The Growing Pain of Manual Accounts Payable

The Growing Pain of Manual Accounts Payable

Manual accounts payable (AP) processes are no longer sustainable for insurance agencies navigating today’s complex financial landscape. What was once a manageable back-office task has become a bottleneck—draining time, increasing risk, and undermining compliance. With 66% of AP departments still manually handling most invoices, the inefficiencies are not just noticeable—they’re systemic.

• Invoices delayed due to data entry errors
• Duplicate payments slipping through due to lack of validation
• Recurring audit findings from missing documentation
• Staff spending 60% of their time on repetitive tasks
• Fraud attempts impacting nearly every U.S. business annually

These challenges aren’t hypothetical. According to MHC Automation, 96% of U.S. businesses face payment fraud attempts each year, and with 74% of data breaches involving a human element, manual systems are dangerously exposed.

Consider the reality: a mid-sized insurance agency processing 500 invoices monthly may spend over 200 hours manually entering data, verifying vendor details, and chasing approvals. That’s time lost from strategic financial planning and supplier relationship management—resources that could be redirected toward growth.

The cost of inaction is mounting. Manual AP doesn’t just slow down operations—it increases exposure to compliance failures, financial loss, and reputational risk. As HighRadius reports, AI-driven automation can reduce invoice processing time by up to 70%, yet only 9% of AP departments are fully automated—a stark gap between potential and reality.

This isn’t just about speed. It’s about resilience. In a sector where trust and compliance are paramount, manual processes create blind spots. They hinder audit readiness, obscure vendor performance, and leave agencies vulnerable to fraud.

The next section explores how AI-powered automation is transforming AP from a cost center into a strategic asset—unlocking visibility, control, and efficiency.

AI-Powered Automation: The Strategic Solution

AI-Powered Automation: The Strategic Solution

In 2024–2025, insurance agencies are no longer choosing between efficiency and compliance—they’re embracing AI-powered accounts payable automation as a strategic necessity. With 66% of AP departments still manually processing most invoices, the gap between legacy workflows and intelligent automation is both a risk and an opportunity. AI isn’t just speeding up data entry; it’s transforming AP into a proactive, audit-ready function that drives financial resilience.

AI-driven automation delivers real-time invoice processing, fraud detection, and dynamic approval routing—all while reducing human error and freeing finance teams for higher-value work. As Mark Brousseau (President, Brousseau & Associates) puts it: “AI is a co-pilot for us in our jobs... It will eradicate the things we don’t like about our jobs.” This shift is not about replacing people—it’s about empowering them with smarter tools.

• 9% of AP departments are fully automated
• 96% of U.S. businesses face annual payment fraud attempts
• AI adoption in AP has quadrupled in the past year
• Invoice processing time reduced by up to 70%
• Operational costs cut by up to 60%

These numbers underscore a clear truth: manual AP is no longer sustainable. The real transformation lies in end-to-end automation—from invoice receipt to payment, with AI handling data extraction, validation, and anomaly detection.

One of the most powerful capabilities of modern AI is multi-stage invoice analysis. Unlike traditional OCR, AI systems with LLM and advanced document recognition can interpret unstructured invoices—scanned PDFs, handwritten notes, or non-standard formats—with auto-matching rates exceeding 90%. This precision eliminates duplicate payments and ensures compliance with internal policies.

Consider the MIT-developed Linear Oscillatory State-Space Models (LinOSS), which outperform existing models in long-sequence forecasting by nearly 2x. While not yet commercially deployed in AP tools, this breakthrough signals the future: AI that learns from historical patterns to predict approval delays, flag high-risk vendors, and even suggest optimal payment timing—all in real time.

Note: No insurance-specific case studies are available in the research, but the principles are transferable across regulated industries.

Still, success depends on strategic implementation. The most effective approach starts with high-risk or high-volume vendors, using dynamic approval workflows based on invoice type, value, and vendor history. This ensures AI handles routine tasks while humans intervene only when judgment is required—a human-in-the-loop model that balances speed with oversight.

Next, select tools with strong OCR, LLM capabilities, and integration with core systems like Salesforce, Guidewire, or SAP. Platforms like HighRadius and MHC Automation lead in fraud prevention and secure, cloud-based workflows—essential for audit readiness in a sector where 74% of data breaches involve a human element.

As AI reshapes financial operations, partnerships with full-service providers like AIQ Labs are becoming critical. These firms offer custom AI development, managed AI employees, and AI Transformation Consulting—ensuring agencies don’t just adopt tools, but build future-proof, compliant, and sustainable systems.

The future of insurance AP isn’t just automated—it’s intelligent, proactive, and resilient. The next step? Assess your current workflow and identify where AI can deliver the fastest impact.

