Project Management

Please login or join to subscribe to this thread

Learning from False Starts - How to Avoid AI Pitfalls

linkedin twitter facebook   Artificial Intelligence   Risk Management  
avatar
Dr. Deepa Bhide Hyderabad, Telangana, India
In recent months, we have been embracing our curiosity, learning about AI, and experimenting with different use cases for its application to project management. Using AI for individual use is one thing, but using it for organizational purposes is a different game altogether. It needs thorough planning, understanding, resourcing, budgeting, etc. We see instances where organizations resort to using AI tools without a clear understanding of the problems they will solve or address; time and money are committed to projects that stall due to a lack of understanding of these AI tools or a lack of proper training of project managers and team members. The resulting false starts and perceptions of waste may lead organizations to question the use of AI tools.

Have you faced a scenario in which a team or organization jumped too quickly into leveraging or implementing AI tools? What was the result? How can this be mitigated?
Sort By:
avatar
Danny PMP, PgMP
Community Champion
Senior Consultant Tokyo, Japan
Besides testing, education, and training, it's crucial to allow people some time to learn and adapt to any major changes, which includes space to make mistakes and learn. I believe this principle applies similarly to AI implementation. Just my 2 cents. While I don't have a concrete example for AI implementation, I do have experience with automation or digitalization projects, which might be somehow related.
...
1 reply by Dr. Deepa Bhide
Apr 05, 2024 4:26 AM
Dr. Deepa Bhide
...
Danny, i agree with you. Getting to the project and then going a full wheel quickly is risky, especially when there is a novice technology involved. A thoughtful ideation is needed even if it's a late start. Thanks
avatar
Dr. Deepa Bhide Hyderabad, Telangana, India
Apr 05, 2024 3:07 AM
Replying to Danny PMP, PgMP
...
Besides testing, education, and training, it's crucial to allow people some time to learn and adapt to any major changes, which includes space to make mistakes and learn. I believe this principle applies similarly to AI implementation. Just my 2 cents. While I don't have a concrete example for AI implementation, I do have experience with automation or digitalization projects, which might be somehow related.
Danny, i agree with you. Getting to the project and then going a full wheel quickly is risky, especially when there is a novice technology involved. A thoughtful ideation is needed even if it's a late start. Thanks
avatar
Sergio Luis Conte Helping to create solutions for everyone| Worldwide based Organizations Buenos Aires, Argentina
The problem is in recent times AI becomes a buzzword and lot of misunderstanding is creating mainly when people confuse AI with generative AI (Chatgpt for example). AI is a boarder term and it is using in projects for long time ago. Projects like advance manufacturing or IoT apply AI. So, based on my experience along the years, nothing new below the sun with AI. Just in case people need to implement the new version of generative AI at organizational level they must consider new roles to be added to the team like lawyers, SMEs in inclusion and diversity, linguistics between others that perhaps are not usual to include in other projects.
avatar
Kiron Bondale Retired | Mentor| Retired Welland, Ontario, Canada
Deepa -

I haven't personally faced such a challenge, but there is the famous case of the lawyer who used GenAI provided info to support a case and was disciplined for doing so once it was clear the AI info was a hallucination.

As I have been saying "Don't trust AND do verify!"

Kiron

Please login or join to reply

Content ID:
ADVERTISEMENTS

"The human race has one really effective weapon, and that is laughter."

- Mark Twain

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