The leasing sector has historically taken a cautious approach to new technology, but artificial intelligence is redefining the terms of engagement. With client expectations rising and tech-led entrants reshaping the market, firms that delay adoption risk operational inefficiency, compliance gaps and declining relevance. Nivo’s Matthew Elliott explains why now is the moment to act.
The leasing industry has always been good at waiting. Waiting for the right deal, the right market conditions, the right technology to prove itself. But, when it comes to AI, that waiting game might be costing more than companies realise; the question isn’t whether AI will eventually find its way into leasing, it’s when. It’s why smart operators are moving now, while others are still sitting on the sidelines.
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The timing couldn’t be more critical. A unique combination of market pressures, technology maturity, and competitive dynamics has created a window where early AI adoption delivers outsized advantages. Miss this window, and you’re not just behind; you’re playing catch-up in a market that doesn’t wait for stragglers.
Market forces
Let’s be honest about what’s happening in leasing right now. Client expectations have shifted dramatically. The same business owners who expect instant everything in their personal lives don’t suddenly develop patience when they need equipment financing. They want quick decisions, transparent processes, and seamless experiences. Traditional leasing workflows, built around manual processes and phone tag communication, increasingly feel clunky by comparison.
Meanwhile, competition is intensifying from unexpected directions. Companies with AI-first approaches are entering the market, offering faster approvals and slicker experiences. They might not have decades of leasing expertise, but they’re proving that speed and efficiency can sometimes trump relationship history. Traditional leasing companies risk being outmanoeuvred by operators who understand technology better than equipment.
Regulatory pressures add another layer of urgency. Compliance requirements continue to expand, documentation standards are tightening, and the need for transparent, auditable decision-making processes has never been greater. Manual compliance tracking isn’t just inefficient anymore. It’s a liability waiting to happen.
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By GlobalDataWhere AI delivers value
Let’s start with what AI actually does well in leasing. The technology excels at handling the repetitive, data-heavy processes that currently consume significant time and resources. Document processing, credit assessment automation, and application routing are areas where AI doesn’t just match human performance, it exceeds it.
Take document intelligence. Instead of operations teams spending hours extracting data from financial statements, lease schedules, and bank records, AI can process these documents in minutes while maintaining higher accuracy rates. This isn’t about replacing human judgment, but about freeing up skilled professionals to focus on complex deal structuring and relationship management, allowing you to grow your business without hiring additional staff.
Similarly, AI-powered application routing can match deals to appropriate funders based on appetite, criteria, and historical success rates. What currently requires broker expertise and multiple phone calls can happen automatically, improving both speed and matching quality. Once again, growth without hiring.
For portfolio monitoring, AI never sleeps. It can track payment patterns, flag potential issues, and identify opportunities for additional business, providing early warning systems that human oversight might miss simply due to volume constraints. Seeing a pattern? Less admin, more deals, growth.
Technology at the fore
Here’s what’s changed in the past two years: AI tools have moved from experimental to genuinely practical. The document processing that used to require custom machine learning models and teams of data scientists can now be implemented with commercial solutions that integrate with existing systems. The technology has reached the sweet spot where it’s sophisticated enough to handle real complexity but simple enough to actually deploy.
Cloud infrastructure has matured to the point where even smaller leasing companies can access enterprise-grade AI capabilities without massive upfront investments. Security concerns that once made AI adoption unthinkable have been addressed through improved encryption, better access controls, and compliance frameworks designed for financial services.
Most importantly, the AI tools being deployed today are designed for augmentation, not replacement. They enhance human decision-making rather than bypassing exactly what leasing companies need to maintain their relationship-focused approach while gaining operational efficiency.
AI-enabled competitors
Early adopters in leasing are already seeing the benefits. They’re processing applications faster, reducing back-office costs, and taking on more volume without proportional staff increases. More crucially, they’re delivering client experiences that feel more responsive and professional than traditional approaches.
This creates a compounding advantage. Better service leads to more referrals, operational efficiency enables competitive pricing, and faster processing captures time-sensitive deals that might otherwise go elsewhere. Companies that implement AI effectively don’t just improve their operations. They reset client expectations for what good service looks like.
Meanwhile, the cost of waiting continues to rise. As AI-enabled competitors establish market positions, traditional operators face the choice between expensive catch-up implementations or gradual market share erosion.
Capability building
The beauty of AI adoption in leasing is that it doesn’t require wholesale transformation from day one. Companies can begin with targeted applications like document processing, application routing, portfolio monitoring and expand as confidence and capability build. The key is starting while the competitive advantage is still available.
The leasing companies that will dominate the next decade won’t necessarily be the biggest or oldest. They’ll be the ones who recognised the “why now” moment and acted on it while others were still debating whether AI was ready for their industry.
The technology is ready. The market is demanding it. The only question left is whether you’ll be leading the change or reacting to it.
Matthew Elliott is co-founder & CDO of Nivo
