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AI for Project and Portfolio Management: tools, use cases and examples of Chat GPT prompts

Q: What skills do project managers need to work effectively with AI tools?

Data and technology literacy : To understand and leverage AI insights. Critical thinking : To evaluate and contextualize AI recommendations. Ethical awareness: To ensure responsible use of AI. Change management expertise : To guide teams in adopting AI-driven processes effectively.

Do you remember what your daily routine looked like before Artificial Intelligence entered your life? Endless reports waiting to be updated, interminable meetings, and poor strategic decisions due to a lack of consistent data… This was the reality for PMOs (Project Management Offices) and Project Managers not long ago. Then AI came along and completely upended the way we work.

Artificial Intelligence has sparked a genuine revolution across all professional sectors, and project and portfolio management is no exception. With businesses now facing an ever-growing volume of initiatives, AI has become the perfect ally for PMOs and Project Managers, enabling them to make data-driven decisions, plan more effectively, and manage and deliver projects with greater speed and accuracy.

In this post, we’ll explore how AI is transforming project management, its key benefits, and real-world use cases. We’ll place special emphasis on showcasing tools and practical examples to help you harness the full potential of AI in your day-to-day work.

How AI is impacting Project Management

Will AI replace Project Managers? The answer is no, but it will change the way they work. As we explained in our post on Trends in Project Portfolio Management, AI is no longer a futuristic concept aimed at replacing our roles—it’s a practical tool reshaping how we operate.

AI is revolutionizing how organizations plan, monitor, and manage projects. In an increasingly complex business environment, where quality standards and time-to-market pressures are higher than ever, AI empowers Project Management professionals to work smarter and more strategically.

Some of the key areas where AI can make a difference in your day-to-day work include task automation, project resource management, and decision making. Not only does AI help reduce manual workload, but it also provides insights that can help you improve project performance and outcomes.

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Benefits of AI for PMOs and Project Managers

Whether you’re looking to accelerate project timelines or plan and mitigate risks, AI offers countless advantages for PMOs and Project Managers.

Here are the key benefits of integrating Artificial Intelligence into project management:

Improved decision-making: AI tools allow you to analyze vast amounts of project data, uncovering trends, patterns, and anomalies. This enables faster, more informed decision-making with reduced errors. Additionally, machine learning models can simulate various project scenarios, helping you optimize performance based on actionable insights provided by these tools.
Resource optimization: AI aids in evaluating workloads, skills, and the availability of resources within your organization. By doing so, it ensures the right resources are allocated to the right tasks at the right time, maximizing efficiency and minimizing bottlenecks.
Increased productivity: say goodbye to late nights spent catching up on overdue reports. AI enables the generation of reports in seconds and can automatically share updates with stakeholders, freeing up your time to focus on higher-value activities.
Risk mitigation: AI helps predict potential project risks by analyzing historical data, external factors, and resource availability. This allows you to proactively address issues, avoiding delays, cost overruns, or scope deviations.
Enhanced communication: AI enhances team communication and collaboration. For example, AI-powered personal assistants can transcribe and summarize meetings.
Greater accuracy: AI significantly reduces errors by delivering high levels of precision in tasks such as cost estimation and risk assessment

AI use cases in Project Management

Whether you’re looking to accelerate project timelines or plan and mitigate risks, AI offers countless advantages for PMOs and Project Managers.

Generative AI

Generative AI uses machine learning models to create content, ideas, and strategies, making it a powerful tool for project creation and planning.

Key use cases of Generative AI in Project Management:

Content creation: Generate reports, project proposals, or presentations within minutes.
Scenario modeling: Create various project scenarios to evaluate potential outcomes and choose the best option for your organization’s needs.
Stakeholder communication: Configure personalized notifications or documentation tailored to different stakeholders.

Tools like ChatGPT, Copilot, and other similar platforms can assist by answering queries, suggesting improvements, or creating project templates.

Analytical AI

Analytical AI focuses on data processing and interpretation. It’s an invaluable resource for Project Managers, offering insights to better understand project dynamics and trends, ultimately improving decision-making.

