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Hot Deals, Cool Tech: AI-Powered, Automated Due Diligence for Enhancing M&A Decision-Making

Artificial intelligence (AI)-driven data analytics and robotic process automation (RPA) can streamline document analysis, risk assessment and data extraction.

AI-powered Automated MandA Due Diligence Intralinks

In 2011, Hewlett-Packard (HP) made headlines with its USD 11 billion acquisition of Autonomy, a U.K.-based software firm. However, the excitement quickly soured as HP reported a USD 8.8 billion impairment charge just a year later.

Allegations surfaced that Autonomy had manipulated its financial performance prior to the acquisition, painting a misleading picture of its health and value. This debacle underscored the importance of thorough due diligence in M&A transactions.

Fast forward to late 2023, when Intercontinental Exchange achieved a milestone in the financial industry with its nearly USD 12 billion acquisition of Black Knight. Yet, this acquisition presented its own set of challenges, notably in navigating complex financial and legal structures. While it’s too early to gauge the success of this deal, it prompts a re-evaluation of traditional due diligence practices.

To address the shortcomings highlighted by HP’s Autonomy acquisition and better navigate deals like Black Knight, a modernized approach to due diligence is needed. This entails leveraging advanced technologies such as AI and data analytics.

AI-powered data analytics tools offer predictive capabilities, analyzing historical data to forecast future performance and identify risks. Real-time analysis facilitates prompt decision-making, which is critical in the fast-paced M&A landscape. Moreover, AI algorithms can uncover hidden patterns and anomalies, detecting irregularities in financial statements or deviations from industry benchmarks.

RPA streamlines repetitive tasks like document retrieval, data extraction and financial modeling, reducing manual errors and expediting the due diligence process. By automating workflow processes, RPA ensures tasks are assigned efficiently and deadlines are met, enhancing collaboration.

Had HP employed even the earliest iterations of these modern technologies during the Autonomy acquisition, they could have conducted a more comprehensive examination of Autonomy’s financial health and contractual obligations. Predictive analytics might have assisted HP in recognizing risks, irregularities and patterns that could have signaled financial statement discrepancies within the company.

Technology: a complement to human judgment, not a replacement

These technologies could have also been utilized to create automated systems for real-time monitoring of financial data within Autonomy, potentially identifying any financial red flags. AI algorithms could also have been employed to navigate through vast amounts of data to uncover financial misconduct or, alternatively, to identify legal and compliance risks by automatically analyzing legal documents. Meanwhile, RPA could have automated the collection of financial data, reduced the risk of human error and expedited the due diligence process, mitigating the risk of oversight.

Similarly, in the case of Black Knight, AI-driven data analytics and RPA could have streamlined document analysis, risk assessment and data extraction. Black Knight was a large target with a complex web of financial instruments, contracts and regulatory obligations.

When they automate the due diligence process, acquirers achieve faster, more accurate analysis as compared to traditional due diligence methods. They can also incorporate real-time, data-driven insights to inform their strategy.

In the context of the Black Knight acquisition, this could mean automating the review of financial statements, legal contracts and other critical documents. AI-driven data analytics tools can highlight areas of concern or opportunity that may have gone unnoticed during a manual review. By employing such technologies, firms can free up resources for critical tasks that can’t yet be fully automated.

However, while these technologies offer significant advantages, they also pose risks. The accuracy and reliability of insights depends on the quality of input data, and AI algorithms may inherit biases from their training data.

Ethical and privacy concerns may also arise from the collection of sensitive information. The growing dependence on technology raises concerns regarding the confidentiality and safety of sensitive financial and legal information. Although automation simplifies processes, human supervision is still essential to address subtle details that automated systems might miss.

Lastly, the use of such technologies increases vulnerability to cyberattacks, potentially leading to data breaches and unauthorized access to sensitive information. Cyber threats loom large in an increasingly digital landscape, and therefore robust firewalls need to be maintained.

It’s crucial to view technology as a complement to human judgment, not a replacement. Human oversight ensures nuanced details are addressed and a comprehensive understanding of due diligence outcomes is achieved.


A balanced approach, combining technology with strategic human involvement, is essential for effective due diligence in today’s M&A landscape. Plus, it is the humans who will still train the AI systems and determine which questions — and follow-up questions — need to be asked.

The failures of HP’s Autonomy acquisition and the complexities of deals like Black Knight underscore the need for a modernized approach to due diligence. By harnessing the power of AI, data analytics and RPA, businesses can navigate deals more effectively, mitigating risks and maximizing opportunities.

The use of automated technologies in M&A must be accompanied by rigorous oversight, attention to data quality, and a strategic blend of human judgment and technological innovation. That is the recommended mix for conducting acquisitions to come.

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Paulina Roszkowska Bayes Business School
Robin Gurschek
Michele Slomp University of Bologna