Essentially through the application of General Systems Theory. There are a lot of mathematical patterns that are found throughout nature much like the "golden ratio" and the Fibonacci sequence, even though the places they are found have no obvious relationships such as cellular biology and finance.
A project may be unique but will have similarities to other projects so patterns in the training data may be evident in the new situation and whether they relate to a positive or negative outcome. A variety of other patterns in training data from seemingly dissimilar things may also be found in project even though it is unique like how the Fibonacci sequence found in flower petals is also found in stock market performance. AI may find project risks by evaluating the project for many different types of mathematical patterns that relate to undesirable outcomes. Generative AI may then propose recommendations for how to change the pattern for a more positive outcome.
Senior Projects Manager | Field & Marten AssociatesNew Westminster, British Columbia, Canada
Arunesh, to add to Keith's feedback, when we identify risks at the outset of the project, we do so for what whole project and all phases and put all risks in a risk register and keep monitoring them - I don't advise you 100% rely on AI to identify Risk Factors!
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1 reply by Arunesh Ghosh
Apr 30, 2024 8:53 PM
Arunesh Ghosh
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Hello Rami,
I understand that, it has to come from a various different sources to create a comprehensive list to cover all bases.
Saving Changes...
Omar JabbarProject Management and Digital Transformation Consultant| OGreen IT Service Inc.Ontario, Canada
I agree with Rami. However, it is crucial to adhere to standard risk management procedures, which involve proactive risk evaluation, risk mitigation planning and contingency planning. AI can help identify and assess risks and enhance mitigation and response plans. Nevertheless, external factors can alter the entire plan, which is why monitoring risks is a key factor in risk management. Saving Changes...
Essentially through the application of General Systems Theory. There are a lot of mathematical patterns that are found throughout nature much like the "golden ratio" and the Fibonacci sequence, even though the places they are found have no obvious relationships such as cellular biology and finance.
A project may be unique but will have similarities to other projects so patterns in the training data may be evident in the new situation and whether they relate to a positive or negative outcome. A variety of other patterns in training data from seemingly dissimilar things may also be found in project even though it is unique like how the Fibonacci sequence found in flower petals is also found in stock market performance. AI may find project risks by evaluating the project for many different types of mathematical patterns that relate to undesirable outcomes. Generative AI may then propose recommendations for how to change the pattern for a more positive outcome.
Arunesh, to add to Keith's feedback, when we identify risks at the outset of the project, we do so for what whole project and all phases and put all risks in a risk register and keep monitoring them - I don't advise you 100% rely on AI to identify Risk Factors!
Hello Rami,
I understand that, it has to come from a various different sources to create a comprehensive list to cover all bases. Saving Changes...
Sergio Luis ConteHelping to create solutions for everyone| Worldwide based OrganizationsBuenos Aires, Argentina
AI is a boarder term. AI is using in projects to support project management activities from more than 30 years ago. I guess you are talking about generative AI. The answer to your question is inside the 3 layers model proposed by the PMI. You can take a look to it including you will find two very useful courses delivered by the PMI for free. You will find lot of information created from long time ago in other sources too. Saving Changes...
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