Artificial Intelligence in Project Management

Artificial intelligence is still rarely used in project management because many stakeholders are not aware of the specific use cases and benefits and have not yet developed a strategy. By using AI, you can identify potential project delays early, manage resources efficiently, and make evidence-based decisions.

Project management is usually characterized by high complexity and routine work.

Artificial intelligences (algorithms) have the potential to decisively relieve project management at these points. For example, by adjusting and optimizing project plans due to delays, capacity bottlenecks or other elements of risk management.

The ability to analyze large amounts of data in a fraction of a second and at the same time draw on empirical values characterizes the potential of an AI. Since the use of AI frees up capacities in project management, these can be used elsewhere in a more value-adding manner.

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Marc Bollmann

Marc Bollmann
Senior Consultant

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Project management is usually characterized by high complexity and routine work.

Artificial intelligences (algorithms) have the potential to decisively relieve project management at these points. For example, by adjusting and optimizing project plans due to delays, capacity bottlenecks or other elements of risk management.

The ability to analyze large amounts of data in a fraction of a second and at the same time draw on empirical values characterizes the potential of an AI. Since the use of AI frees up capacities in project management, these can be used elsewhere in a more value-adding manner.

Your contact

Marc Bollmann

Marc Bollmann
Senior Consultant

Get in touch

Manage your projects in a targeted manner by automating routine tasks and efficiently analyzing complex data sets.

Use the potential of automation for recurring tasks and focus on your strategic project management

AI is best suited for handling repetitive and time-consuming tasks and the rapid analysis of complex data sets. Optimizing your project management by using AI or machine learning requires that a clearly defined use case is determined. With the “AI Use Case Analysis”, INVENSITY has developed an effective method to support you in this central issue.

Possible areas of application are in effort estimation, schedule creation, resource allocation or in project reporting or risk management.

We would be happy to inform you in a personal meeting about the possibilities of artificial intelligence.

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Get in touch now
Learn more about our AI use case and download our OnePager for free.

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Download OnePager (DE)

AI is best suited for handling repetitive and time-consuming tasks and the rapid analysis of complex data sets. Optimizing your project management by using AI or machine learning requires that a clearly defined use case is determined. With the “AI Use Case Analysis”, INVENSITY has developed an effective method to support you in this central issue.

Possible areas of application are in effort estimation, schedule creation, resource allocation or in project reporting or risk management.

We would be happy to inform you in a personal meeting about the possibilities of artificial intelligence.

.

Get in touch now
Learn more about our AI use case and download our OnePager for free.

.

Download OnePager (DE)

Use Case

Basic Step: Create a cleansed and unified database tailored to your projects and needs

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AI systems depend on being supplied with adequate data. The greater the amount and quality of data, the more reliable the predictions. We help you collect and prepare your data from previous projects so that it can be used by an AI. The result is a cleansed and unified database tailored to your projects.

Example: Using AI to estimate the effort of your work packages.

Based on your individual use case, an AI prototype can be developed and implemented step by step. A selection of algorithms of different methods, represent the basis of the development. For example, an AI system for effort estimation could look like the one shown below.

The starting point is the cleansed database that contains, among other things, information from effort estimates of your past projects. A machine learning AI prototype is developed and trained. 80% of the total data is used for development and training. An algorithmic reward system is used to iteratively improve the accuracy of the estimates until there is very little variance between estimated effort and actual effort. The remaining 10% of the data, which is previously unknown to the bot, is used to confirm the performance of the prototypes.

Do you have questions about Project Management, or are you considering hiring external support?

Please feel free to contact me at any time. Click on the button below and easily choose a time slot so that we can discuss your project without obligation and free of charge.

Schedule appointment

Simon Stieber
Head of Project Management

Do you have questions about Project Management, or are you considering hiring external support?

Please feel free to contact me at any time. Click on the button below and easily choose a time slot so that we can discuss your project without obligation and free of charge.

Schedule appointment

Simon Stieber
Head of Project Management