Key use cases of Analytical AI:

Data analysis: Examine performance metrics to identify inefficiencies and bottlenecks.
Trend identification: Detect patterns in project timelines, resource usage, or costs.
Dashboard automation: Analyze real-time dashboards to evaluate the health of projects and portfolios.

Aspect	Analytical AI	Generative AI
Purpose	Processes and interprets data to extract insights and identify patterns.	Creates content, ideas, or solutions from prompts or data patterns.
Focus	“What do the data tell us?”	“What can we create from this?”
How it works	Analyzes historical and real-time data for trends and performance metrics.	Produces new content like project plans, reports, or creative solutions using advanced AI models.
Use cases	Performance reports and dashboards. Identifying workflow inefficiencies or bottlenecks. Conducting cost-benefit analyses.	Performance reports and dashboards. Identifying workflow inefficiencies or bottlenecks. Conducting cost-benefit analyses.
Limitations	Restricted to interpreting existing data and cannot create new content.	May produce irrelevant or impractical results if instructions are unclear or data lacks context.

Predictive AI

Predictive AI leverages historical data and predictive models to forecast outcomes. It enables organizations to take a proactive approach, anticipating potential challenges, minimizing bottlenecks, and ensuring smooth project execution.

Key use cases of Predictive AI in Project and Portfolio Management:

Project timeline planning: Predict project completion dates with greater accuracy and identify potential delays based on historical trends and current data.
Risk prediction: Identify potential risks and assess their likelihood of occurring.
Demand forecasting: Anticipate future resource or budget needs, enabling better planning.

Prescriptive AI

Unlike predictive AI, prescriptive AI takes it a step further by providing actionable advice and recommendations. This application of AI helps organizations proactively address issues before they escalate.

Key use cases of Prescriptive AI:

Decision Optimization: Recommends the best course of action for projects based on goals and constraints.
Resource allocation: it offers practical suggestions for reallocating resources to maximize efficiency.
Risk mitigation: It proposes alternative strategies to mitigate identified risks.
Conflict resolution: Suggest solutions for team conflicts or overlapping schedules and deadlines.

Aspect	Predictive l AI	Prescriptive AI
Purpose	Forecasts future outcomes using historical and current data.	Recommends specific actions to achieve desired outcomes.
Focus	"What will happen?"	"What should we do?"
How it works	Uses statistical models and machine learning to identify trends, patterns, and potential events.	Combines predictive insights with optimization algorithms and decision rules to suggest actions.
Use Cases	Predict delays. Forecast resource demand. Estimate potential cost overruns.	Recommend strategies to meet deadlines or reallocate resources to prevent delays. Optimize resource allocation based on demand forecasts. Suggest budget adjustments.
Limitations	Provides insights but does not specify how to act on them.	It relies on data quality and may oversimplify complex decisions.

Automation

One of the most apparent benefits of AI in Project Management is the ability to automate tasks. With AI, Project Managers no longer need to spend hours manually updating reports. Instead, they can focus on tasks that truly add value.

Tasks PMOs and Project Managers Can Automate Using AI:

Project updates: Automatically update project schedules or send alerts and notifications to various teams.
Workflow automation: Manage workflows or approvals without human intervention.
Report generation: Instantly generate project reports, reducing the administrative burden.

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Best practices when using AI in Project Management

Now that you understand AI use cases and tools, successful implementation requires clarity on:

Objectives you aim to achieve.
Processes you want to improve.
The roadmap for rolling out AI across your organization.

Here are seven best practices to ensure the successful integration of AI into your project management workflows.

1. Align AI implementation with organizational goals

Just because AI is trending doesn’t mean it should be used arbitrarily. Its adoption must be a strategic move aligned with your organization’s overarching objectives. Start by identifying areas where AI can add the most value.

For instance:

Do you need to improve project planning?
Accelerate resource allocation?
Enhance risk management?

Once these goals are defined, choose AI tools that best fit your objectives. Misalignment in your AI strategy will lead to disappointing results.

