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Future of AP: Old challenges, fresh perspectives



Future of AP: Old challenges, fresh perspectives

Imagine turning your often-overlooked Accounts Payable department into a strategic powerhouse. While businesses race to optimize every corner of their operations, AP quietly holds untapped potential.

The future of AP automation promises to transform this traditional back-office function into a strategic asset that drives company-wide growth.

As businesses face increasing financial pressures, the modern AP team must evolve beyond manual tasks. In the new era of Accounts Payable— every invoice processed should be a step towards long-term success.

AP automation: A landscape of opportunity

Building on Accounts Payable's evolving role, the AP automation market offers a wide range of solutions to meet this new strategic imperative.

These tools go beyond simple digitization, offering comprehensive platforms that automate invoice processing, streamline approvals, and optimize payment workflows.

Finding the right vendor can be overwhelming with so many players in the AP automation market. This overview highlights critical providers offering solutions to streamline workflows, optimize payments, and boost efficiency. 

From AI-driven platforms to full-service automation, these top AP automation vendors help organizations future-proof processes and free up valuable resources.

AP Solution Market Segment Value Proposition Pricing G2 Rating
Nanonets Midmarket + Enterprise AI-powered invoice OCR automation with customizable workflows From $999/month 4.7/5
Tipalti Midmarket + Enterprise Global payments automation with tax compliance From $299/month per user 4.6/5
AvidXchange Midmarket + Enterprise Paperless processing with extensive system compatibility Custom pricing 4.5/5
Stampli Midmarket User-friendly interface with real-time collaboration for quick invoice approvals From $500/month 4.8/5
MineralTree SMB + Midmarket Full AP automation with ERP integration and fraud protection Custom pricing 4.4/5
Bill.com SMB Easy-to-use AP automation for payments and vendor management From $45/user/month 4.3/5
Basware Enterprise Scalable AP and procurement automation for global operations Custom pricing 4.3/5
SAP Concur Enterprise Comprehensive spend management integrated with ERP systems Custom pricing 4.2/5
NetSuite Midmarket + Enterprise All-in-one ERP with automated AP workflows and detailed financial analytics Custom pricing 4.4/5
Coupa Midmarket + Enterprise Procurement and AP automation with real-time spend visibility Custom pricing based on modules 4.5/5
Beanworks SMB + Midmarket Streamlined invoice approvals with accounting integration From $1,000/year 4.7/5
Melio SMB Flexible payment options with automated reconciliation Custom pricing 4.2/5


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Challenges with current AP processes

Organizations face a critical juncture between promise and reality as the AP landscape evolves. While the vision of a fully integrated, AI-driven AP process is compelling, many current solutions fall short of this ideal.

Many existing solutions only partially automate specific parts of the AP process. This leads to inefficiencies, as businesses have to rely on manual workarounds or additional software to fill the gaps. 

Proper end-to-end AP solutions powered by AI are designed to streamline the entire workflow, from procurement to payment, eliminating unnecessary complexity and human intervention. 

Let's explore some of these challenges:

Integration complexity and overreliance on consultants

A major challenge in AP automation is integrating various tools for different tasks.

Many businesses still rely on multiple systems for invoice processing, approvals, and payment reconciliation – this is highly inefficient. SaltPay's experience illustrates this issue:

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SaltPay, initially struggled to manage separate systems for invoice processing and procurement, leading to delays and inaccuracies.

They overcame this by adopting Nanonets' unified AP automation solution, which streamlined workflows and achieved 90% automation in invoice processing. This significantly reduced the need for manual intervention and allowed for faster, more accurate processing.

Many companies often face challenges similar to Saltpay's. They rely on specialized skills for custom integrations, which increases complexity and costs.

The future of AP lies in seamless, integrated platforms that eliminate the need for disjointed systems and reliance on external consultants.

Limited or nonexistent inventory management and PO matching

Many AP platforms, including Bill.com, lack robust inventory management or item-level PO matching. This forces businesses to manually reconcile POs with invoices, slowing the process and increasing errors. It also creates a gap in automating the entire procure-to-pay cycle. 

Automating your accounts payable process can integrate tasks like invoice capture, approval routing, and payment processing while managing inventory and purchase orders, streamlining operations, reducing manual intervention, and improving overall efficiency​.

