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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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Pankaj . Consultant| Nippon Koei Company Limited Mabalacat City, PAMPANGA, Philippines
I haven't used GenAI for my work. I am still learning and trying to gather as much knowledge as possible before using AI. I firmly believe in gaining knowledge about the technology before actually using it. It's a great programme and very informative.
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SRINIVAS GAJAWADA SARABAIAH Mooresville, NC, United States
I have been using Gen AI to build my resume, draft emails and I also wrote a book about south indian cooking. I intend to learn more about doing POCs and implement effective Project management.
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KANNAN ALAGARSAMY Oakville, Ontario, Canada
In my company, I used the 'Watsonx' code assistant to automate the masked/synthetic healthcare test data creation, developed a website, and automated data entry from scratch.
It requires basic training on the code assistant capabilities, how to setup it up with IDEs, how to assemble and deploy the codes generated by the AI assistant. It also helped me to study the existing code and document the same.
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Isa Muhammad Other| Nigerian Gas Processing & Transportation Company Limited Warri, Delta, Nigeria
Thank you for the question. I have not used the GenAI yet but from what I am learning, it offers a lot to make one more efficient and effective both at personal level and in an organization.
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Roksana Jahan Tumpa University Lecturer| Central Queensland University Sydney, Australia
Very useful proof-of-concept and insights!
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Nicholas Beaudoin Director of AI Programs| Caltech (CTME) Pasadena, United States
As a manager that still spends time on the keyboard, I find that I have saved a tremendous amount of time in creating AI prototypes that work. Before the end of 2022 when ChatGPT was released, developers would scour the internet in search of frameworks to kick-start their code. However, most of these frameworks are a prompt away. Albeit there are ways to iterate and get better starting frameworks, the general AI/ML developer consensus is that ChatGPT (via o1 or similar GPT model releases), Google Gemini, and my personal favorite, Anthropic Claude (yay for Artififacts) makes prototyping orders of magnitude faster.

Example: This past week I needed to create a prototype for a client. It would have taken multiple days to get something ready. With Claude, I was able to have a working demo in 3 hours! As someone that doesn't have their hands don't their hands on the keyboard, or know the latest tricks that all the cool kids are using, this was spectacular.

Now don't get me wrong, I don't think that this is an example of Jensen Huang's premise to not learn coding, but it was a real eye opener to how far we have come.
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Marcos Garcia Salas Eden Prairie, MN, United States
Being part of PMOs in multiple organizations, I usually face the need of defining frameworks, policies, procedures, plans and templates for everything.

I have used Gen AI as a starting point and then I finish the detailed work needed, saved time substantially and I was able to increase the amount of concurrent initiatives progressing in parallel.

It is a great asset to have an AI Assitant that can gather data, information and results from both external and internal sources however we as human are still the key ingredient thru prompt engineering to avoid allucinations.
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Ishpinder Kailey Melbourne, Victoria, Australia
While generative AI has notably improved my projects, it has also come with significant challenges. One of the primary concerns has been the AI’s reliance on data quality. AI models are only as effective as the data they are trained on, and incomplete, biased, or poorly structured data can lead to inaccurate or skewed outputs. This has sometimes required extra time and resources to clean and validate the data before it can be used effectively. Additionally, despite AI's efficiency, I’ve found that it is occasionally too generic, lacking the specific insights needed for complex project scenarios and its responses requiring manual refinement. There’s also the challenge of ensuring the right balance between AI automation and human oversight. Over-reliance on AI can result in missing the nuances of project-specific contexts, which could undermine decision-making. While AI can streamline processes, it’s clear that human expertise remains indispensable to ensure quality and alignment with broader project goals.
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Donald Thomas Daphne, Al, United States
I've used GenAI from Agile development roadmapping to generating email responses and almost ever use case in between.
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Alessandro CalabrĂ² Innovation & Growth Manager| Seabreeze Villas Riva San Vitale, Switzerland

During my career as a PMP-certified Management Engineer and Project Manager, I've had several opportunities to integrate Generative AI into my projects, yielding unexpected and transformative outcomes. For instance, as Innovation & Growth Manager, I utilized Generative AI to analyze market trends and support the development of predictive models for investment portfolio management. By leveraging AI to process large datasets, I refined a business model that aligns closely with real market dynamics, achieving increased reliability and improved revenue optimization.



One notable success was designing a data-driven AI model to forecast cash flow revenues. The AI system's ability to generate insights from historical and real-time data significantly improved decision-making and enhanced stakeholder confidence.



Challenges included ensuring data quality and overcoming initial resistance to AI integration among team members. Through strategic communication and demonstrations of AI’s capabilities, I secured buy-in and established a workflow that balanced human expertise with AI’s computational power.



The benefits of integrating Generative AI were profound: it increased efficiency, improved forecasting accuracy, and introduced a scalable solution for ongoing business growth. These experiences solidified my belief in the transformative potential of AI when aligned with robust data strategies.

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