Using Artificial Intelligence for Project Management

“Project management is not just about managing projects anymore. It’s about steering your organization toward a future that’s defined by intelligent technology and strategic excellence,” says Dr. Rich Sonnenblick, chief data scientist at Planview.

Artificial intelligence assistants, like Planview Copilot, are ushering in a long-overdue transformation in the world of project management.

For decades, project managers have had to rely on the same static tools to perform their jobs – slides, spreadsheets, and documents, all retrofitted to perform the role of communicating necessary project information. Using these tools required immense manual effort on behalf of project managers and project teams.

AI is poised to handle many of the administrative and data-processing aspects of project management. This frees project managers to spend less time on routine tasks and more time on strategic thinking, leadership, and complex problem solving – the tasks that only humans can do.

AI and machine learning can take the load off project managers by accelerating various aspects of the project life cycle, such as:

• Automating routine tasks
• Providing data-driven insights for decision-making
• Predicting potential issues or outcomes
• Optimizing resource allocation and scheduling
• Improving risk assessment and management
• Upskilling employees quickly

The possibilities for leveraging artificial intelligence in project management are truly endless – helping project managers make more informed decisions, increase efficiency, and improve project outcomes.

The application of artificial intelligence to project management is still in its infancy. But after looking at just a brief history of AI, you can see how the pace of change is accelerating. AI is expected to usher in a massive overhaul of the industry by the end of the decade.

• By 2026, 70% of job titles will shift from a portfolio, program, project (3P’s) hierarchy to role-based descriptors due to the increase of AI in strategic portfolio management.
• By 2028, PMO leaders will rely on AI to predict project delays and budget overruns with an accuracy of over 90%, enabling proactive mitigation strategies and increasing portfolio resilience.
• By 2030, 80% of project management (PM) work will be eliminated by AI.

Source: Gartner Report: Build a Generative AI Roadmap for Your Portfolio Management Life Cycle, 1 July 2024, ID G00795336

It’s important to consider each of these predictions in this context: AI is meant to enhance human capabilities, not replace them. Project management involves many aspects that AI can’t replicate, such as emotional intelligence, stakeholder management, and creative problem-solving in unique situations.

One day, AI could eliminate 80% of the manual, tedious work that project managers do to maintain inefficient systems.

By embracing AI and developing skills to leverage it effectively, people involved in the project lifecycle can position themselves as invaluable assets in the evolving field of project management. As AI takes over routine tasks, new roles will emerge. Project managers who adapt and learn to work alongside AI will be in high demand for their combined human and technological expertise.

Instead of ignoring AI, consider how you can upskill to work effectively with AI tools. This might involve learning data analysis, AI implementation, or focusing on developing your uniquely human skills.

Applying AI to project management involves integrating AI-powered software and techniques into various aspects of the project lifecycle. Here are seven examples of how AI can be applied to project management in practice:

Planning and scheduling

Artificial intelligence can make planning and scheduling in project management more efficient and more accurate. Project managers can use AI algorithms to analyze historical project data and create optimized schedules and implement machine learning models to predict task durations and dependencies.

Resource management

AI can enable more efficient resource management in project management. Project managers can use AI to match team members’ skills with project tasks, or predictive analytics to forecast resource needs and availability.

Risk management

AI can help project managers proactively reduce risk. Using natural language processing, AI can scan project documents and identify potential risks. Machine learning can be used to assess risk probabilities and potential impacts.

Project monitoring

To monitor projects, project managers can implement AI-powered dashboards for real-time project status updates and use computer vision to track progress on physical project components.

Decision support

PMs can also leverage AI for decision support: For larger decisions, AI can analyze multiple scenarios and recommend optimal courses of action. PMs can also use chatbots or virtual assistants to provide quick answers to project-related queries.

Task automation

Artificial intelligence can lift some of the burden of task automation. PMs can implement robotic process automation (RPA) for repetitive administrative tasks and use AI to automatically update project documentation and reports.