2. Invest in training

To unlock AI’s full potential, teams need to understand how to use it effectively. While AI can automate tasks, generate content, and provide recommendations, human oversight is essential for interpreting its insights.

Training your team will empower them to:

Master AI tools and integrate them seamlessly into project workflows.
Interpret AI-driven predictions and recommendations accurately.

3. Prioritize data quality

AI relies on the quality of data it processes. To generate valuable insights, the input must be accurate and contextually relevant. Here’s how to ensure this:

Establish clear data quality and consistency guidelines within your organization.
Use tools that update project and portfolio data in real time to reflect the latest information.
Leverage technologies that identify and rectify duplicates, errors, or inconsistencies.
Encourage project teams to handle data meticulously for reliable AI outcomes.

4. Use AI responsibly

AI’s potential in project management is immense, but over-reliance on it can be risky. Use it judiciously, recognizing its limitations:

Verify AI outputs: Cross-check AI-generated insights and recommendations with your expertise and organizational knowledge.
Question AI results: Don’t hesitate to challenge AI findings, especially if they seem contradictory or inconsistent with established practices.

5. Integrate AI with Existing Project Management processes

For maximum impact, AI tools should seamlessly integrate with your current applications and workflows. For example:

Ensure your project portfolio management software integrates with AI tools. Tools like Triskell Software can connect with OpenAI, enabling you to manage project documents and data directly through interfaces like ChatGPT.
Similarly, if you use platforms like Teams or Slack, you should ensure compatibility for automating tasks such as meeting minutes.

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6. Start small and scale over time

When incorporating AI into project management, adopt a gradual approach. Begin by using AI for simple tasks such as:

Sending project status updates.
Creating reports.
Generating meeting minutes.
Predicting project timelines.

As your teams grow more comfortable, expand AI use to more advanced applications, such as resource allocation or risk identification and mitigation.

7. Monitor and evaluate AI performance

No matter how AI is used, continuously monitor and assess its value. Measure performance based on factors such as:

Prediction accuracy.
Time saved through process automation.
User satisfaction and adoption rates.

Since AI is here to stay, staying updated on the latest developments and tools is crucial. This ensures you can optimize current processes and keep your organization ahead of the curve.

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Best AI tools for project management

In recent years, numerous AI-powered tools have emerged, making it challenging to identify the best ones for project leaders. Here are five AI tools that can boost your efficiency and creativity in project management.

AI tool #1: Chat GPT (OpenAI)

ChatGPT is an advanced language model capable of generating human-like text based on prompts. It can assist with various project management tasks, such as:

Generating reports.
Drafting of project documentation.
Automating communications.
Supporting brainstorming and problem-solving efforts.

Additionally, ChatGPT integrates with several project and portfolio management tools, including Triskell Software.

AI tool #2: Copilot

Developed by Microsoft, Copilot offers similar features to ChatGPT, specifically within the Microsoft ecosystem. It helps with:

Drafting documents.
Analyzing data.
Tracking project progress across tools like Microsoft Project, Excel, and Teams.

With Copilot, you can automate routine tasks, analyze large datasets, and gain actionable insights for better project planning and execution.

AI tool #3: Gemini

Google’s AI assistant, Gemini, stands apart from ChatGPT and Copilot with its seamless integration into Google Workspace. Its key differentiator lies in its ability to deliver more accurate results by cross-referencing information with Google’s search engine. It is an excellent choice for professionals already embedded in the Google ecosystem.

AI tool #4: Notebook LM

Another Google AI tool, Notebook LM is designed for managing and synthesizing large volumes of information. Unlike Gemini, this tool is tailored for:

Organizing notes.
Linking related content.
Extracting insights from extensive documentation.

Notebook LM is particularly useful for projects that require intensive reading and research.

AI tool #5: Claude

Finally, we highlight Claude, a next-generation AI assistant developed by Anthropic. Ideal for brainstorming, content creation, and document analysis, Claude excels in processing complex documents, such as codebases or financial reports.