Too reliant on manual ways of working

Many AP teams still have to rely on manual entry for invoice coding and data enrichment, which increases the risk of errors and slows down the process. Without AI-driven tools, these platforms can't automatically apply the correct general ledger codes or detect discrepancies in invoice data. 

This lack of intelligence in existing systems results in inefficiencies, making it harder for AP teams to keep up with high invoice volumes and maintain accuracy.

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For instance, Tapi, a property maintenance company processing growing volumes of invoices, spent over $10K monthly on manual validation, with a turnaround time of more than 6 hours.

By adopting Nanonets, Tapi reduced costs by 70%, and invoice processing time dropped to just 12 seconds, greatly enhancing their efficiency and customer experience.

Limited approval routing customization and poor exception handling

Approval routing is often a huge challenge for AP teams, especially in businesses with complex workflows. Managing invoice exceptions without intelligent automation is manual and time-consuming.

For example, mismatches between a purchase order (PO) and an invoice often need manual review, causing delays and inefficiencies. 

Traditional systems offer rigid approval processes that slow invoice approvals and create bottlenecks, leading to delays and errors. These systems lack AI capabilities for automatic exception handling, leading to increased intervention from AP teams.

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Happy Jewelers, a retail company, faced similar challenges with limited approval routing customization. By integrating Nanonets' AI-driven AP automation, they implemented flexible approval workflows tailored to their business needs. 

"We reduced our manual workload by 90% using Nanonets' automated workflows." – Happy Jewelers

Adopting flexible approval routing through automated workflows will help AP teams manage high invoice volumes more efficiently, reducing errors and improving financial oversight.

Cross-border multi-currency transactions

The future of AP automation will focus on simplifying complex, cross-border transactions. 

Managing different currencies, tax regulations, and compliance rules across countries can be overwhelming for AP teams, but AI-driven automation can help. These systems can automatically handle real-time currency conversions, validate taxes, and reduce manual errors. 

For example, Nanonets’ two- and three-way matching features compare invoices with purchase orders and receipts, making the payment process faster and more accurate without the need for manual checks.

Nanonets automates multi-currency reconciliation by syncing directly with ERP systems. With AI-powered tools like these, AP teams can streamline global transactions, ensuring payments are processed accurately and on time.

Key technologies in future AP processes

The future of AP lies in intelligent automation, yet adoption often faces hesitation.

Concerns about complexity and job security can overshadow these technologies' transformative potential. However, AI and related tools aid human capabilities rather than replace them.

Let's have a look at the key accounts payable automation technologies that AP teams must explore and adopt:

AI-driven invoice processing

Automated invoice processing, driven by AI, can significantly transform an organization by addressing inefficiencies in traditional methods.

AI-powered tools streamline the accounts payable (AP) process from start to finish, automating the capture of invoices, matching them against purchase orders and delivery notes, routing them for approval, and recording transactions within accounting systems—all in a few clicks. 

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42% of organizations still rely on outdated AP processes, and 47% continue to scan or mail physical invoices. These traditional methods can cost $12-$15 per invoice, compared to the $2-$3 cost with automation. 

Nanonets has enabled businesses to reduce invoice processing times by 60% and cut costs dramatically, demonstrating the potential of AI-driven automation to improve efficiency, accuracy, and cost savings.

OCR and NLP enabled invoice capture

AI-powered OCR and NLP technologies have revolutionized invoice capture, significantly easing the workload of AP teams by automating the extraction of invoice data from scanned documents, PDFs, or images, regardless of format. 

This automation eliminates the need for manual data entry, drastically reducing errors and accelerating invoice processing times. 

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For instance, Nanonets helped Expatrio reduce manual data entry by 95%, transforming their AP processes and saving significant time and resources.

With such tools, AP teams can focus on higher-value tasks while the system accurately captures vendor details, invoice numbers, and amounts, streamlining the workflow.

Invoice templates: AI vs template-based solutions

Traditional AP systems rely on pre-defined templates to process invoices, but AI-driven systems learn and adapt to new formats, reducing the need for constant updates.

Template-based solutions require continuous manual adjustments, whereas AI systems automatically recognize new invoice structures, offering greater flexibility and scalability.

