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What successes have you experienced with Generative AI?

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Claudia Alcelay
PMI Team Member
Learning & Innovation Research Manager| Project Management Institute (PMI) Spain
Have you experienced wonderful, potentially unexpected successes using Generative AI in your projects? 

I'm eager to hear about the innovative outcomes you've achieved with Gen AI, and how data played a role in these ventures. 

What challenges did you encounter, and what benefits did you realize in this process?
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LAQUITTA JAMMIE JONES Project Management| 528
There are many opportunities for the GenAI to provide successful outcomes. The ways that this can be accomplished include but are not limited to: improving project outcomes, generate innovative ideas, simulate user interactions, erring third party providers, and ensuring that solutions are relevant and actionable.
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Pratheep Gnanasekar Subbaiyan Sr. Project Engineering Manager| Larsen and Toubro Limited Chennai, TN, India
Yes.

1) Condensing a large amount of data from a Project feasibility report in to a presentable crisp information.

2) Capturing Critical information from a customer specification when given with the requirement.
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Anonymous
I use generative AI to synthesize lessons learned from cybersecurity program and project management, then analyze the results for continuous improvement. Additionally, I ensure strict control to manage interactions with AI (like Chat GPT) to protect the confidentiality, integrity, and availability of company data
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Oluwaseun Ogundipe Project Manager| Malokun Labs Lagos, Nigeria
I have been using Gen AI to write my project reports and also to brainstorm. Still learning how to refine my prompt engineering skills with Gen AI.
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Cheryl Bowden Founder| Project Management, Training & Consulting Norton, Ma, United States
I use Gen AI to do Reflections for our teams. It provides great insights on recommendations and next steps.
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Antonio Alcada
Jan 04, 2024 9:41 AM
Replying to Kyle Trolan
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I've been using GenAI to help with brainstorming, developing articles and communication templates, and do some project management excel worksheet building. I've been able to produce documents much faster and increase my efficiency.
It seems a very good idea. Indeed, the Excel steel remain a very important tool to collect data. I'm triyng to develop a woorsheet that could resume the important monthly data. But the difficulty is to have a datasheet with the anual results and conclusins based on the collected monthly data. So I'll give you my congratulations to achive a very cheap and important goal
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Rex Holmlin Clinical Professor of Project Management| Mason School of Business College of William and Mary Williamsburg, Va, United States
I have had success with GenAI in helping with preliminary project planning and in integrating geographic information into task sequencing. But the human in the loop concept is crucial because I have also seen GenAI models hallucinate. You have to be very cautious with this tool.
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Antonio Alcada
Jan 04, 2024 4:56 AM
Replying to Sergio Luis Conte
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Challenges remain the same from long time ago (Gen AI is outside there from long time ago): AI entities have a grade of confidence associated to them that must be published with the results. So, the final decision still remains in human being hands. The same for the outcomes: helps me to search patterns in a hugh amount of data to create the information I need adding that today I can find data public and outside my organization.
I agree with you. A decades ago the Engineers made the calculations with a Rler and a calculator, after. When the calculations software appeared, many Engineers belived the wright output. Many wrong structural design was made because the «human» decision didn´t analyse carefuly the results. It was a very sad period to the Engineering because it was so easy to calculate comparing with the past.
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Raiyansh Bhardwaj SAP PM Consultant| WAV Haryana, India

Generative AI has driven significant successes across various domains, from content creation to advanced problem-solving. One major achievement is its ability to automate and enhance creative processes. In text generation, AI models like GPT have been instrumental in drafting reports, generating marketing copy, and even assisting in creative writing, significantly improving efficiency and reducing workload.



In the realm of image and video generation, tools like DALL·E and Stable Diffusion have enabled the rapid creation of high-quality visuals, benefiting industries like advertising, gaming, and design. Similarly, in software development, generative AI has streamlined coding by offering real-time suggestions, automating documentation, and debugging code, enhancing productivity for developers.



Another success is AI’s impact on personalized experiences. Generative AI has been used to create tailored chatbots, AI-powered tutors, and recommendation systems, improving user engagement and customer support. Additionally, in scientific research, AI has accelerated drug discovery, generated synthetic data for testing, and facilitated rapid prototyping in various fields.



By leveraging generative AI effectively, businesses and individuals have unlocked new levels of creativity, efficiency, and problem-solving, demonstrating its transformative potential in both creative and technical fields.
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Anonymous
The lessons learned example is interesting. I am curious to know how much time was spent sanitizing the data before using the generative AI, especially if the intention is to use the lessons learned from hundreds of projects. Was generative AI used to support that process?
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