1 / 12

The 6 Best AI Technologies revolutionizing Project Management

AI (artificial intelligence) is making a new buzz in the technology industry. It is regarded as a new future and its impact on society and our work culture. AI projects are on the rise and they are going to make organizations take smarter and faster decisions. This brings to light AI project management and the technologies associated to be explored.

Dharanarola
Télécharger la présentation

The 6 Best AI Technologies revolutionizing Project Management

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 6 Best AI Technologies revolutionizing Project Management

  2. 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.

  3. 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).

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Conclusion - Narola Is a Top Artificial Intelligence (Ai) Company with Expertise in Machine Learning & Natural Language Processing. Offering Cutting-Edge Ai Development Services in USA, India. Email: info@narola.email Contact number: +1 (650) 209-8400 Website: https://www.narolainfotech.com/ai-artificial-intelligence-company

  12. Thank You

More Related