# Better AI Starts with Better Context _Published: 2026-10-23T10:00:00.000-04:00_ Evaluating AI in commercial lending? Look past the feature list to connectivity, adaptability, and explainability, with guidance from Gartner. _Many AI tools for commercial lending look strong in a demo. Here's what to check underneath: connectivity, adaptability, and explainability._ Business lending runs on **context. ** A single client can involve multiple entities and owners to verify, and a relationship may extend across different types of lending like C&I, CRE, construction, and even treasury services. Serving that client with the right quality and speed requires understanding all of it, including financial performance, existing exposure, covenants, collateral, and past decisions. **Experienced lenders know how to bring those pieces of context together.** As AI takes on more work across lending, that context becomes a part of the technology equation, too. AI is already handling intelligent document processing at intake, automating financial spreading, answering credit policy questions in natural language, monitoring covenants, and more. That's hours back from rekeying data, chasing documents, and answering status questions — hours your team can use to focus on growing relationships. But AI only works from the information it can reach. If that's one application, one document set, or one system, it makes its call in a silo, without the rest of the relationship or the wider book of business in view. A banker in that position would know to go looking for what's missing. An AI model often won't, and its output can look finished anyway. That can leave you with a weaker result than if a banker had done the work. AI does its best work for your people when it can see the whole relationship. That means looking _beneath_ the AI, to the context it draws from. ## Look Beyond AI Capabilities AI capabilities can seem easy to evaluate. What can a tool summarize? What can it automate, recommend, or monitor? That’s where most of the attention is going right now, and it makes quick-fix point solutions look strong in a demo. But a tool that can only see a portion of the relationship can only do half the job, and that’s hard to tell from evaluating the capability alone. Doing the whole job comes down to **what lending context is behind those capabilities**. In business lending, useful intelligence depends on access to the information that shapes the relationship: borrower and financial data, exposure, credit policy, documents, decision history, and the rest of the work happening across the credit lifecycle. That information has to come together somewhere. A **system of record** provides a reliable, current view of the borrower, the relationship, the credit history, and the decisions made. Depending on your technology environment, that record may be centered in a lending platform or assembled through connections across several systems. Not everything requires AI, and it's important to look at the current processes and be intentional about [what to automate, where an agent can help, and where a banker's judgment should lead.](https://www.ncino.com/blog/not-every-touchpoint-needs-an-agent) Wherever AI enters, its usefulness depends on what information it can access. **A system of record gives your people and the intelligence supporting them that shared context. ** A record like that has a lot of ground to cover. [Gartner’s Market Guide for Commercial Loan Origination Solutions](https://explore.ncino.com/gartner-guide/na) examines how the CLOS market is evolving and what banks should be considering as they evaluate modern lending tech. The guide maps commercial credit across the lifecycle, from client acquisition and application intake through underwriting, approval, booking, servicing, and loan management, with lending technology interacting across systems including core banking, CRM, and risk and compliance. Before asking what AI can do, look at what your lending technology actively records and makes available. Does your CLOS give you a reliable record of the borrower, the relationship, the credit history, and the decisions made? That could tell you what context your AI will have to work from. If that context is fragmented or incomplete, that’s a good place to start. ## What Makes Better Lending Context Possible Once you know what record your intelligence will work from, the next step is to examine how the lending technology sustains that record. A "complete" record is a moving target. The relationship itself is changing all the time, from borrower information to exposure, credit decisions, and risk signals. Plus, your institution may eventually have new products, workflows, data sources, policies, and AI roles. The technology behind that record has to be able to keep up. Gartner’s recommendations offer a helpful lens for evaluating. ### Can your system stay connected? Business lending already relies heavily on information and services that live in different places. The quality of the connections between those places determines how easily the information can come together. Gartner recommends looking at a platform’s prebuilt integrations and ecosystem, confirming its APIs follow industry standards, and examining the integration and orchestration layers behind them.  Strong connectivity gives your lending technology a clearer path to the information your people need, whether it comes from the core, the CRM, external data sources, or specialist services. ### Can your technology adapt with you? Business lending changes constantly. You may launch new products, respond to new requirements, adopt new tools, or adjust your current workflows. Gartner recommends prioritizing lending technology that has a componentized, modular architecture, making it easier to adjust to future change. Plus, you’d have the flexibility to choose capabilities and products that support your business goals and evolve as those goals change without overhauling the entire platform. Those design choices help your technology keep pace with how you work, so the context available to your people and your AI tools can keep pace, too. ### Can your team explain AI-supported work? As AI becomes a part of more lending tasks, you need visibility into how those capabilities are working within your processes. Gartner emphasizes that explainability and governance are important as AI-supported credit decisioning becomes more common. They recommend verifying model governance, transparency, and data security, and looking specifically for AI capabilities supported by governance frameworks and guardrails. Your institution is still responsible for how AI-supported decisions are used. You need to be able to see what informed an output and understand how it was reached so you can maintain appropriate oversight. ## What To Carry into Your Evaluation AI capabilities are spreading quickly across business lending. As Gartner notes, many CLOS vendors now offer similar technologies and features. It’s becoming harder to distinguish one offering from the next based on functionality alone. This makes it more important now to look beyond the feature list and understand what those capabilities are really built on. As you evaluate your options, think about: - What information the intelligence will have access to (borrower, relationship, credit, policy, etc.) - How well your lending platform connects to the different systems needed to keep that information current (the core, CRM, external data sources, etc.) - How easily you can change workflows, rules, and capabilities as your product and lending processes evolve - How clearly your team can see and explain what informed an AI-supported output and understand how it was reached The right fit will depend on how you lend, the systems you already have in place, and where you want to go next.  Give your people and the intelligence supporting them the lending context they need to work from, then build from there. That’s how AI can become a part of your strategy rather than another capability in the tech stack. Gartner’s Market Guide for Commercial Loan Origination Solutions takes a broader look at the vendor landscape, where the market is heading, and more considerations bank leaders can carry into their own evaluations. [Download the Gartner Market Guide for Commercial Loan Origination Solutions.](https://explore.ncino.com/gartner-guide/na) --- [View sitemap](https://www.ncino.com/api/markdown/sitemap)