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Artificial intelligence in M&A transactions - Impacts on the due diligence process

Artificial intelligence (AI) is also increasingly being used in corporate transactions. In the following section we discuss the possible uses, opportunities and risks in the due diligence process.


The M&A industry is on the verge of a revolution - the use of AI could radically change the due diligence process. In the past, very many human resources were needed for data analysis. However, highly efficient AI algorithms could help to process large volumes of data in the shortest time.

By using AI in the context of due diligence, consultants will be able to identify potential risks and opportunities more quickly and precisely. AI systems can provide support for comprehensive analyses as well as for reviewing contracts and legal requirements. 

As a result, the efficiency of the due diligence will be enhanced. 

Please note: Despite all the advantages there are nevertheless challenges and potential risks associated with the use of AI in due diligence. It is important to understand these and to put appropriate arrangements into place in order to still be able to ensure both the integrity and confidentiality of the data as well as the quality of the advice.

Fields of application for the buy side and the sell side

Virtual data rooms constitute a basic technology for the application of AI in due diligence processes. A virtual data room is where documents and data are made available by the sell side to the buy side.

If AI or a data analysis function is included in these data rooms then this allows the buy side to create a more automated due diligence process. Some examples here are the AI-assisted recognition of patterns and inconsistencies in annual financial statements, or the identification of contract durations and notice periods in rental and employment agreements.

Another field of application in the context of virtual data rooms for cross-border transactions is AI-assisted document translation. In this case, data room users are able to display document contents in their preferred language. 

Please note: This has the added advantage that none of the contents are entered into separate translation tools outside of the data room and thus no sensitive information is uploaded to the internet.

Besides due diligence activities on the buy side, the application of AI in virtual data rooms on the sell side can moreover be used, among other things, to automatically categorise documents and allocate them to the corresponding index reference points. All parties could thus benefit from the application of AI in virtual data rooms and reduce their respective manual workloads (cf. summarised in Table 2).

Potential risks and limits

The use of AI will have particular benefits when large volumes of data are supposed to be processed. 

Risks could however arise for data protection reasons, for example, if AI models are trained using personal data. Here, care should always be taken to ensure that companies or the data room providers who offer AI systems comply with the data protection regulations and safeguard personal data. 

A substantial limitation of AI is moreover its lack of ability to contextualize. While AI algorithms can identify patterns and relationships in the analysed data, yet they do not fully understand the context. This can lead to faulty results in the case of automatic evaluation. In this regard, human expertise and experience within the scope of due diligence are still vital for interpreting the results of the AI analysis and for drawing conclusions from it.

Conclusion: The combination of human and machine as the key to success

Decisions taken by humans are often prone to error and could be based on prejudice. This can notably be observed with regard to decisions that seem complex and are time critical and marked by uncertainty. 

The use of AI in the context of the due diligence process can however help to minimise such sources of errors and thus also to provide for more neutrality and transparency. Furthermore, with AI the increasing complexity of dealing with large data sets and data structures can be reduced and time-critical processes can be accelerated. 

Although, AI is currently still coming up against its limits, notably in the area of the contextualisation of patterns and relationships in analysed data.  

Ultimately, the interplay between humans and machines in the due diligence process represents the crucial key to success.

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