Investigation made easy? How AI influences the due diligence process of mergers and acquisitions

dc.contributorAalto Universityen
dc.contributorAalto-yliopistofi
dc.contributor.advisorHelanummi-Cole, Heli
dc.contributor.authorLappi, Jatta
dc.contributor.departmentJohtamisen laitosfi
dc.contributor.schoolKauppakorkeakoulufi
dc.contributor.schoolSchool of Businessen
dc.date.accessioned2023-09-17T16:01:03Z
dc.date.available2023-09-17T16:01:03Z
dc.date.issued2023
dc.description.abstractAI has been hailed as the new gold of the future. Not only does it replace a human in a variety of areas such as production, health care and business, it can also perform tasks in these business fields exponentially faster than a human. While AI is growing, M&As are showing signs of fatigue: half of M&As fail to create any long-term value. One of the biggest reasons for a failed M&A is the lack of due diligence, which is the investigation of the target with the main goals of reducing deal risk and inspecting the capabilities of the organisation. This investigation is something that AI can assist with, as AI due diligence tools can work as documents readers, analysists and forecasters in the due diligence process. At the same time, employees are shown to feel less attached to their work after new technology has been introduced. Studying the reaction of employees to the introduction of AI in the organisation can be done through employee engagement, which is about an employee being present at work both physically and mentally. This research aims to understand how the use of AI due diligence tools influences organisations’ due diligence process of M&As. It especially focuses on how the process has changed because of AI tools. The second part of the study concentrates on how AI introduction has influenced employee engagement of employees who work in the due diligence process with AI. The results give more insight into how AI can be leveraged by organisations better and how employees are most likely to react to the change. The study was conducted by semi-structured interviews collected from 10 different experts working in the business and consulting fields. Eight of the interviewees work in legal due diligence and two in technical due diligence. The results of the study are varied: legal due diligence uses AI in the due diligence process mostly as a document reviewer, while in technical due diligence the influence of AI is still minimal. In some cases, AI due diligence tools influence the legal due diligence progress considerably, mainly because of efficiency gains and infrastructural benefits such as process management, transparency and overview purposes. At the same time, the boundaries in which the AI tools work are quite rigid, because of which accuracy, language and training problems were present. According to the study AI’s influence on employee engagement ranges from neutral to considerable, as employees felt excited about AI, got to do more interesting work and to try new things. Some were still apprehensive about AI use because of limited time resources for learning to use the tool and because of understanding the limited capabilities the AI has. AI has influence on three aspects of an organisation: organisational, cultural and technical. Because of this large area of influence AI has an enhancing factor on due diligence, which in the future can result in better executed M&As.en
dc.format.extent74+17
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/123537
dc.identifier.urnURN:NBN:fi:aalto-202309175894
dc.language.isoenen
dc.locationP1 Ifi
dc.programmeManagement and International Business (MIB)en
dc.subject.keywordartificial Intelligenceen
dc.subject.keyworddue diligenceen
dc.subject.keywordmergers and acquisitionsen
dc.subject.keywordemployee engagementen
dc.titleInvestigation made easy? How AI influences the due diligence process of mergers and acquisitionsen
dc.titleHuolellisuuden helpottuminen: tekoälyn vaikutus yritysjärjestelyissäfi
dc.typeG2 Pro gradu, diplomityöfi
dc.type.ontasotMaster's thesisen
dc.type.ontasotMaisterin opinnäytefi
local.aalto.electroniconlyyes
local.aalto.openaccessyes

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