Examples of ChatGPT prompts for Project and Portfolio Management

Among the many AI tools available, ChatGPT stands out as the most popular. However, popularity doesn’t necessarily equate to being the best or most comprehensive tool. ChatGPT requires well-crafted, precise prompts to deliver optimal results.

Despite its limitations, ChatGPT can be a valuable asset for PMOs and project managers. Below are over 50 examples of prompts tailored to cover all processes in Project and Portfolio Management. These prompts are particularly effective when integrated with portfolio management tools like Triskell Software.

NOTE 1: To maximize the potential of these prompts in ChatGPT, refer to the Frequently Asked Questions section of this post.

NOTE 2: be cautious not to share sensitive information and align your usage of ChatGPT with your organization’s Compliance and Security policies.

Examples of ChatGPT prompts for project planning and scheduling

Project timeline: “Suggest a project timeline for a [Project Type], considering tasks like [list of tasks]. Assume a team of [team size] and the following constraints: [list of constraints]. Include key milestones and dependencies.”

Optimization of the project task schedule: “Analyze this list of project tasks: [list of tasks]. Identify potential bottlenecks and propose adjustments to optimize the schedule while maintaining deadlines”.

Task sequencing: “Given the tasks: [list of tasks], arrange them in a logical sequence considering dependencies, estimated durations ([duration estimates]), and deadlines ([deadline]).”

Scenario Simulation: “Develop an alternative project schedule for [project scenario], where [constraint or challenge] occurs, such as [e.g., delayed resource availability].”

Critical path identification: “Here is a project schedule: [task list with durations and dependencies]. Identify the critical path and any tasks that can be delayed without affecting the project timeline.”

Project milestones planning: “Suggest critical milestones for a [Project Type] that includes phases like [list of phases]. Provide typical timelines for each milestone.”

Examples of ChatGPT prompts for Resource Management

Resource allocation planning: “Suggest a resource allocation plan for [project description], considering team roles: [list of roles], availability: [hours per week or constraints], and skills: [list of skills required].”

Identifying resource gaps: “Based on this project requirement: [project description], identify potential skill gaps in the current team: [team composition]. Recommend the type of additional resources needed.”

Cross-functional resource management: “For a cross-functional (type of project) involving [departments or teams], suggest strategies for resource sharing and resolving conflicts over shared resource availability.”

Skill development plan: “Based on these project requirements: [list of requirements], recommend training or development plans for the (team composition) to improve readiness for upcoming tasks.”

Capacity analysis: “Analyze the workload for the team: [team details and tasks]. Highlight any over-allocation or underutilization and suggest resource balancing strategies.”

Examples of ChatGPT prompts for Budget and Financial Management

Budget estimation: “Create a preliminary budget estimate for [Project Type]. Include typical cost categories such as [list categories, e.g., labor, materials, software]. Assume the following parameters: [specific project details].”

Cost-breakdown analysis: “Provide a detailed cost breakdown for this project: [project description]. Include fixed, variable, and contingency costs based on the following budget: [budget details].”

Budget vs actuals analysis: “Analyze the following financial data: [list actual costs vs. budgeted costs] for this project (project type). Identify any significant variances and propose corrective actions.”

ROI analysis: “Calculate the ROI for [Project Type] given the following inputs: [initial investment], [expected benefits or savings]. Provide a step-by-step breakdown”.

Budget Risk assessment: “For this project (project type), review the following budget plan: [budget details]. Identify potential financial risks and recommend contingency measures.”

Financial impact of scope changes: “For this project [project type], assess the financial impact of these proposed scope changes: [list of changes]. Suggest strategies to minimize budget overruns.”

Examples of ChatGPT prompts for Risk Management

Risk identification: “Identify potential risks for [Project Type]. Consider factors such as [scope, timeline, resources, stakeholders]. Provide a categorized list of risks.”

Risk prioritization: “For this [project type], evaluate the following risks: [list of risks with descriptions]. Rank them based on impact and likelihood using a risk matrix.”

Risk communication: “Draft a communication plan to inform stakeholders about the following risks: [list risks]. Include key messages and preferred channels.”