Implementing Automation: A Phased, Proven Approach

Implementing Automation: A Phased, Proven Approach

Manual invoice processing is no longer sustainable for insurance agencies facing rising fraud risks and staffing challenges. A structured, phased rollout minimizes disruption while maximizing ROI and compliance readiness. The key is starting small, scaling smart, and embedding human oversight where it matters most.

Begin by mapping your existing invoice lifecycle—how invoices arrive, who reviews them, where bottlenecks occur, and where errors are most common. This diagnostic step reveals pain points and identifies high-impact areas for automation.

• Identify high-volume vendors with repetitive invoice types
• Flag high-risk vendors with frequent discrepancies or late payments
• Document recurring manual tasks like data entry, matching, and exception handling
• Evaluate system silos that hinder visibility across Salesforce, Guidewire, or SAP
• Measure current processing time per invoice and error rate

According to MHC Automation, 66% of AP departments still manually handle most invoices, signaling widespread inefficiency. A clear workflow audit is the first step toward closing that gap.

Focus your initial automation efforts on high-volume or high-risk vendors—not every vendor at once. This targeted approach delivers visible results quickly and builds internal confidence in the system.

• Start with vendors generating 50+ invoices/month
• Target vendors with inconsistent pricing or frequent duplicates
• Automate standardized invoice types (e.g., IT services, software subscriptions)
• Use AI to extract data from PDFs and scanned images with high accuracy
• Enable auto-matching to POs and contracts (achieving >90% match rates, per HighRadius)

This strategy aligns with expert guidance from Mark Brousseau: “The first thing you’ll want to do in 2025 is automate your invoice-to-pay process” (MHC Automation).

Choose platforms with strong OCR and LLM capabilities and proven compatibility with core systems like Salesforce, Guidewire, and SAP. Security and audit readiness are non-negotiable—especially in regulated insurance environments.

• Prioritize cloud-based platforms with end-to-end encryption and access controls
• Ensure audit trails are automatically generated for every action
• Verify compliance with privacy regulations (e.g., GDPR, HIPAA)
• Confirm integration with existing financial systems to avoid data silos
• Evaluate vendor sustainability practices—74% of data breaches involve a human element, making secure systems critical (MHC Automation)

Leverage AI to route invoices based on value, vendor history, invoice type, and risk profile. Use intelligent rules to flag anomalies—like duplicate payments or pricing outliers—while automating routine approvals.

• Set auto-approval thresholds for low-risk, low-value invoices
• Trigger human review for high-value or non-standard transactions
• Use AI anomaly detection to prevent fraud (96% of U.S. businesses face payment fraud attempts annually, per MHC Automation)
• Maintain human-in-the-loop oversight for complex or high-stakes payments

This balance ensures speed without sacrificing control—letting AI handle volume, while humans focus on judgment.

To avoid vendor fragmentation and ensure long-term success, engage a partner like AIQ Labs that offers AI Development, Managed AI Employees, and AI Transformation Consulting. This single-source model streamlines strategy, implementation, and governance.

• Gain access to custom AI systems built for your agency’s unique needs
• Benefit from managed AI personnel who work alongside your team
• Receive ongoing optimization and risk monitoring
• Future-proof with support for emerging models like MIT’s LinOSS, which improves long-sequence forecasting by nearly 2x (MIT News)

With this phased, expert-guided approach, insurance agencies can transition from reactive AP to proactive financial leadership—driving efficiency, compliance, and strategic insight.

Best Practices for Sustainable, Secure Adoption

Best Practices for Sustainable, Secure Adoption

The future of insurance agency finance hinges on responsible automation—where AI enhances efficiency without compromising security, ethics, or sustainability. As AP automation accelerates, agencies must prioritize governance, compliance, and environmental stewardship to ensure long-term success.

Key considerations include: - Maintaining human oversight for high-value or complex transactions
- Implementing AI governance frameworks to manage risk and ensure ethical use
- Prioritizing energy-efficient AI models to reduce environmental impact
- Ensuring compliance with privacy regulations critical to the insurance sector
- Using secure, cloud-based platforms with audit trails and access controls

According to MHC Automation, 74% of data breaches involve a human element, making secure, auditable systems non-negotiable. Meanwhile, MIT research warns that global data center electricity use reached 460 TWh in 2022, underscoring the need for sustainable computing practices.

A real-world example of responsible adoption lies in the phased rollout strategy recommended by experts. Starting with high-risk or high-volume vendors—such as claims processors or reinsurance partners—allows agencies to test systems, validate outcomes, and build trust before scaling. This aligns with Mark Brousseau’s advice: “The first thing you’ll want to do in 2025 is automate your invoice-to-pay process.”

Agencies should also partner with providers like AIQ Labs, which offers AI Transformation Consulting, managed AI employees, and custom AI development—ensuring strategic alignment and operational ownership without vendor lock-in.

Moving forward, the focus must shift from mere automation to responsible automation—where technology serves people, not the other way around.