Volatile markets, complex transactions and increasing pressure on returns are forcing private equity investors to scrutinise potential investments even more thoroughly. AI provides transparency into the target company’s operations and highlights potential value creation opportunities.
More than 80% of the private equity professionals surveyed in our recent survey said that they already use AI regularly in due diligence or are testing its use. The debate has therefore shifted from whether to use AI to how it can support sound investment decisions and the identification of value creation potential – and how the associated risks can be adequately managed.
Where AI delivers tangible value
A due diligence requires large volumes of data from different areas of the business to be analysed – from legal and operational to commercial, financial and technological information. AI tools can process thousands of documents such as PDFs, spreadsheets, emails or images in a short space of time and extract the relevant content.
Knowledge graphs and data analytics make connections within extensive data sets visible. AI also facilitates cross-functional searches: a procurement team, for example, can pull up a relevant supplier contract within seconds.
In the due diligence phase, AI can contribute both to value creation and to value preservation. In our survey, 31% rated market and operational insights as the most successful AI use case; 26% cited forecasting models and scenario analyses. One in five respondents also referred to fraud and anomaly detection as well as the monitoring of regulatory requirements and compliance.
AI risks and human judgment
To use the benefits of AI responsibly, human oversight and clear accountability are required at the decisive points of every process step.
As large volumes of data are processed at speed, the bottleneck shifts to the quality and reliability of the results. Inadequate preparation, unsuitable prompts or an uncritical adoption of the outputs can create a flawed picture of the company and encourage poor financial or operational decisions.
Due diligence teams therefore need the technical know-how to use the tools properly, critical thinking skills as well as operational and industry-specific expertise. Ultimate responsibility remains with the human.
In complex transactions, data collection is only part of the task. Equally important are the identification of hidden risks, the development of value creation plans and detailed analyses. Expert teams must assess the quality of the AI results and identify patterns and dependencies across the various workstreams. Hands-on implementation experience remains indispensable.
Conclusion
AI expands the scope of due diligence, supports integrated reviews and provides valuable analyses for complex transactions. At the same time, the abundance of quickly available results underlines the importance of human oversight. Especially in critical situations, the judgment of experienced professionals matters more than ever.
About the author:
Till Prinz is a Managing Director in the Private Equity Performance Improvement practice of Alvarez & Marsal in Germany. He has many years of experience in operational performance improvement, turnaround projects and restructuring programmes. His focus is on the implementation of performance improvement programmes for private equity portfolio companies as well as on interim management.
Mr Prinz has advised clients from numerous industries, including retail, fashion, entertainment, manufacturing, packaging, machinery and plant engineering, steel, chemicals, marketing and telecommunications.
