AI is prevalent throughout modern business, primarily tasked with streamlining mundane and repetitive tasks to free up workers to focus on high-level cognitive tasks. But when machines are asked to flip from simple data entry processes to being involved in critical financial processes and decisions, stakeholders tend to get concerned with AI’s potential error rate.

AI in due diligence

AI error rates are a concern, particularly when it comes to due diligence where accuracy and reliability are critical. At Liquidity, we recognise that AI models can occasionally generate incorrect or incomplete outputs. To mitigate the risks, our R&D and data science teams follow strict processes and procedures that combine technology-enabled insights with human intelligence. 

“We view AI as an augmentation tool rather than a standalone decision-maker.”

– Oron Maymon, Co-Founder and Chief Science Officer 

Human oversight, layered verification and robust validation processes remain essential in ensuring data integrity and minimising risk. AI brings speed and scale to due diligence, but human judgement is still the final safeguard. 

AI tools to cut time and costs of due diligence

One of the key benefits of AI is its ability to process vast amounts of unstructured and structured data at scale and speed. Liquidity is actively exploring AI-powered tools to streamline parts of the DD process.

AI tools can streamline processes such as document analysis, financial data extraction, market benchmarking and risk flagging. 

“Leveraging these tools can significantly reduce the time and cost of routine tasks, allowing our analysts to focus on higher-level judgement, negotiation and decision-making,” says Maymon. 

Mitigating the liability risk of AI tools in due diligence

Mitigating the liability risk of AI’s inclusion in due diligence processes is a major consideration. Liability risk arises if AI-driven outputs are used without sufficient human validation. To address this, Liquidity approaches AI as a complementary resource rather than a replacement for traditional third‑party providers.

Third party validation continues to remain an essential part of the risk‑management process, especially in cases where legal, regulatory or reputational risks are high. 

“Our AI adoption strategy is focused on enhancing efficiency while maintaining accountability and risk controls. Trusted third-party validation and AI insights together provide our strongest risk defence.”

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