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Provided that a post-merger integration process is very complex process involving a lot of accurate comunication skills, soft skills in general and a lot of human interactions, still there are some more “quantitative analysis and assessments” that are more or less common to different deals and that can be considered “routinary”. in this respect, what is the role of the AI that can be enivsage for the foreseeble future in the integration process (for instance in the financial integration)?
Sorting through large amounts of date during due diligence can certainly be one area. In addition AI can search through all available public date to bring attention to various risks not considered in the business plan. Also processes such as IT and financial reporting and management information system integration can also apply AI.
AI, can also ‘comb’ through any data that are similar to other acquisitions that have happened in the past and provide insight to what worked and what didn’t.
AI can be a very useful tool for financial integration of historical information. You have to be careful with regards to the accuracy and reliability of the data. Havin the right checks and balances in place can greatly benefit the financial integration. These checks and balances stretch beyond the finance world as the could impact other parts of the business, where assumptions are used in your financials.
I think it will be helpful in almost every area that doesn’t require soft skills. However accessing data and the accuracy of the current AI engines will be a challenge at least on the short term.
Agree with many of your sentiments above that AI will be helpful in gather and sorting data but when it comes to implementation, especially in the IT field, go old fashioned “hands on” is still in vogue —- for now.. 🙂
AI could be helpful in all of the technical routine tasks, from data consolidation and cleansing, to cost synergy indications, to compensation benchmarking and many more. While AI can provide valuable support in these quantitative and analytical aspects, it is important to recognize that human judgment, soft skills, and effective communication remain integral to successful post-merger integration. AI should be seen as a tool to enhance decision-making rather than a replacement for human expertise. Additionally, considerations such as data privacy, security, and ethical use of AI should be prioritized throughout the integration process.
There are some advanced AI tools now readily available that can assist in PMI activities. Finance is an obvious area in integration activities. While communication doesn’t seem like an obvious area, AI can be used to help craft messages and communication with the right prompts. This will only be beneficial from a time saving perspective if the detailed prompts are given with the foundation of the communication and objectives. Regardless, communication generated by AI tools will need to be vetted.
As there are enough comments on data and technical applications, I would actually suggest that generative AI has the ability to support efficient development of communications and early versions of integrated go-to-market resources. This is all very time consuming and requires a lot of thought, but since much good work has been done but either exists somewhere internally or in multiple places, generative AI could be instructed to address certain topics and content, then be edited by humans for the finer points, style, etc.
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