Technology providers are increasingly focused on understanding the perspectives of equipment lenders and dealers to maximize the potential of artificial intelligence (AI) in financial services. A recent report from market research firm Statista revealed that nearly 70% of financial services firms experienced AI-driven revenue growth in 2024, with most reporting increases of 5% to 10%. AI investments in the sector reached approximately $45 billion this year, representing a significant rise of 28.6% compared to 2023.
As AI continues to transform the landscape of equipment finance, fintech companies are recognizing the importance of comprehensive insights from lenders to enhance new technological solutions. Shivi Sharma, co-founder and president of Kaaj.ai, a San Francisco-based fintech, emphasized the necessity of understanding lender challenges to maximize the effectiveness of AI-driven solutions. Kaaj.ai employs AI agents to automate and expedite small-business lending processes for equipment financiers and credit unions.
“We get a lot of lender perspectives on what their challenges are, what the bottlenecks are that they are facing in their operations,” Sharma said. “And then we build the products to address those challenges.” The company engages with hundreds of lenders annually, facilitating in-depth discussions about their workflows and the processes they wish to enhance.
Many small-business lenders are grappling with increased application volumes and the need for data-driven decision-making. Recognizing this, Kaaj developed a credit intelligence platform designed for end-to-end automation, capable of processing unstructured data to improve profitability amidst rising application numbers. “Most of the time they’re working on thin margins,” Sharma noted, highlighting the critical need for efficient solutions.
“That’s what we wanted to focus on,” she continued. “How do we build the right technology, right solution that really helps them analyze the data and provide intelligence so the burden on their teams reduces?”
The insights from equipment dealers are similarly shaping the development of AI tools that facilitate smoother interactions between lenders and end-users. For instance, loan automation software provider Northteq recently launched Aurora IDP, a platform that automates the extraction and verification of data from applications, invoices, and other documents. The initiative was informed by a survey conducted at the 2025 Associated Equipment Dealers conference, which identified “time to decision” as the primary challenge in dealer finance operations.
“That’s the main driver of why [dealers] would choose one lender over another,” said Kristian Dolan, Northteq’s Chief Executive. “So, if you start with what the vendors and dealers want, and then you work backwards from there, you’re like, ‘Well, those are the bottlenecks.’” Many dealers indicated that manual document processing significantly impeded financing decisions.
“Dealers want to be able to get financing easily,” Dolan explained. “They’re creating order forms. They’re creating invoices. So, if you can simply send over an invoice to a finance company, and the finance company can take that, extrapolate the equipment data, customer data and everything they need to get the credit application going, it just removes work for the vendor, makes their life easier.”
As these developments unfold, it is vital for fintechs to accurately assess the needs of lenders when gathering feedback. In the short term, many lenders express a preference for maintaining their existing systems rather than undergoing extensive replacements. “If they’re using Salesforce, what will the integration into Salesforce look like?” Sharma posed. “What kind of fields should be mapped? How do we address any concerns around maybe creating duplicates?”
Considerable effort is devoted to comprehending what will facilitate the adoption of new solutions with minimal disruption and retraining, as one of the significant challenges of implementing new technology is the need for staff retraining.
The trajectory of AI in equipment finance is indicative of a broader trend in the financial services sector, where enhancing operational efficiencies and improving decision-making processes are paramount. As fintechs and lenders continue to collaborate, the integration of advanced technologies like AI is likely to play a crucial role in shaping the future landscape of financial services.
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