Will the widespread adoption of prompt engineering commoditize project management skills, or can it help PMs differentiate themselves and command higher value?
Director, Learning Design & Development| PMIAsheville, NC, United States
Hi PMI Community! I’m Sarah Philbrick, and I work as a Product Manager at PMI with a focus on our learning offerings. As we go on this skill-building journey together, I’m excited to engage in meaningful conversations, explore trending topics, and learn from each other.
Reflecting on one such topic, GenAI and prompt engineering, I am interested to hear your perspective on commoditization vs. differentiation.
Will the widespread adoption of prompt engineering commoditize project management skills, or can it help PMs differentiate themselves and command higher value?
The adoption of prompt engineering will give value in project management to those who have a good capacity to adapt in this disruptive world Saving Changes...
While prompt engineering may streamline certain aspects of project management, skilled project managers who combine technical knowledge, soft skills, and strategic thinking could be continue to command higher value.
Well said. The difference doesn't come from the power of AI... It's actually what you do with it. The more experience and skill, the better the prompts. Saving Changes...
Daniel SapienzaeCommerce Manager - LAC| AnsellSao Paulo, SP, Brazil
Could be commoditized in some level of projects, however on my point of view, the adoption of LLMs and other AI technologies increases productivity and standardization could be mixed with personal know-how and experience by the AI user. Saving Changes...
The widespread adoption of prompt engineering in the context of project management could have a multifaceted impact. Here's a breakdown of the potential effects:
Commoditization of Project Management Skills
1. Automation of Routine Tasks:
Prompt engineering can automate many routine and administrative tasks such as scheduling, status reporting, and documentation. This might lead to the perception that basic project management skills are more easily replaceable by AI tools.
2. Standardization:
With prompt engineering, certain project management practices can become standardized, leading to a level playing field where basic PM skills are no longer a differentiator.
3. Lower Entry Barriers:
The barrier to entry for new project managers could be lowered, as prompt engineering can assist less experienced PMs in performing tasks that would typically require more expertise.
Differentiation and Commanding Higher Value
1. Focus on Strategic and Complex Tasks:
Project managers who leverage prompt engineering can free up time from routine tasks to focus on more strategic, complex, and high-value activities, such as stakeholder management, risk mitigation, and strategic planning. This shift can help them differentiate themselves.
2. Enhanced Decision Making:
By using prompt engineering to quickly gather insights, analyze data, and generate reports, project managers can make more informed decisions faster, enhancing their effectiveness and perceived value.
3. Skill Augmentation:
Mastery of prompt engineering itself can be a valuable skill. PMs who can effectively harness AI tools to enhance project outcomes can differentiate themselves and command higher value in the market.
4. Innovation and Adaptability:
Project managers who are adept at integrating new technologies and methodologies into their workflow can drive innovation within their organizations. This adaptability is highly valuable in dynamic business environments.
5. Enhanced Communication:
Prompt engineering can improve communication by generating clear, concise, and well-structured updates and reports, enhancing the PM's ability to communicate effectively with stakeholders.
The adoption of prompt engineering has the potential to both commoditize certain aspects of project management and provide avenues for differentiation. The key for project managers will be to leverage these tools to move beyond routine tasks, enhance their strategic capabilities, and continuously adapt to new technologies to remain valuable and relevant in the field.
ISIAKA OLUTOBA FADAHUNSICONTRACT MANAGER| SHELL NIGERIA EXPLORATION AND PRODUCTION COMPANYLagos, Nigeria
May 27, 2024 10:31 AM
Replying to Omar Jabbar
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This trend raises important questions about the future of project management in a rapidly evolving technological landscape. Many people have wondered whether AI will replace project managers. It's clear that PMs need to adapt and learn how to use and leverage AI to stay relevant and effective in their roles.
Who would have imagined 20 years ago that vehicles would not need drivers? We may not be there yet, but we will be soon.
