, editor 

Keeping Sensitive Data Away From AI

Two kinds of companies will cause problems with their approaches to AI security. The first is the kind of company that is so conservative about the use of gen AI by employees that it blocks access to tools like ChatGPT and Claude.

"They're afraid they're going to give away their company secrets to ChatGPT," says Ashok Krish, head of the AI practice at Tata Consultancy Services. "They have an existential fear that these are learning entities and that if you give them enough information, they will understand their business better than they do."

The second category of companies may be braver and more attractive to job candidates, but not smarter. They're embracing gen AI with enthusiasm and prioritizing speedy testing and adoption, eager to see an ROI. The problem is that their data governance implementations are proceeding at a much slower pace.

IBM's Cost of a Data Breach Report, released in July, found AI governance and security woefully inadequate at most of the surveyed organizations. A small number of respondents had AI access controls or governance policies in place, and few had the tools to detect or stop unsanctioned AI use. The problem is that some research estimates that up to 30 percent of the data that employees ingest in public AI tools is sensitive or private data.

To gain insight into how companies can enhance their AI security, we spoke with Tim Freestone, chief marketing officer of private data network company Kiteworks.

A recent survey by Kiteworks found that in some companies, only IT policies and employee training stand between the employee and the exposure of sensitive company or customer data to an AI tool. Why are companies behind on this?

Before the advent of generative AI, the data layer, or data governance in general, received little attention. Everyone put security at the network layer or the application layer. It was too big a problem to deal with security solutions that addressed every single data point in the company. So, there was hardly any data governance.

So, how can companies get on track?

The big movement now is something called DSPM, data security posture management. The goal is to get everything in the cloud, as well as in your endpoints, network and databases, classified and tagged so that you can apply governance management to block data from entering AI systems. DSPM was an afterthought three years ago; now it's a major priority of corporate boards.

Once you have classified and tagged all the data, what do you do next? You block it from being used. That's another layer of technology; the blocking and control layer based on the classification and tagging system in place. An employee won't be able to download a file from your repositories and upload it to ChatGPT.

How does a company approach security when using internal AI systems to do things like streamline workflows?

Companies are developing their own internal AI systems for accessing sensitive data, and they're utilizing one of several open-source models. They are putting access layers on those to make sure only specific data goes into them. That's controllable.

Public models are different. Inside the company network, you can install access controls on a browser, so an employee can't use ChatGPT. But that's only within the network. What happens when the employee goes home? That's where the risks start. "Shadow AI" refers to the unauthorized use of AI. It's challenging to block, unless you have control over every piece of data.

AI "privacy incidents" are on the rise. Can you explain what those are?

When anybody sees something that's private that they shouldn't, it's a privacy violation. Before AI, the mechanisms included an email sent to someone, an open repository that could be viewed, a structured database to which someone had access or an application to which someone shouldn't have access. LLMs are another place where data lives. Companies need to make sure all private data, all of the 'I's"—IP, PII, PHI, PCI—are adequately controlled. Because once that information leaks into an AI [tool], you can't get it out.

—Vincent Ryan, editor, CFO Leadership, vince@cfolc.com      

A CFO's guide to strategic month-end close: This guide reveals how chaotic closes, surprise invoices, and audit fire drills all stem from one overlooked source: broken intake. Learn the hidden costs of unstructured intake, and what to do about it + a one-page checklist to assess your close-readiness today.

The lead instructor of our increasingly popular FATE Tech Certification course, Mark Sue, develops Action Journals to walk executives through the process of evaluating and adopting new solutions for the finance tech stack. The following step-by-step guide is borrowed from the Action Journal for Module 1, Automation in Finance.

Cash Forecasting Upgrade

The value proposition for improving cash forecasting is self-evident; liquidity management, capital raising, capital expenditures, M&A investment, global tax management and working capital optimization all require timely visibility into cash levels and accurate, up-to-date cash forecasts.

If you're still using a spreadsheet to track an asset that important, your organization is missing out on some of the latest features of cash forecasting software, like AI systems that can recognize and incorporate business seasonality; real-time tracking of revenue, expenses and cash flow; enhanced visualization and scenario planning; and customizable financial modeling.

