In today’s rapidly evolving digital landscape, project management continues to play a crucial role in ensuring the successful execution of strategic initiatives. With Artificial Intelligence (AI) reshaping how projects are planned, delivered and monitored, we’re seeing exciting opportunities for organizations to drive efficiency, increase productivity and enhance decision-making processes.
According to Gartner, 80% of today’s project management tasks will be eliminated by 2030 as big data, Machine Learning (ML) and Natural Language Processing (NLP) empower AI to perform data collection, tracking, reporting and predictive analysis.
Whether you’re a seasoned project manager or just stepping into the field, understanding these AI-driven shifts will undoubtedly shape the way you approach projects and excel in project management.
1. Planning and scheduling
By analysing resource availability and task dependencies, AI tools can create accurate and optimized project schedules that align with objectives and deadlines.
They can also adjust them based on changing circumstances, ensuring successful project execution.
What’s out there?
Using your input and goals, monday AI uses automated task generation to create project plans. The AI assistant is currently in beta testing and is gradually being rolled out to select users.
2. Task automation
By harnessing AI-powered automation, project managers can redirect their focus from mundane, repetitive tasks towards more strategic and value-driven activities.
Routine responsibilities such as data entry, status updates, and scheduling can be efficiently handled by AI systems, freeing up valuable time and resources. This not only boosts productivity, but also minimizes the risk of human error.
What’s out there?
Trello’s Butler is an AI-powered tool that assists with automating various tasks, processes and workflows. It allows project managers to set up custom or predefined rules, buttons and commands, helping teams automate routine actions within Trello boards.
3. Resource management
AI-driven tools assist with allocating resources to tasks based on skill sets, availability, and workload.
They can also forecast needs for future projects and identify peak demand periods, making it possible for project managers to assign resources strategically and helping to prevent overallocation, shortages or bottlenecks.
What’s out there?
Asana’s Workload feature uses AI to distribute tasks among team members based on their capacity, availability and estimated effort, ensuring that work is evenly distributed and meets deadlines.
4. Communication and collaboration
AI-powered chatbots and virtual assistants enhance team communication by providing real-time updates, answering common queries, and facilitating effective collaboration among members and across different time zones.
Through Natural Language Processing (NLP), project managers can conversationally interact with AI systems, simplifying data retrieval and updates.
What’s out there?
Among several other features, Microsoft 365 Copilot assists with summarising lengthy email threads and drafting quick responses in Outlook, as well as running more effective meetings by creating agendas based on chat history, organizing discussion points and distributing key actions.
5. Risk management
By leveraging advanced algorithms, AI can identify patterns and potential issues that might go unnoticed using manual methods.
With automated alerts and continuous data analysis, project managers can swiftly detect emerging risks and take proactive measures to minimize their impact. This empowers them to assess and prioritize risks accurately, devise mitigation strategies and safeguard project outcomes.
What’s out there?
Alongside predictive scheduling, LiquidPlanner’s Schedule Insights alert project managers to potential schedule and workload risks as they unfold. It then takes it a step further by illustrating potential consequences and providing data to facilitate issue resolution for optimal results.
6. Budget and cost management
Through real-time visibility into project finances, AI supports project managers in identifying potential cost overruns, anomalies and areas for optimization. This is done by analysing historical spending patterns, vendor costs and resource utilization while taking into account project progress and external factors.
Early warnings about budget deviations means strategies can be adjusted and resources can be allocated more effectively. Additionally, AI can help automate expense or budget approvals through workflows that adhere to predefined criteria.
Equipped with AI-generated insights, project managers are able to make informed choices, maintain tighter control over costs, and deliver projects within budget, which cultivates financial success and project excellence.
What’s out there?
In a recent update, Scoro introduced enhanced financial project insights, helping project managers track and forecast budgets through the use of dynamic charts where overservicing and overutilization can be easily identified ahead of time.
7. Predictive analytics
AI can predict project outcomes by assessing historical data and patterns, and comparing them to current progress.
This insight gives project managers the ability to align strategies with data-driven forecasts, helping them to anticipate potential delays, budget overruns or scope changes, take corrective action promptly and proactively mitigate issues before they escalate.
What’s out there?
Leveraging their machine learning prowess, Wrike’s Work Intelligence® solution detects recurring project issues and historical trends, offering a comprehensive assessment of potential risks to ensure projects run smoothly.
These developments illustrate the immense potential for AI to revolutionize the industry, drive project success and allow project managers to focus on higher-value activities such as strategic planning, stakeholder engagement and fostering team collaboration.
As organizations look to maximize their project outcomes in a competitive landscape, harnessing the power of AI is becoming indispensable. The successful integration of AI in project management requires a careful balance between utilizing technology and leveraging human expertise.
This post was previously published on Medium.com.