Managing projects is something humans have done ever since there was a reason to delegate a task to someone else. Yet, even in this most human of activities, we're seeing AI gain a foothold. Enterprises are using AI for project management to not only improve the way they create, manage and operate projects, but also to treat their projects as strategic.
Making project management more efficient
Organizations have widely adopted a range of team communication and messaging tools to facilitate, coordinate and centralize group communication. Tools such as Slack and Flock are already well-integrated with popular project management suites, including Jira, Asana and Trello. Many of these offerings now have chatbots that can facilitate much of the project communication tasks that previously required human oversight. For example, these AI chatbots can handle simple, repetitive tasks, such as scheduling meetings or sending activity reminders for team members.
A few years ago, Cisco Spark partnered with Redbooth to transform the way teams interact and run their projects, enabling better planning and real-time collaboration, via bot integration. These bots can also keep tabs on individual worker activities and notify management when these activities are starting to deviate from the expected plan. AI systems are also able to automatically issue alerts when they detect potential budgeting or scheduling issues.
Additionally, AI for project management is helping to reduce overall project costs. According to an Accenture study, managers spent 54% of their time on project management-related administrative tasks. However, organizations now expect AI to cut that time in half, freeing up employees to work on higher-value activities. Intelligent bots are helping to automate project management duties, such as project documentation and quality check activities. They can also interact with workers to provide instant access to the status of various projects, dependencies and critical project-related information. AI chatbots save huge amounts of time in fielding queries and requesting updates.
These intelligent assistants also help reduce the workload associated with keeping track of various project management activities. The use of these automated systems reduces human error and keeps aspects of bias in check by systematically and reliably keeping project management records.
Better project analysis
One of the biggest challenges in project management is having enough data to know how well projects are performing against desired deliverables, objectives and goals. Through the use of predictive analytics and other aspects of machine learning, AI systems can use data that organizations collect about their projects to determine the completion rate of teams and predict the likelihood of them delivering products on time.
AI-enhanced data visualization then helps identify bottlenecks and areas where process improvements or other changes can be applied to improve overall performance. In particular, AI systems are good at pattern matching. With machine learning, AI systems can optimize decision-making by clearing through the noise and clutter of data. They can identify slowly ramping trends in data that may be critical to the business but are hard for humans to observe in the noise of all the project management data.
AI for project management is also helping make project data more useful. Augmenting project management data with other critical profile and data points helps to improve data suitability, quality and understanding. In addition, these AI systems put powerful predictive analytics capabilities into the hands of non-data scientist project managers. This helps make performing value and risk analysis easier and faster and provides more insight-oriented analytics and reports that facilitate more effective project management decision-making.
The intelligent future of project management
The primary job of project managers is to make sure that the strategic vision of senior management is realized through the various activities the business performs. However, project managers spend most of their time on the administrivia of handling projects, rather than shepherding activities in more strategic ways. It's clear that intelligent systems are making a significant impact by eliminating much of the necessary but low-value activity of project management. This type of intelligent assistance can focus the organization on the project at hand and not on the minutiae of project management activities.