AI-powered accruals: Automated close for the middle market

Finance and accounting teams across the middle market face mounting pressure to adopt artificial intelligence, yet generic tools rarely meet the accuracy, control and compliance standards this function demands. Companies can address that gap by embedding AI directly into the accrual process to extract data from source documents, confirm estimates with vendors and internal owners, and maintain a complete audit trail throughout, all without adding headcount.

BlackLine makes this possible through a fit-for-purpose, agentic solution built on a unified data foundation, auditable governance and specialized AI agents designed for finance and accounting workflows. This approach automates accrual identification, calculation and preparation end to end for actual invoices, purchase orders and estimates based on historical vendor activity.

The payoff: cut the time spent on accruals by more than 80%, accelerate close by multiple days and free your accounting team to focus on strategic financial analysis instead of manual, repetitive work, all while maintaining full visibility and control at every step.

Where middle market AI adoption stands today

When people talk about AI, they mean different things—and that lack of clarity fuels fragmented adoption. Executive mandates are pushing organizations to adopt AI, but many leaders still lack a clear understanding of how to use it effectively, leading to reliability issues and a shortage of AI talent.

A strong, clean, centralized data foundation is critical for reliable AI outputs and effective adoption. It’s a garbage-in, garbage-out concept: a data architecture built around a single source of truth is essential for building trust in AI.

To demonstrate the shift as organizations move from exploring AI to embedding it into daily operations, the recent RSM Middle Market AI Survey 2026 shows just how far adoption has progressed: 97% of executives who have implemented AI say they are satisfied with the business value they’re seeing, and 86% have integrated AI into their operations. 

However, there’s still a gap between adoption and transformation: only 36% say AI is fully integrated across their core operations and processes, and just 17% describe their AI strategy as transformational. In other words, organizations are seeing value from AI, but that value is still concentrated in pockets of the business rather than fundamentally changing how the business operates. 

In addition, the workforce is set for a significant change: 88% of respondents expect their workforce to look different over the next two to three years, while 91% expect humans and AI to operate as integrated teams during that same period.

“According to RSM’s MMBI AI Survey, 85% of respondents say leadership is more enthusiastic than employees. The enthusiasm gap is where those adoption programs are going to stall,” says Roush. “This is not necessarily a technology problem; it’s a change management issue.”

Furthermore, a successful AI initiative requires clear value aligned with business objectives. This should be demonstrated tangibly to stakeholders in any long-term, scalable implementation.

The key steps include:

If an AI initiative does not align with one of these three priorities, it risks becoming a science project rather than a business investment.

Building trust in AI-powered finance with BlackLine

AI presents significant opportunities for finance and accounting teams, but many AI solutions, particularly generic models, aren’t designed to meet the specific requirements of these functions, raising three key risks:

Therefore, for AI to work effectively in finance, an architecture designed specifically for the function is required. BlackLine delivers this framework through its agentic financial operations approach, built around four components:

In addition, BlackLine has also embedded AI across its platform, spanning record-to-report, invoice-to-cash, source-to-pay and enterprise performance management, including variance analysis.

Modernizing the accrual process with AI

Accrual processes are often highly manual, requiring finance teams to extract and reconcile data from multiple systems, review prior journal entries, analyze new invoices, coordinate with internal and external stakeholders, update accruals, and maintain detailed audit records.

Once accruals are audit-ready, teams typically enter the information into the enterprise resource planning (ERP) system and prepare reports, including variance and flux analysis. Depending on the organization, this can take more than 100 hours each month.

The solution: BlackLine automates this end-to-end process while accounting for each organization's unique accounting workflows, cutting the time spent on accruals by more than 80% and often deploying before the next month-end close.

Here’s how the process works: BlackLine integrates with existing ERP, accounts payable and procure-to-pay systems through read-only connections. Supported platforms include NetSuite, Sage Intacct, Oracle Fusion, Dynamics, Workday and SAP, as well as procure-to-pay tools such as Coupa, Tipalti, Zip and Ariba, and accounts payable platforms including Bill, Airbase and Brex.

AI analyzes structured and unstructured accrual-related data, including invoice line items, memo fields, PDFs and spreadsheets, to draft and categorize journal entries.

In addition, BlackLine automates accrual-related communications with internal and external stakeholders, including follow-ups and the review of responses and attachments. The platform can then update accrual amounts and maintain a complete record of each step in the process.

Benefits of AI-powered accruals automation

Shifting accrual tasks to an AI-powered platform delivers measurable benefits across the close, including:

Accruals automation can support organizations of any size, from large enterprises with significant accrual volumes to midsize and fast-growing companies. It can address accrual challenges across industries, with particular relevance for healthcare and manufacturing.

In addition, when calculating return on investment for AI-powered accruals automation, there's no fixed threshold for determining which organizations benefit most. The key indicator is when accruals consume significant time and resources, often because of high vendor volumes or extensive vendor-related communication.

A proactive approach to AI-powered accruals

As middle market executives mandate AI adoption, choosing technology built for finance, not generic tools, is what determines whether AI adoption sticks or stalls.

For accounting teams, the payoff isn’t just faster closes. It’s the confidence that every number is traceable, every vendor conversation is documented and every dollar accrued reflects what actually happened, not just an estimate carried forward out of habit.

Ready to get started? RSM’s BlackLine advisors can help you evaluate AI-powered accruals solutions and build a stronger foundation for reliable, scalable close automation.