The 6 Best AI Technologies revolutionizing Project Management

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6 Best AI Technologies revolutionizing Project
Management

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What is AI Project Management?

• The AI project management is a system that
  performs day to day administration activities
  without any human interference. It helps to
  automate the work while developing an
  understanding of key project performance to
  uncover project insights, in simplifying complex
  projects, and to make decisions.

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Top AI technologies which are impacting project
management

• Though AI technologies might sound like a new
  thing, for a long time, we are already relying on
  this (remember Google home, SIRI, Alexa).

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KNOWLEDGE-BASED SYSTEM (KBS) -

• According to a report, in the upcoming years, the
  impact of knowledge-based systems on
  organizations is about to jump from 37 to 71.
  The knowledge-based system understands the
  context of issues and provides insights to make a
  better decision. Here Natural language processing
  and machine learning algorithms help management
  to create accurate development planning. As an
  example, in the medical field, KBS helps to
  diagnose the right issues based on provided
  information and symptoms.

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MACHINE LEARNING -

• Although Machine learning is in the initial stage
  to help in the project stage, it has been
  considered as the next step up from KBS. With a
  little human interference, it analyzes the data
  to speed up the project. We can take an example
  of Netflix, which predicts exactly what you like
  based on your browsing pattern and makes an
  accurate prediction as it learns. While 31 of
  organizations are already impacted by machine
  learning, 69 say that in the coming few years,
  it will affect them too.

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DECISION MANAGEMENT -

• AI plays an important role to make crucial
  decisions. In, decision management is an
  automated set of rules to create an automated
  decision. As per a survey, 29 of organizations
  are already affected by decision management,
  while 68 are expecting a moderate future
  impact. In AI project management, it can be
  related to resources such as taking a decision to
  assign the task, etc., based on a few sets of
  rules. It is also when machine learning
  algorithms work to show the features of the
  product and uses by a consumer and help project
  managers to make decisions accordingly.

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EXPERT SYSTEM -

• It simulates human intelligence to solve any
  particular problems and provide project managers
  with expert thinking. Many organizations are
  already impacted by the expert system, and many
  more are expecting a moderate future impact. The
  ES helps to interpret accurately, predicts,
  repairs, and monitors system behaviors by looking
  at the expert decision pattern and drawing an
  insight to provide management with expertise.

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DEEP LEARNING -

• Deep learning helps to train, build, and test
  neural networks based on probabilities to predict
  outcomes. In a neural network, there are three
  types of layers of neurons the Input Layer, the
  Hidden Layer(s), and the Output Layer. Also, in
  AI technologies, self-driving cars are an example
  of deep learning that has been taught to detect
  signs, humans, other vehicles, etc. Deep learning
  is good at detecting objects, recognizing speech,
  translating languages, that help in making
  correct decisions.

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ROBOTIC PROCESS AUTOMATION (RPA)

• The robotic process automation imitates and
  automates corporate tasks to support all
  organizational processes. It is also one of the
  first technologies to support project managers,
  and many more advancements could be anticipated
  in this in the future. It has been considered as
  a gateway for AI. We can take payroll processing,
  invoicing, or handling customer inquiries as an
  example of robotic process automation.

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Conclusion

• In the coming years, artificial intelligence and
  Machine learning will continue to grow a lot.
  Organizations should opt for AI technologies to
  pull details from multiple sources, to get deeper
  opportunities, for efficient and detailed project
  planning, for better decision making, and
  accurate result predictions.

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Conclusion -

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