Predictive analytics

Using AI for predictive analytics can reduce risk, save time, and save effort. Project managers can apply machine learning models to forecast project outcomes, delays, or cost overruns, and use AI to identify potential bottlenecks or issues before they occur.

Upskilling talent

AI can quickly upskill talent by reducing the time it takes to ramp someone up on a job, product, or solution. AI helpbots can access product, solution, or other information quickly and efficiently.

Implementing artificial intelligence in project management boosts speed, productivity, and effectiveness, reducing the effort required to plan, monitor, and deliver projects. This frees project managers to spend more time on the high-value, strategic work that only humans can do.

The project manager of the future will work in harmony with artificial intelligence, passing off the manual, tedious, and repetitive tasks that once occupied much of their time to intelligent tools.

The key benefits of artificial intelligence in project management are:

• More efficient planning and scheduling
• Improved risk assessment and mitigation
• Enhanced resource optimization
• Insightful predictive analytics
• Efficient task automation
• Enhanced decision-making
• More accurate cost estimation

Finding an AI tool that works seamlessly with existing project management tools can help project managers maximize the benefits of artificial intelligence. For example, Planview Copilot is a generative AI-powered assistant integrated into Planview’s portfolio and work management solutions. Designed to aid users with project management tasks, Planview Copilot leverages generative AI technology to enhance decision-making, improve efficiency, and automate routine processes.

Getting started with applying artificial intelligence to project management can seem intimidating, but it doesn’t have to be. Follow these five steps to apply AI to your work.

Select appropriate AI-powered project management software and tools.

Begin by assessing the specific needs of your organization. Research and compare various AI solutions, focusing on features like predictive analytics, automated reporting, and natural language processing.

Integrate AI solutions with existing systems.

Start by mapping out how the AI software will interact with existing tools, such as your CRM, ERP, software development, or communication platforms. Work closely with IT professionals to ensure compatibility and to address any potential integration challenges. Proper integration allows AI to pull data from all relevant sources, providing a holistic view of your projects and enabling more accurate insights and recommendations.

Train team members on using AI-enhanced software and interpreting AI-generated insights.

Training your team is crucial to fully harnessing the power of AI in project management. Organize training sessions that cover both the technical aspects of using the AI software and the analytical skills needed to interpret AI-generated insights. Ensure that team members understand how AI can augment their work, from automating routine tasks to providing data-driven recommendations.

Ensure data is safe, secure, and protected.

Implement robust cybersecurity measures to protect sensitive information from unauthorized access, breaches, and data loss. This includes using encryption, secure user authentication, and regular security audits. Make sure that the AI tools you select comply with industry standards and regulations, such as GDPR or CCPA, to safeguard personal and project data.

Continuously feed project data into AI systems to improve their accuracy and effectiveness.

AI systems thrive on data, becoming more accurate and effective as they process more information. Continuously feeding project data into your AI tools allows them to learn and improve over time. Regularly reviewing and refining the data inputs can help the AI system adapt to changing project environments and provide more relevant insights.

By maintaining a steady flow of accurate, up-to-date data, you enhance the AI’s ability to predict trends, identify risks, and recommend strategies, ultimately leading to better project management decisions.

Artificial Intelligence and Automation in Project Management

Artificial intelligence automation can include automated task assignments and reminders, automatic data collection and reporting, Robotic Process Automation (RPA) for repetitive tasks, and automated progress tracking and status updates.

Leveraging AI and automation in project management can result in increased efficiency and productivity, more accurate planning and estimation, reduced human error in routine tasks, data-driven decision making, and improved resource utilization.

Project managers can leverage AI and automation in several parts of the project lifecycle.

AI and automation can be used in project planning and scheduling, resource management, risk management, budget tracking and cost estimation, team collaboration and communication, and performance monitoring and reporting.

