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Adopting Copilot for Businesses

Authors: Valabh, Helder Harshil;

Adopting Copilot for Businesses

Abstract

A inteligência artificial (IA) tornou-se uma ferramenta crucial na transformação da produtividade no local de trabalho, sendo o Copilot um exemplo claro desta mudança ao automatizar tarefas repetitivas e melhorar a eficiência dos fluxos de trabalho. Esta dissertação explora a adoção e o impacto do Microsoft Copilot em ambientes empresariais, com foco na integração, nos desafios e nas dificuldades associados. O Microsoft Copilot é um assistente baseado em IA que melhora a produtividade ao tirar partido de modelos avançados de linguagem natural, incluindo o GPT-4, e ao integrar-se com o Microsoft Graph para fornecer informações contextuais com base em dados organizacionais. O Copilot foi criado para aumentar a produtividade, simplificar os processos de trabalho e permitir que as organizações aproveitem melhor os dados que já possuem, através da automatização de tarefas e da geração de insights orientados por IA. Com base na documentação oficial da Microsoft, este estudo analisa de que forma o Copilot responde às necessidades específicas das empresas, enquanto aborda desafios como a formação da força de trabalho, os obstáculos à implementação e as preocupações com a privacidade dos dados. O objetivo desta dissertação é fornecer recomendações práticas bem como uma breve observação para empresas que pretendem adotar ferramentas de IA como o Microsoft Copilot, ajudando-as a ultrapassar desafios e a maximizar o seu valor para o negócio. Para além disso, esta investigação oferece um contributo relevante tanto para o meio académico como para a prática empresarial, ao apresentar uma análise do impacto destas tecnologias. O estudo pretende ainda apoiar técnicos e estudantes na compreensão das implicações da IA e do seu papel na transformação digital das organizações.

Artificial intelligence (AI) has become a critical tool for transforming workplace productivity, and Copilot exemplifies this shift by automating repetitive tasks and improving workflow efficiency. This thesis explores the adoption and impact of Microsoft Copilot in enterprise environments, where the focus is on integration, challenges and difficulties. Microsoft Copilot is an AI assistant that enhances productivity by leveraging advanced Large Language Models, including GPT-4, and integrating with Microsoft Graph to provide context-aware insights using organizational data. Copilot is designed to boost productivity, streamline workflows, and enable organizations to make better use of their existing data by providing AI-driven insights and automating tasks. Using insights from official Microsoft documentation, this study analyzes how Copilot supports enterprise-specific needs while addressing challenges such as workforce training, implementation barriers, and data privacy concerns. The objective of this thesis is to provide practical recommendations for companies looking to adopt AI tools like Microsoft Copilot, helping them overcome challenges and maximize their business value. Additionally, this research contributes both academically and to business practices by offering an analysis of the impact of these technologies. The study aims to support technicians and students in understanding the implications of AI and its role in the digital transformation of organizations.

Country
Portugal
Keywords

Microsoft Copilot, LLM, Machine Learning, Generative AI, Copilot Microsoft 365, AI Training

  • BIP!
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green