A New AI Series on Payables Place
The power of artificial intelligence (AI) is undeniable. Its impact and influence are revolutionizing the Accounts Payable (AP) and Business-to-Business (B2B) payments automation market. According to research from Ardent Partners, AI will soon be ubiquitous in this sector, offering unparalleled efficiencies and capabilities. The transformative possibilities of AI will drive innovations in invoice processing, payment automation, fraud detection, and overall financial management, streamlining enterprise operations and improving business decision-making.
In view of these advancements, Ardent Partners is launching a special “AI in Action” interview series. Our “AI in Action” series represents an opportunity for our Chief Research Officer, Andrew Bartolini to sit down with senior executives at the ePayables solution providers that are focused on AI now and in the near-term and use these discussions as an opportunity to share their company’s focus on, expertise in, and vision for AI within the AP industry.
Today’s AI in Action profile features a conversation with Jon Titel, Senior Vice President of Product for DocuPhase.
AB: Good day Jon, tell our readers a little bit about yourself.
My name is Jon Titel, SVP of Product. I have 20+ years building AP Automation platforms.
DocuPhase
AB: Thank you. I think I know your answer but let me ask anyway … what are the biggest opportunities for AI to improve AP and B2B payment efficiencies and productivity?
JT: The most significant opportunities for AI lie in streamlining manual, time-consuming processes, such as invoice data extraction, validation, and approvals. AI can automatically categorize and route invoices based on historical data, reducing the time AP teams spend on processing. In B2B payments, AI can optimize cash flow management by predicting payment cycles, recommending optimal payment terms, and even preventing fraud by identifying unusual transaction patterns. This results in faster processing, and overall higher productivity for both AP teams and finance departments.
AB: How do you view your customers’ (and prospective customers’) AI attitudes?
JT: Our customers are increasingly open to adopting AI, but there’s a mix of excitement and cautious optimism. Many recognize the potential for AI to transform their processes, but there is still so much unknown about AI and how it applies to their daily lives. They’re unsure where to start. Our prospective customers want to see practical use cases with clear ROI before fully committing and ensure AI is not replacing, but rather enhancing, their existing processes. Our customers who are already relying on automation tools tend to be more willing to invest in AI, particularly if it directly addresses common pain points like data entry, duplicate payments, or fraud detection.
AB: What are the leading AI subsets (e.g., machine learning, natural language processing, deep learning, etc.) with the biggest impact on accounts payable/B2B payment solutions? And why?
JT: Machine learning (ML) is one of the most impactful AI subsets in AP, particularly in predictive analytics for cash flow and fraud detection. ML algorithms improve over time, allowing systems to more accurately identify patterns and anomalies. Natural language processing (NLP) is also critical, especially in extracting and understanding unstructured data from invoices, contracts, or emails. Deep learning, while still emerging, can play a role in enhancing the accuracy of these processes by analyzing vast datasets with a level of precision that traditional methods can’t match.
AB: How are you ensuring the accuracy and reliability of customers’ AI models (AI data output)?
JT: We ensure accuracy and reliability by combining AI-driven processes with a human-in-the-loop approach. While AI is powerful, it’s not perfect, and we’ve found the greatest success in terms of data accuracy when a person is involved to catch and flag potential errors. This process has been refined over years of testing within our platform, allowing customers to rely on AI outputs with added confidence. Additionally, our approach includes high-quality, diverse datasets for model training, real-time monitoring, and continuous feedback loops from customers to adjust models based on actual interactions, ensuring they stay aligned with evolving business needs.
AB: How do you plan to support your AP clients if/when an AI skills gap exists?
JT: Our goal is to make AI accessible to AP teams without the need for deep technical expertise. We provide intuitive, user-friendly solutions that have AI capabilities built-in, so clients can leverage advanced technology without needing data science backgrounds. AI is constantly learning from our customers’ processes, becoming more accurate and efficient over time. For organizations that need additional support, we offer dedicated training sessions, educational resources, and ongoing customer support to bridge any skills gap. As AI becomes more widespread, we’re committed to equipping our clients with the knowledge and tools they need to succeed.
AB: Where do you see AI going within the ePayables (AP automation) market over the next five years?
JT: Over the next five years, AI will become integral to AP automation, moving from a “nice-to-have” feature to a core component of efficient operations. We’ll see more advanced predictive analytics for optimizing payment strategies, enhanced fraud detection systems, and near-complete automation of invoice processing. AI will also likely drive the creation of more personalized and intelligent dashboards that offer real-time insights into AP performance. The goal is for AP teams to spend less time on manual tasks and more on strategic decision-making, enabled by AI-driven insights.
AB: I appreciate your time today!
JT: Thank you.