Do you need to upgrade your cash forecasting capabilities? Here are the steps:

Phase 1: Evaluate and describe your current cash visibility setup

How is cash data tracked, consolidated and forecasted currently? What tools or systems do you use (FP&A tool, Excel)? How often do you generate cash flow reports? What's your level of visibility into receivables, payables and cash-on-hand?

Phase 2: Identify gaps and risks

What challenges does the organization face that reduce cash forecast accuracy, delay reporting or hinder planning? Are your systems fragmented, with multiple banks and AP/AR not integrated, for example? Do you rely heavily on data entry? What causes any delays in cash reporting? Are you unable to stress-test scenarios or forecast cash in volatile markets?

Phase 3: Explore opportunities to improve through automation

Which features would deliver the most value to your organization?

• Real-time dashboards for cash balances and trends
• Centralized data feeds from multiple bank accounts, AR/AP
• Automated forecasting models based on live data
• Scenario analysis capabilities
• Predictive analytics to forecast cash risks
• Automated generation of weekly or daily cash flow statements

Phase 4: Assess current tools vs. potential upgrades

Do your existing systems support the desired features and meet future-state requirements? Are you using the features from your accounting software, or is it a dedicated platform? Are there underutilized modules or integrations in your existing stack?

Phase 5: Define Metrics for Improvement

Use one or two of the following metrics to target for measuring: frequency of cash flow reporting, accuracy of cash forecast vs. actual, time spent gathering and consolidating data and ability to test multiple financial scenarios.

Phase 6: Build a 60-day action plan

Assign an owner and target date to each step:

• Document current forecasting workflows (including tools, templates and timing).
• Meet with FP&A or IT/BI teams to explore dashboard and integration options.
• Evaluate potential solutions or upgrades and schedule demos or trial accounts.
• Build a new scenario forecast using existing data (Start with a 10 percent revenue dip model or faster new sales ramp of 20 percent).
• Launch or pilot real-time reporting for cash.

 For a deeper dive into crucial areas of finance automation, see module 1 of the FATE Tech Certification course.

Workday acquired Paradox, a job candidate "experience agent" that uses conversational AI to simplify steps in the job application journey through features like self-scheduling capabilities and 24/7 support. Terms were not disclosed.

Payroll provider Gusto released Gusto Solo, an all-in-one compliance solution designed for solopreneurs—businesses with no employees. The product includes an S-corp tax savings calculator, a "reasonable salary" calculator and a contractor payments solution.

AccountsIQ launched a non-financial metrics feature for its AIQ3 platform. The new capability enables finance to track and analyze operational KPIs alongside core financial data, eliminating the need for manual consolidation.

Business payments platform PayQuicker announced it is adding same-day ACH transfers to its real-time payout capabilities. Same-day ACH will be available to U.S.-based users across its various verticals, including gig economy, affiliate marketing and clinical trial payees.

Procurify appointed Jonathan Su chief product and technology officer to spearhead its AI innovation. Su was previously the SVP of product and engineering for spend management at U.S. Bank and the CTO of Bento for Business.

UKG hired Jim Joudrey as its chief technology officer, reporting to CEO Jennifer Morgan. Joudrey recently served as VP of digital acceleration at Amazon. Before Amazon, he was SVP of analytics cloud engineering at Salesforce.

M-Files appointed Debbie Umbach to the role of chief marketing officer. Umbach was formerly CMO of Own (acquired by Salesforce) and has held marketing leadership roles at Dynatrace and Bitsight.

Stock prices are as of the market close on September 3, 2025.

Plan to join us at the Finance and Accounting Technology Expo, the country’s largest annual trade show for buyers and vendors of corporate finance and accounting software. Next year’s event will occur at New York’s Javits Convention Center on November 13 and 14, 2025. This is an excellent opportunity to network with industry peers, learn from experts and discover new products and services. Register online at cfoleadership.com/fate/

Tech Spotlight: From Static to Strategic: How AI Is Transforming FP&A

September 26, 2025 | 1-1:45pm ET | Virtual

AI in Finance Forum
Co-Hosted by CFO Leadership and Amazon Web Services
November 12, 2025 | 12:30-5:00pm | Javits Center, New York 

Finance & Accounting Technology Expo
November 13-14, 2025   | Javits Convention Center | NYC

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