ACM Services, a Maryland-based remediation contractor, is an example of a shift from template-based to AI-driven invoice processing. Before implementing Nanonets, ACM relied on traditional systems that required continuous manual adjustments to process invoices due to rigid templates. 

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After adopting Nanonets' AI-driven solution, the system began learning and adapting to new invoice formats. This eliminated the need for constant template updates and significantly increased flexibility and scalability.

ACM saved 90% of its time on manual data entry, making its AP processes much more efficient.​

Automating 3-way matching

AI-based automation enhances the 3-way matching process by cross-referencing invoices, purchase orders, and delivery receipts in real-time. This ensures that every detail, such as quantities and prices, matches across documents before processing payments, reducing discrepancies and delays.

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 For example, Nanonets helped a property maintenance company, Tapi, automate its 3-way matching, eliminating manual checks and significantly reducing processing times. 

By automating these tasks, Tapi reduced their AP costs by 70%, highlighting how AI-driven 3-way matching can improve accuracy, speed, and efficiency for high-volume AP teams.​

Machine learning for GL coding

Manual GL coding can be a time-consuming and error-prone process, especially for AP teams dealing with large volumes of invoices. Traditionally, AP staff manually assign general ledger (GL) codes based on invoice data, often leading to inconsistencies and delays in financial reporting.

Studies show that companies using automated GL coding can process more than 18,649 invoices per full-time employee annually, compared to just 8,689 for those still relying on manual methods.

This shift to automation results in significant time savings and cost reductions.

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By implementing Nanonets' AI-based automation for GL coding and invoice processing, companies like ACM Services saw remarkable improvements.

ACM achieved a 90% reduction in manual data entry, which not only streamlined their AP operations but also significantly improved the accuracy of their financial reporting.

Here's the workflow that Nanonets implemented for ACM:

Future of AP: Old challenges, fresh perspectives

Adopting machine learning for GL coding empowers AP teams to operate with higher efficiency, reduce operational costs, and maintain more accurate financial records.

Robotic Process Automation (RPA) for multistep workflows

Based on pre-set rules, RPA streamlines AP processes by automating multi-step workflows, such as invoice receipt, approval routing, and vendor payments.

This eliminates manual intervention, improves accuracy, and reduces invoice processing times.

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Nanonets helped Tapi automate 70% of their invoice processing, including approvals, making the process 70% faster.

Automating tasks based on value thresholds reduced delays and improved efficiency, allowing the team to handle high invoice volumes without extra staff. Large invoices were sent for senior management approval, while smaller ones were auto-approved. 

Upskilling for the AI future: How AP teams can get ahead

With increasing pressure to upskill in the era of AI and automation, AP teams must adapt to emerging technologies like AI, machine learning, and data analytics.

Mastering these skills will enable finance professionals to leverage automation tools, improve efficiency, and drive innovation.

Developing technical skills: AI, ML, and Data Analytics for finance professionals

In the AP context, developing skills in AI, machine learning (ML), and data analytics isn't about mastering these technologies but understanding how to use them effectively.

  • AI: AP teams can start by learning how AI automates tasks like invoice processing, data capture, and matching using tools like OCR. AI-driven platforms can match invoices with POs and flag discrepancies automatically.
  • ML: Machine learning helps predict cash flow patterns by analyzing historical data. AP professionals should understand how ML models analyze trends like seasonal payment peaks to forecast future payables.
  • Data Analytics: AP professionals can track KPIs such as payment cycle times and supplier performance using Tableau or Power BI platforms. This helps identify bottlenecks and implement cost-saving strategies.

Finance professionals can upskill and improve their daily work by focusing on automation trends specific to AP.

Building a culture of innovation and continuous learning in AP departments

Building a culture of continuous learning is vital for AP teams to harness the benefits of AI and related technologies fully. Encouraging a growth and innovation mindset enables teams to keep pace with rapidly changing technological demands. 

Companies like Amazon and PwC have led the charge by investing in workforce upskilling initiatives focused on AI capabilities. By fostering collaboration on AI-related projects and providing opportunities for hands-on learning, organizations can empower AP professionals to drive innovation. 

Emphasizing continuous learning will help businesses stay agile and future-proof in a tech-driven landscape​.



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