Mitigation strategies: “For this [project type], propose mitigation strategies for the top three risks in this project: [list risks]. Include detailed steps and contingencies.”

Early warning indicators: “For this [project type], develop a set of early warning indicators for these risks: [list risks]. Include metrics and thresholds for proactive monitoring.”

Scenario planning for risks: “For this [project type], develop a scenario plan for the following high-impact risk: [risk description]. Include a response plan and recovery strategy.”

Examples of ChatGPT prompts for Portfolio Management

Portfolio prioritization: “Based on these projects: [list of projects with descriptions and objectives], suggest a prioritization strategy considering factors like ROI, strategic alignment, and resource availability.”

Project health assessment: “Analyze the health of the following project portfolio: [list of projects and statuses]. Highlight risks, bottlenecks, and underperforming projects.”

Balancing resources across projects: “Given these resource constraints: [resource details], propose a reallocation plan for the current portfolio to optimize resource utilization across [list of projects].”

Portfolio alignment with strategy: “Review the following portfolio: [list of projects]. Assess its alignment with the organization’s strategic goals: [strategic goals description]. Provide recommendations for better alignment.”

Portfolio optimization under budget constraints: “Review the following portfolio: [list of projects]. Optimize the portfolio to fit within this budget: [budget amount]. Suggest adjustments to project scopes, timelines, or resource allocation.”

Portfolio risk analysis: “Perform a portfolio-level risk analysis for these projects: [list of projects and risks]. Identify cumulative risks and suggest mitigation strategies.”

Examples of ChatGPT prompts for Strategic Planning

Setting organizational goals: “Develop a list of strategic goals for an organization in [industry or field]. Consider trends, competitor analysis, and internal strengths: [details or attached document].”

SWOT Analysis: “Perform a SWOT analysis for this organization: [organization details or industry]. Provide insights into potential strategic priorities.”

Scenario Planning: “For this organization: [organization details], develop a scenario plan for the following strategic challenges: [list challenges]. Include best-case, worst-case, and most-likely scenarios.”

Competitive positioning: “Develop a strategic positioning statement for [organization or product]. Use this data: [competitor analysis or market insights].”

Defining KPIs: “For this organization: [organization details], define KPIs for tracking the success of this strategy: [strategy description]. Ensure they are aligned with objectives and measurable.”

Examples of ChatGPT prompts for Collaboration and communication

Team communication plan: “Draft a team communication plan for [type of project]. Include details on communication methods, frequency, and key updates required for team members and stakeholders.”

Meeting agenda preparation: “Create a detailed agenda for a project status meeting. The topics to cover include [progress updates, risks, and issues]. Specify estimated durations for each topic.”

Team roles and responsibilities: “Create a RACI roles and responsibilities matrix for the team involved in [project name]. Use the following inputs: [list team members and tasks].”

Feedback collection: “For this project [project type], draft a survey to collect feedback from team members on the effectiveness of current communication practices. Include questions about clarity, frequency, and channels used”

Project Kickoff presentation: “Create a draft outline for a project kickoff presentation for [project name]. Include sections on goals, timelines, team roles, and expectations.”

Escalation procedure: “For this project [project type], develop an escalation procedure for handling issues during [specific project phase]. Specify communication channels, roles, and timelines.”

Examples of ChatGPT prompts for Task automation

Email automation: “Draft automated email templates for common scenarios in project management, such as [task assignments, deadline reminders, and stakeholder updates].”

Automated status report: “Create a template for an automated project status report that includes data fields such as [progress percentage, risks, milestones].

Data entry and analysis: “Import project task data from the spreadsheet [attach spreadsheets] and organize it by priority and deadline.”

Workflow optimization: “For this project [project name] Identify areas in this workflow: [describe workflow] where automation could improve efficiency.”

Examples of ChatGPT prompts for Predictive analytics

Project success probability: “Analyze the likelihood of success for [project name] based on historical data: [list of project attributes, e.g., budget, duration, team size, risk factors]. Provide insights into key success factors.”

