While the AI lease abstraction tools currently on the market—such as Docsumo, LeaseLens, Kira Systems, Imprima, Prophia, Lease cake, and Summize—offer advanced features and automation, they still fall short in one critical area: the absence of a human in the loop.

Here’s why this lack of human oversight can be a significant drawback:

1. Limited Contextual Understanding
AI tools excel at extracting data from lease agreements based on pre-set templates and algorithms, but they lack the nuanced understanding that human professionals bring to the table. Legal documents, especially leases, often contain complex clauses that require interpretation and judgment, which AI models can misinterpret. For example, ambiguous phrases, outdated legal jargon, or region-specific regulations might be overlooked or misunderstood by AI systems.

2. Handling Complex Scenarios
When leases involve intricate terms, such as escalation clauses, renewal options, or unique tenant-landlord agreements, AI tools may not always provide accurate abstraction. In such cases, having a human in the loop ensures that these clauses are interpreted correctly, minimizing the risk of errors or omissions. Without human oversight, AI tools might overlook important subtleties, which could lead to costly mistakes or compliance issues.

3. Custom Adaptation
AI lease abstraction tools are primarily driven by pre-defined rules and machine learning models that are trained on large datasets. However, every lease document is unique, and these tools might struggle with non-standardized language or documents that deviate from the norm. Human professionals can adapt to such cases and apply judgment that is impossible for AI systems to replicate. In contrast, AI tools, when left entirely on their own, may not adapt well to unusual lease formats or unique conditions without custom configuration.

4. Ensuring Compliance
AI tools can identify non-compliant clauses or provisions to some extent, but regulatory and legal frameworks are constantly evolving. Human involvement ensures that all abstracted data complies with the latest legal standards and industry regulations. Relying solely on AI could expose a company to legal risks, especially in complex or high-stakes leases.

5. Quality Control and Error Handling
Even the most advanced AI systems can produce errors, especially when dealing with varied lease structures. A human in the loop serves as an essential quality control checkpoint to catch mistakes that might slip through AI processes. Having human review mitigates the risk of AI-generated errors propagating through a company’s workflow and causing downstream issues.

6. Custom Client Requirements
Every client or real estate firm may have specific requirements that AI tools cannot automatically understand or cater to without human intervention. For example, certain clients may prioritize specific data points or need specialized reporting formats. Without a human operator to adapt and adjust, AI tools may fail to deliver customized results that meet each client’s unique expectations.