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Publicado em Feb. 21, 2024

How companies can measure results after the implementation of Artificial Intelligence?

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The integration of artificial intelligence (AI) tools into modern business practices is not just a trend, but a strategic necessity to improve efficiency, reduce costs and optimize resources.


As the technological landscape evolves, it becomes imperative for managers to not only understand the potential of these tools, but also know how to measure their real impact on daily operations.


At the heart of this integration is the mapping process, a preliminary phase that lays the foundation for further assessment.


Process mapping allows for a detailed analysis of the inner workings of a company, identifying where and how AI can be implemented to maximize benefits. This initial understanding is crucial as it provides a baseline against which progress can be measured.


A key aspect of AI adoption is the ability to quantify its impact. This is done by establishing clear indicators that reflect efficiency before and after implementing AI tools.


For example, reducing the number of hours required to complete a task and reducing the number of employees involved are tangible indications of process optimization. These indicators not only demonstrate human resource savings, but can also lead to a direct reduction in operating costs.


In addition to direct savings, adopting AI tools can result in indirect benefits, such as reducing the use of raw materials in manufacturing processes.


These indirect savings, although sometimes less obvious, are equally important to a company's financial and operational sustainability. Therefore, the indicators chosen should reflect a range of benefits, both tangible and intangible, to provide a comprehensive assessment of AI's impact.


AI adoption, therefore, requires a holistic approach that considers not only the immediate benefits but also the long-term impacts.


Managers must strive not only to choose the right tools, but also to establish continuous monitoring practices to evaluate and adjust AI strategies as necessary.


This dynamic approach is critical to ensuring companies remain agile and competitive in an ever-changing business environment.

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About the author

Robson Clemente Da Silva

Consultor de marketing e comunicação e pesquisar de IA

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