Learning & Innovation Research Manager| Project Management Institute (PMI)Spain
Are you utilizing any specific checklists or protocols within your projects or company to assess your readiness for working with Generative AI data? I'm curious to know what strategies or tools you've implemented to prepare for integrating Gen AI into your workflows. Please share your approaches in the comments below! Saving Changes...
Due to confidentiality concerns in Healthcare industry we haven't started using AI models yet/
Yes, that´s true, and at least in my organization, we are at the same time thinking a little bit about how we can take benefits from what is going on with AI, but it is not a secret that medical companies have a lot of information that they are responsible for about what to share and what not. Saving Changes...
GenAI has the potential to be the most disruptive technology since the internet—and this transformation will impact the data-heavy tax function sooner than most. With the power of GenAI in taxation, tax professionals can enhance and expedite the data management process, driving improvements across a range of tasks. By harnessing the skills and expertise of tax professionals alongside GenAI tools, tax leaders can be even bolder in their plans to transform tax operations in the years to come.
1) Automation of basic tasks - Document generation and communications, form completion, preliminary review functions, and other administrative tasks.
2) Tax compliance - Automating the time-consuming aspects of tax compliance and reporting—such as data capture, computation, and reconciliation—can liberate tax professionals from routine transactional processes so they can add greater value beyond compliance. GenAI can also provide a narrative analysis of information and output while supporting human analysis.
3) Risk management of a global tax landscape - Large multinational companies operating in multiple jurisdictions need to rapidly identify and make sense of the latest developments across the globe. GenAI models can read, translate, and accurately summarize relevant documents in seconds, giving tax practitioners actionable information at speed.
4) Risk monitoring and analysis - Workflow status monitoring, near-real-time summary and analysis of tax filings, reports and support details, issue spotting, and causal analysis.
5) Strategic planning and communications - Scenario planning, near-real-time business issue analysis, and summarization of complex tax issues into business-friendly narratives. Saving Changes...
Mahalakshmi PavithraProject Manager| The Everly Putrajaya HotelCyberjaya, Selangor Darul Ehsan, Malaysia
Our organization is currently in the exploratory phase of adopting AI, navigating through the vast amount of information available and engaging in testing and trials. We're actively participating in training sessions to deepen our understanding. Saving Changes...
To prepare for integrating Generative AI data into workflows, as a student in project management, I'm focusing on research, education, and collaboration to understand its potential applications and limitations. Additionally, I'm conducting risk assessments, ensuring legal and ethical compliance, and implementing small-scale pilot projects to test feasibility and effectiveness. Continuous training, performance monitoring, and a culture of improvement are essential for adapting to the evolving landscape of Generative AI technology. Saving Changes...
Solomon OtemaSenior Manager, Towers and Structures| IHS Nigeria Ltd (IHS Holding Ltd)Victoria Island, Lagos, Nigeria
Hi Claudia,
We haven't yet started assessing how we can incorporate AI into our work at the Project Management Office at my organization. However, on a personal level, I have been able to use ChatGPT for some tasks and I can confirm that it is not very good with structured data such as that that would be provided in Excel Spreadsheets or CSV files. If the spreadsheet contained a lot of data, it even made it more difficult for ChatGPT to provide any kind of insight. Saving Changes...
Great question - Though we aren't there yet with Gen AI, I believe it is important to understand the data that we have, laws and regulations around the data usage and business goals that are being targeted. I would consider the below key items for my initiatives:
1. Understand the data, create knowledge groups to evaluate the available data, ensure only quality data is passed through for processing.
2. Once the data is understood and finalized, liason with the business for key objectives. Also, use standard analytics tools/applications to derive insights. This might help business fine tune their goals or even provide them insights into key business processes and areas of growth.
3. Ensuring proper training and understanding of Gen AI by the team. Few examples could be shared with the team to be able to connect the dots.
Gen AI is a powerful tool and with the right usage and understanding, the benefits are manifold. Saving Changes...
Claudia, this is a great question. However, given the nature of what we do as consultants, we haven't yet started preparing for this but would be very interested to see what other professionals and organizations are doing!
Agree. Saving Changes...
Fatoumata DiabyProject Manager| NoneIvry Sur Seine, Idf, France
I work as an external consultant for Finance IT projects. The clients I have are reluctant in using AI in their daily processes. The only way I see this innovation use is when implementing software that contains AI feature. In the sort term, I won't be able to leverage on on the day-to-day work. However, I can now see how to incorporate AI in the construction and devlopment of our own consultancy practice. Saving Changes...
Learning & Innovation Research Manager| Project Management Institute (PMI)Spain
Feb 28, 2024 8:38 AM
Replying to SHYAMAL GHOSH
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Data should be qualitative, structured and used RAG concepts for prompt feedback compared to fine tuning method. Model preparation is time consuming and precise, accurate with large data inputs for correct outputs due to proper trained inputs.
Thank you Shyamal, I like it when you say data should be qualitative, which I infer should not be easy to structure. Could you please give us an example of this kind of information so that we can learn how to transform qualitative into structured? Saving Changes...
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