However, be mindful of the following common challenges associated with AI and automation:

• Integration with existing systems: Make sure that the automations integrate well with other tools in your system.
• Data quality and consistency: Ensure that the automation will reliably transfer data with accuracy and consistency.
• Team adoption and change management: It may take teams time to get used to new automation workflows. Prioritize training and check-ins to make sure teams feel comfortable and confident using any new automation.
• Balancing automation with human oversight: Too much automation without human oversight can increase risk. Take care to ensure there are checks and balances in place to monitor systems.

If you’re looking to simply start using AI tools in project management, many tools exist. However, rather than piecing together AI tools, it is far more effective to utilize an integrated, AI-powered platform.

Generative AI assistant

Planview Copilot allows you to converse with and query your data using natural language to glean insights, derive recommendations based on best practices, and inform strategic decisions.

AI help and upskilling

The AI help in-app interface provides plain text answers to your questions, giving you quick access to answers across thousands of customer success center help articles and other product- or solution-specific documentation.

Sentiment analysis

Sentiment analysis can help you understand whether a product, project, or work item is truly on track by analyzing the emotional tone and sentiments of comment and status texts, as well as computational linguistics behind aggregated comments over time. You can use these scores to reveal positive, neutral, or negative insights and make pivots before delivery is impacted.

Summarizers

AI summarizers can help you save time, enhance knowledge, and provide actionable information by summarizing risks, issues, and work in progress, and even building release notes with the click of a button.

Optimizations and simulations

Scenario planning allows you to explore multiple avenues to pinpoint the most efficient and effective allocation of your capital and capacity for peak performance and strategic success.

Although incorporating AI into your work can be an intimidating concept, many find that the conversational format of a generative AI assistant is surprisingly easy to use. Using generative AI tools can save considerable time and effort compared to traditional research methods.

Tools like Planview Copilot use natural language processing, allowing users to interact with the system using natural language queries, making it easier to retrieve information, generate reports, or update project statuses.

Planview Copilot is designed to support project managers and teams in making more informed decisions, improving project outcomes, and increasing overall productivity through AI-driven automation and insights. By simply chatting with Copilot, project managers can enhance decision-making, improve efficiency, and automate routine processes.

Artificial intelligence can be used to enhance both project and portfolio management, but the focus and application differ. In portfolio management, AI can improve project, program, or initiative selection and prioritization; resource optimization; portfolio performance analysis; and scenario planning. Leveraging artificial intelligence in strategic management can aid in decision making, reduce risk, increase visibility, and help teams maintain strategic alignment.

Project, program, or initiative selection and prioritization

AI algorithms can analyze multiple factors (strategic alignment, resource availability, risk, ROI) to recommend which projects to include in the portfolio. Machine learning models can predict project success rates based on historical data to help with selection and prioritization.

Resource optimization

AI can optimize resource allocation across multiple projects, considering skills, availability, and project priorities. Predictive analytics can forecast resource needs and identify potential bottlenecks.

Portfolio performance analysis

AI can provide real-time insights into portfolio performance, identifying trends and anomalies. Automated dashboards can visualize complex portfolio data for easier decision making.

Scenario planning

AI can simulate various portfolio scenarios, helping business and technology leaders understand the impact of different decisions.

Objectives and key results (OKRs)

By integrating OKRs into AI-driven portfolio management, organizations can ensure that their project portfolios remain tightly aligned with strategic goals. This approach combines the goal-setting framework of OKRs with the analytical power of AI, enabling more data-driven, strategic portfolio management.

The challenges of applying AI to portfolio management are like those in project management: First, AI is only as good as the data it’s based on – so data quality and consistency across the portfolio are critical for success.

Integration with existing tools and processes can be tricky and require a holistic approach. Confidence in change management and AI adoption among stakeholders can vary, which can affect outcomes. And finally, it’s always important to maintain a fine balance between AI insights and human expertise and judgment to reduce risk.

For decades, the world of project management has relied on retrofitted tools that required extensive effort to use and maintain. AI is poised to usher in a new era of project management, where project managers are empowered by tools that work for them.

Turbocharge your project management efforts with Planview’s AI-powered platform.