As long as PM use Gen AI responsibly and ethically. Creating quality prompts is key to getting the right output from GenAI. Project Managers can leverage this tool to simplify tasks and increase productivity. Saving Changes...
M. Aslam MirzaCEO & Principal Consultant| PM-Strategists CornerHouston, Texas, United States
My view is to focus on learning the best use of GenAI and Prompt Enginnering for exploring the peak of performance with creativity and innovation.
Replacement of just happened PM with highly trained PM for high performance is definitely going to be in a near future time. Saving Changes...
Prompt responses are like strong root. The more it gets input, the accurate will be the output. PM's capability to ask right question and critical thinking according to situation magnify the quality. Skills can be commoditize but value depends on quality. Saving Changes...
Max MooreGroup Director - Corporate Program Management Office (PMO)| Roush Management, LLCCommerce Township, Mi, United States
I agree wholeheartedly with Olaitin Lasisi and several others in the above thread. AI can never replace experienced and informed Project Managers, "but rather empower them to function optimally". The technology is only as powerful as we are capable of extractung the power of the tools. Saving Changes...
Brian KellySenior Programme and Project Manager | ContractLondon, United Kingdom
In my opinion the creation of a powerful tool that leverages a company's collective project management wisdom while maintaining data security and privacy is the AI Holy Grail for project managers. This will allow you to benefit from AI capabilities without relying on external services, ensuring full control over your sensitive project data. A human vs. machine approach is still required to disseminate the nuances of doing business in this VUCA world, and this is where the project manager will continue to add value. Large companies (with large datasets) have the opportunity now to be first movers adopting an AI mindset throughout their business segments. As an example use case, I want to prompt an AI to build a business case for my new company project. First I need to get the infrastructure and data management solution in place, then I simply run the prompt. Here’s how:
PART A.
1. Infrastructure and Deployment:
Set up a secure infrastructure to host the private LLM. This typically involves using a Kubernetes cluster for scalability and management. This requires deployment of components such as:
A managed Kubernetes cluster (e.g., using Gardener)
Ollama for running the LLM efficiently within Kubernetes
AnythingLLM for user interface and model interaction
Ingress NGINX for routing traffic
Certbot for SSL certificate management
A vector database like chromadb for storing embeddings
2. Data Preparation and Integration:
To leverage the historical project management data:
Collect and organize all relevant datasets, deliverables, and documents
Clean and pre-process the data to ensure quality input for the LLM
Convert documents into a format suitable for ingestion by the LLM
Implement a system for continuous data updates as new projects are completed
3. Model Selection and Fine-tuning:
Choose an appropriate base LLM and fine-tune it on the company's specific project management data. This will help the model understand the organization's unique terminology and practices.
4. Security and Compliance:
Implement robust security measures to protect sensitive project data:
Use encryption for data at rest and in transit
Set up access controls and user authentication
Ensure compliance with relevant data protection regulations
Regularly audit and monitor the system for potential vulnerabilities
5. Integration with Existing Systems:
Develop APIs or integrations to connect the private LLM with existing project management tools and databases.
6. User Interface and Workflow:
Create a user-friendly interface that allows project managers to easily query the LLM and retrieve relevant information from past projects.
7. Training and Adoption:
Provide training to project managers on how to effectively use the LLM for tasks like creating business cases. Develop guidelines for best practices in leveraging the system.
8. Continuous Improvement:
Implement a feedback loop to continuously improve the LLM's performance based on user interactions and new project data.
PART B.
For the specific use case of creating a business case in the Initiate phase:
1. Ensure the LLM is trained on a comprehensive set of past business cases.
2. Develop a prompt template that includes key elements of a business case (e.g., project justification, cost-benefit analysis, risk assessment).
3. Implement a system to input current project specifics (e.g., objectives, stakeholders, budget constraints) into the LLM query.
4. Use Retrieval-Augmented Generation (RAG) to allow the LLM to reference specific relevant past projects when generating the new business case.
5. Set up a review process where the LLM-generated business case is validated and refined by experienced project managers. Saving Changes...
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