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Do you think that AI could help with Risk Management?

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Laura Lazzerini
Community Champion
Head of International Project Management Office| Deutsche Telekom Praha, Czechia
I would see risk management as one of these areas where the seniority of a project manager is more recognisable. Do you think that AI could help or support the project manager in Risk Management. If yes, which tools are you using?
 
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Sergio Luis Conte Helping to create solutions for everyone| Worldwide based Organizations Buenos Aires, Argentina
AI is in use in things like Risk Management from long time ago. Almost 30 years ago. While both are focused on generative AI my recommendation is taking a closer look to both courses published for free by the PMI, In fact, you will find a list of tools inside them.
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1 reply by Laura Lazzerini
Jun 02, 2024 7:13 AM
Laura Lazzerini
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I absolutely agree with you. The two courses offered by PMI and also the whitepapers and other resources created by PMI are highly useful and give very interesting hints on several aspects.
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Md. Golam Rob Talukdar
Community Champion
Project Manager| AWR Development (BD) Ltd. Cox's Bazer , Bangladesh
Jira
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Rami Kaibni
Community Champion
Senior Projects Manager | Field & Marten Associates New Westminster, British Columbia, Canada

Laura, AI can definitely supports PMs in Risk Management by analyzing large data and providing predictive insights for PM to make informed decisions.

Oracle Primavera uses AI for Risk Analysis and Project Planning!

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Keith Novak Tukwila, Wa, United States
There are a lot of ways AI can support risk management. The question is what problem you are trying to address and whether AI is the right solution for the application.

LLMs can help compare your project to case studies to identify common issues. I think AI has the best potential yet for making documented lessons learned actually of some real value.

Image recognition algorithms are already used in various applications to detect potential threats. Is there a risk on the project which could be detected visually if there were cameras and/or radars monitoring some important work area?

Machine learning algorithms can review very large datasets for patterns us mere humans would never find. AI can be used to find trends and then provide notifications of something significant like an incredibly powerful control chart.

There are also negative aspects like cost and trusting the data. Some problems are immensely complicated and involve massive data requiring supercomputers. Other problems can be mitigated with a caution sign. Constantly being watched is perceived differently in the context of a nuclear reactor core, vs. an integrated laptop camera in someone's home office.

I personally use AI embedded in a variety of tools such as grammar aides, search engine type tasks, enabling applications in MS Office, and I'm learning Minitab for statistics. None are mind-blowing technology in today's age, but they do enable capabilities that were much more labor intensive before assistance from AI. That can change the cost benefit ratio from not worth the effort, to easy and highly effective.
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1 reply by Laura Lazzerini
Jun 02, 2024 7:15 AM
Laura Lazzerini
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Thank you very much Keith for your considerations and also for raising the point that a very important aspect is the quality of the data. This is an element that we have always to take into account when using AI.
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Laura Lazzerini
Community Champion
Head of International Project Management Office| Deutsche Telekom Praha, Czechia
May 23, 2024 5:42 PM
Replying to Sergio Luis Conte
...
AI is in use in things like Risk Management from long time ago. Almost 30 years ago. While both are focused on generative AI my recommendation is taking a closer look to both courses published for free by the PMI, In fact, you will find a list of tools inside them.
I absolutely agree with you. The two courses offered by PMI and also the whitepapers and other resources created by PMI are highly useful and give very interesting hints on several aspects.
avatar
Laura Lazzerini
Community Champion
Head of International Project Management Office| Deutsche Telekom Praha, Czechia
May 26, 2024 7:12 PM
Replying to Keith Novak
...
There are a lot of ways AI can support risk management. The question is what problem you are trying to address and whether AI is the right solution for the application.

LLMs can help compare your project to case studies to identify common issues. I think AI has the best potential yet for making documented lessons learned actually of some real value.

Image recognition algorithms are already used in various applications to detect potential threats. Is there a risk on the project which could be detected visually if there were cameras and/or radars monitoring some important work area?

Machine learning algorithms can review very large datasets for patterns us mere humans would never find. AI can be used to find trends and then provide notifications of something significant like an incredibly powerful control chart.

There are also negative aspects like cost and trusting the data. Some problems are immensely complicated and involve massive data requiring supercomputers. Other problems can be mitigated with a caution sign. Constantly being watched is perceived differently in the context of a nuclear reactor core, vs. an integrated laptop camera in someone's home office.

I personally use AI embedded in a variety of tools such as grammar aides, search engine type tasks, enabling applications in MS Office, and I'm learning Minitab for statistics. None are mind-blowing technology in today's age, but they do enable capabilities that were much more labor intensive before assistance from AI. That can change the cost benefit ratio from not worth the effort, to easy and highly effective.
Thank you very much Keith for your considerations and also for raising the point that a very important aspect is the quality of the data. This is an element that we have always to take into account when using AI.

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