Timeline optimization: “Analyze the provided project schedule: [attach project schedule]. Use predictive modeling to recommend an optimized timeline with reduced risk of delays.”

Cost overrun analysis: “Use predictive analysis to identify the probability of cost overruns for [project name]. Consider factors such as [budget, resource allocation, historical variances].”

Risk probability scoring: “For [project name], using these identified risks: [list of risks and their attributes], calculate the probability and impact score for each risk. Suggest mitigation strategies.”

Portfolio performance forecast: “Predict the performance of this project portfolio: [attach portfolio data]. Include metrics such as ROI, resource utilization, and time-to-delivery.”

Examples of ChatGPT prompts for Agile Project Management

Sprint planning assistance: “For [project name], based on the current backlog: [list backlog items], suggest a sprint plan for the next [number] iterations. Include task prioritization and estimated story points.”

Epic breakdown suggestions: “Provide a breakdown of this epic: [epic description]. Suggest smaller user stories that align with Agile principles.”

Scrum Master guidance: “Draft a checklist for the Scrum Master to facilitate an efficient daily stand-up meeting. Include focus areas such as [blockers, progress updates, and sprint goals].”

Burndown Chart analysis: “Interpret this burndown chart: [attach or describe chart]. Highlight potential risks to sprint completion and suggest corrective actions.”

Agile metrics reporting: “Create a report template for Agile metrics tracking. Include fields for [velocity, cycle time, lead time, and cumulative flow].”

Backlog prioritization: “Using these backlog items: [list items with descriptions], recommend a prioritization strategy based on [criteria such as business value, complexity, and dependencies].”

Conclusion

We are all boarding the AI train. Whether it’s streamlining planning and resource allocation or acting as a virtual assistant for content creation and data analysis, AI is reshaping how PMOs and Project Managers approach their responsibilities.

However, AI should not be seen as a threat to your role. Instead, view it as a tool to enhance your capabilities. By using AI responsibly and aligning it with clear objectives, you can tackle daily challenges more effectively, make better decisions, and focus on what truly matters: delivering successful projects and achieving business results.

The future of Project Management is undeniably intertwined with Artificial Intelligence. Are you ready to take your Project Management to the next level?

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FAQ AI in Project Management

How to make the prompts in this article provide valuable answers for your work in Project Management?

Make sure you have the GPT-4o version. If you don’t, the subscription is only 20 euros/month, so it’s well worth it.
Most of the prompts we have provided require you to fill in information in the brackets (such as project type, task list, resources, etc). The more information you provide, the better.
If you are not clear about the type of information you need to provide, or if the results ChatGPT gives you are not entirely satisfactory, try using this prompt to refine and improve the prompts you are using.

“I need your help to validate the quality and value of this ChatGPT prompt. You are a project management professional with a strong background in Artificial Intelligence. You are an expert in creating detailed and relevant prompts to optimise all Project and Portfolio Management processes.

The prompt I will provide you with to refine and improve it is as follows:

[ INSERT PROMPT HERE ]”

As you can see, the prompt asks you to fill in some information. Based on your experience as a Project Manager, fill in all the missing information in the prompts, so I can check how this prompt would look like.

This approach ensures higher-quality responses from ChatGPT.

Will AI replace traditional project management and PPM tools?

No. AI complements these tools by adding features like automation and predictive insights. Together, they optimize efficiency while leaving strategic decision-making firmly in human hands.

How do I choose the right AI tools for my project management needs?

Identify specific challenges you want to address (e.g., automation, risk prediction, resource allocation).
Evaluate tools based on their features and alignment with your workflows.
Ensure they integrate seamlessly with your existing platforms.
Prioritize scalability to meet future needs.
Test tools with your team to identify the best fit for your operations.

What skills do project managers need to work effectively with AI tools?

Data and technology literacy: To understand and leverage AI insights.
Critical thinking: To evaluate and contextualize AI recommendations.
Ethical awareness: To ensure responsible use of AI.
Change management expertise: To guide teams in adopting AI-driven processes effectively.