Application of artificial intelligence (AI) in project management
Application of artificial intelligence (AI) in project management - infoweb24.com

Application of artificial intelligence (AI) in project management

Application of artificial intelligence (AI) in project management

artificial intelligence in project management – Artificial Intelligence (AI) is a term that has been the subject of much debate since its birth in 1956. From information technology to finance, artificial intelligence has affected all industries and related businesses. While some are skeptical of the effects of artificial intelligence, others see it as a major development. It is also expected to have a major impact on project management principles in the coming years.

According to the PMBOK guide, there are five different stages in project management:

  • Beginning
  • planning
  • Performance
  • Monitoring and control
  • to close

The ability to interpret artificial intelligence data can provide real insights into project metrics. This system can enable project managers to make data-based decisions based on past experience. Cap Gemini, for example, uses the IBM Watson Cognitive Computing System to improve resource deployment in projects through efficient resource planning.

In this article, we will talk about the different ways that artificial intelligence can help manage a project.
The importance of artificial intelligence in project planning.

Application of artificial intelligence (AI) in project management
Application of artificial intelligence (AI) in project management – infoweb24.com

A project consists of a set of tasks designed to achieve a specific goal. A project can be developing a new product or service, building a bridge or building, renovating a home, updating a data system, running a new business, and so on.

Artificial intelligence (AI) in project management:

Regardless of the nature and size of the task, each project manager tries to meet the goals of the project, ie its delivery within the specified time and budget. Effective project planning paves the way for its success.

Project planning is one of the basic components of project management. Determines the scope of the project and the goals to achieve them. The project plan includes how the project will be implemented, monitored, controlled, and closed. The plan should include any project constraints, including costs, risks, resources, and deadlines. The project plan consists of six basic stages:

  • Create to-do lists
  • Forming a budget plan
  • Prepare a risk management plan
  • Generate a communication plan
  • Prepare a project schedule
  • Allocate appropriate resources for appropriate tasks

Artificial intelligence tools help project managers perform a variety of tasks at each stage of the project planning process. It also enables project managers to process complex project data and discover patterns that may affect project delivery. Artificial intelligence also automates most redundant tasks, thus increasing employee interaction and productivity.

According to Gartner, artificial intelligence will eliminate 80% of today’s project management craft by 2030. Artificial intelligence machines take care of everything from programming to data collection, tracking to reporting, and more.

Artificial intelligence in project management

From scheduling to analyzing teamwork patterns, AI has become an obvious advantage for project managers.

Here are some AI applications that help the project management cycle:

Expert Knowledge-Based Systems (KBS System)

A knowledge-based expert system is a computer program that demonstrates the analytical knowledge and skills of one or more humanities specialists on a particular problem. The system records the human expert experience and encodes it on a computer so that any user can understand it.

Here you can see the KBES architecture diagram.

The knowledge engineer or human specialist provides the information to KBES. This information is often declarative, for example, the expert states some facts, rules, or relationships in the knowledge base. The inference engine then uses the knowledge database as a data file to determine knowledge and provide output.

In most cases, professionals use IF-THEN rules to enter knowledge. The if-then rule is as follows:

If <conditions>, then <solution>

The solution is limited and determined depending on the rules that enter the system. For example,

“If a mammal stands on two legs and dresses, then it is a human.”

Here, “two legs” and “dressed” are the conditions, and based on this knowledge, KBES can identify the solution as “a human being”.

Knowledge-based systems work in several applications. Here is a list of KBES programs:

  • Classification: The network identifies an object based on the listed properties.
  • Detection: KBES infers any malfunctions from the data.
  • Monitoring: This system compares data from a previous system to predict patterns.
  • Planning: KBES develops or modifies a project based on the project.
  • In the medical field, for example, KBES helps physicians better diagnose diseases. KBES is also used in industrial equipment troubleshooting, avalanche path analysis, and cash management.

Another example of KBES is the Presence Recording System (ACRS). This automated system saves both managers and employees. This system reduces errors and prevents disputes by removing the manual record. ACRS has several benefits, including:

  • Personal information of employees
  • Faster information retrieval
  • Easy production and review of reports
  • Full database backup
  • Special permits and security levels for employees

 

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