Vikas MahendraProgram Manager| GP StrategiesNavi Mumbai, Maharashtra, India
I want to know, what are the common reasons or use cases you use generative AI for? You may also add your experience about the output you have - Useful, Fast, Accurate...etc Saving Changes...
Testing third-party generative AI models involves evaluating their accuracy, reliability, and safety before integration. Start by defining the use case and creating realistic prompts to test outputs. Assess response quality, bias, hallucinations, and performance across different scenarios. Businesses often rely on generative ai development services to properly evaluate models, ensure compatibility with applications, and maintain secure, responsible AI implementation.
I use generative AI in my day to day work to improve project planning, support decision making, streamline communication, and enhance productivity. From a project management perspective, I use AI to structure project plans, summarize meetings, draft project documentation, identify potential risks, analyze information, develop stakeholder communication, and organize tasks according to project priorities.
In my project management work associated with Edoxi Kuwait, I explore how generative AI can support project coordination, strategic planning, stakeholder engagement, risk assessment, and performance monitoring. AI-assisted research helps me organize information, evaluate possible approaches, prepare project updates, and develop structured action plans aligned with project objectives and business requirements.
For projects involving Edoxi Kuwait's professional training and development initiatives, I am particularly interested in applying AI to project scheduling, resource planning, progress tracking, communication management, and continuous improvement. AI can also help organize feedback, identify recurring issues, document lessons learned, and support evidence-based decisions throughout the project lifecycle. I view generative AI as a decision-support tool rather than a replacement for a project manager.
I review AI-generated outputs for accuracy, feasibility, bias, and relevance before using them in project activities. I also consider data privacy, confidentiality, ethical AI use, stakeholder expectations, and organizational policies when selecting and applying AI tools.
My approach aligns with key project management principles emphasized by the Project Management Institute (PMI), including value delivery, stewardship, stakeholder engagement, risk management, adaptability, and accountability.
Ultimately, I aim to use AI responsibly to improve project outcomes, support collaboration, and deliver measurable business value while ensuring that final decisions remain guided by professional judgment and human oversight. Saving Changes...
