Project Management

Please login or join to subscribe to this thread

When using AI systems, what are some best practices for ensuring the results you receive are accurate, relevant, and aligned with your original goals?

linkedin twitter facebook   Artificial Intelligence  
avatar
Sarah Philbrick
PMI Team Member
Director, Learning Design & Development| PMI Asheville, NC, United States

Validating and checking outputs is critical when working with AI systems like Generative AI. Such validation approaches may include establishing clear criteria, implementing strong testing protocols, and continuous refinement.

In your experience with AI, what are some best practices for ensuring the results you receive are accurate, relevant, and aligned with your original goals?
Sort By:
< 1 ... 2 3 4 5 6 7 8 9 10 11 12 ... 191 >
avatar
Nisar Ahmed Project Manager | PTCL Karachi, Pakistan
Provide detailed and specific information and review the output
avatar
Achille NDJOH SIMI IT Project Manager| Fédération québécoise des municipalités (FQM) Quebec, Canada
Ensuring accuracy, relevance, and alignment when using AI systems is crucial. Here are some best practices:

- Clear and specific prompts
- Verify outputs
- Understand the AI's limitations
- Iterative refinement
- Maintain context
- Critical thinking by applying our own expertise and judgment to evaluate AI outputs.
- Set clear evaluation criteria
- Use AI as a tool to augment, not replace, human decision-making.
- Involve subject matter experts in reviewing and validating AI-generated content.
- Be mindful of potential biases in AI outputs and ensure compliance with relevant regulations and ethical guidelines.

​​​​​​These are some points that deserve attention when we use AI systems in Project Management.
avatar
Eba'a Mobydeen Project Manager | Senior Motion Graphics Artist and Video Editor| Self-employed Amman, AM, Jordan
When using AI systems, follow these best practices to ensure accuracy, relevance, and alignment with your goals:

1. Define Clear Objectives: Clearly articulate the goals and criteria for the AI system to address.
2. Use High-Quality Data: Ensure the data used for training and testing is accurate, relevant, and up-to-date.
3. Regularly Validate Results: Continuously monitor and validate the AI's output against your objectives and real-world scenarios.
4. Incorporate Human Oversight: Implement regular reviews by domain experts to catch and correct any discrepancies.
5. Adjust and Optimize: Continuously refine and update the AI model based on feedback and changing requirements.
avatar
Anonymous
I'll definitely agree with most of the comments on emphasizing the importance of detailed information while being EXTRA diligent ensuring no confidential information is shared.
avatar
ABDUL SALEEM PC Project Manager| Gerab System Solutions LLC Dubai, United Arab Emirates

Context-driven prompts unlock AI's power for project managers. By tailoring prompts to specific project details, you can automate repetitive tasks based on your unique needs. Imagine generating customized meeting agendas or project reports with a few well-crafted instructions.



This frees you to focus on high-value activities. Instead of spending hours on administrative tasks, you can dedicate time to strategic planning, team development, and proactive risk mitigation.



I've seen the impact firsthand. By providing context in my prompts, I've automated scheduling, generated tailored reports, and even received AI-powered risk assessments. This empowers me to deliver exceptional results and stand out as a data-driven project leader.
avatar
Rasaq Olaniyan Houston, TX, United States
By avoiding ambiguity. Asking right question and having right data will bring about AI capacity to generate accurate report
avatar
Bhanu Viswanadha Product Manager| NetApp Inc. Fremont, Ca, United States
Be clear on what you are asking for and have an idea of what output you are expecting. Remember you are dealing with 'history' data and which may not be relevant for what you are looking for to use. Remember, vague questions will have vague answers.
avatar
Lenin Hazim Santo Domingo, Distrito Nacional, Dominican Republic
By using the correct prompt formula you will be able to get the output you are looking for considering the context, however AI is not perfect, that's why we need to consult and compare the outputs we receive with the reliable sources. In complex cases when the CREATE formula is necessary, it is a good practice to feed our LLM providing context from reliable sources.
avatar
Adedeji Adebanjo, PMP Data Analyst| Amazon London, United Kingdom
To ensure results received are accurate, relevant and aligned with original goals; effective prompts should be adopted because they serve as the blueprint for AI-generated responses, guiding the model toward producing relevant and actionable outputs
avatar
Alberto Mendoza Project Manager| Microsoft (Through Aquent) Dallas, TX, United States

In my experience, the following best practices can ensure that you receive more accurate information aligned with your objectives:


Narrow down your objective.
Be precise in your request.
Ask for detailed steps needed to complete the task.
Provide context to your request.
Specify the outcome you expect.
Request additional sources if necessary.

We are just beginning to understand the impact of AI. Its applications extend beyond project management to many other fields. Therefore, practices such as testing, learning from failures, and drawing insights from analogous industries could help us maximize the power of AI and achieve our project goals.
< 1 ... 2 3 4 5 6 7 8 9 10 11 12 ... 191 >

Please login or join to reply

Content ID:
ADVERTISEMENTS

Even if you're on the right track, you'll get run over if you just sit there.

- Will Rogers

ADVERTISEMENT

Sponsors







Vendor Events

See all Vendor Events

Newsletters

Jun 3: The Career Problem Facing New PMs
May 20: Your PM Career as a Project Life Cycle
May 13: The Big Lie After Layoffs

See all newsletters