Ever since humans have had people and projects to manage, we’ve had challenges keeping the projects on time, on budget, and people on task. The field and industry of project management emerged as a way to manage a collection of people towards an end goal. For project managers, it is commonplace to be managing not only multiple teams, but also multiple projects at the same time. These projects often must come together towards a bigger goal. For a field that is known for having lots of moving parts, finding ways to make the process easier and more efficient is a primary goal. By creating a smoother process, project managers are able to turn out more reliable outcomes and can even help coach individual employees more effectively. Artificial intelligence is increasingly finding its way into project management tools and technology to handle everything from scheduling to analyzing the patterns of a working team and offering suggestions. These augmented tools make AI an obvious benefit to project managers going forward.

AI, with its unique ability to monitor patterns, is a capable assistant to project managers.. Studies have shown that project managers spend more than half of their time on administrative tasks such as dealing with check-ins and managing updates. AI bots are capable of stepping up and handling these less intensive tasks for the project manager with current systems cutting time spent on busywork in half. This is a significant timesaver, which allows for project managers to focus more on the complex processes behind their management strategy. It also enables them to spend more time focusing on their employees, which can in turn help them to empower their employees and find further efficiencies. There is nothing that will slow a project down more than a project manager who simply does not have the time to speak to every single team member’s needs. With the time saved using AI-enabled project management systems, these managers can focus more on what matters to them. Freeing up that amount of time in a day is not only a great way to help projects move along more efficiently, but it can also make for a more comfortable work environment where employees feel supported and know that they have the appropriate resources in place.

A primary benefit for AI tools when it comes to project management team members is the fact that they can save time on busywork. For most employees, a significant amount of time is put into record keeping, reporting, and various other remedial tasks. Passing these kinds of processes onto AI systems is an excellent way to free up time so that employees can work on their deliverables. This also makes the entire process more efficient, which can in turn save on time and budget costs by allowing employees to focus on the tasks that really matter.

Those who have implemented hundreds or even thousands of AI projects realize that despite all this diversity in application, AI use cases fall into one or more of seven common patterns. The seven patterns are: hyperpersonalization, autonomous systems, predictive analytics and decision support, conversational/human interactions, patterns and anomalies, recognition systems, and goal-driven systems. Any customized approach to AI is going to require its own programming and pattern, but no matter what combination these trends are used in, they all follow their own pretty standard set of rules. These seven patterns are then applied individually or in various combinations depending on the specific solution to which AI Is being applied.[1]

Project management has emerged because the characteristics of our contemporary society demand the development of new methods of management. Of the many forces involved, three are paramount: (1) the exponential expansion of human knowledge; (2) the growing demand for a broad range of complex, sophisticated, customized goods and services; and (3) the evolution of worldwide competitive markets for the production and consumption of goods and services. All three forces combine to mandate the use of teams to solve problems that used to be solvable by individuals. These three forces combine to increase greatly the complexity of goods and services produced plus the complexity of the processes used to produce them. This, in turn, leads to the need for more sophisticated systems to control both outcomes and processes.

PMBOK Guide (6th Edition) Processes Flow

Applying Forbes 7 Patterns of AI to PMBOK Processes Flow

Potential Use Cases:

• Report Progress and task status can be tracked automatically and alerting the project manager in the exception-based scenarios
• Machine learning algorithms can be used to provide estimates of the duration and resource requirements for project activities based on expert knowledge and lessons learned from previous projects
• Machine learning algorithms are capable of giving recommendations on prioritizing projects based on data from previous projects
• Cost assumptions and time constraints can be examined by combining current project data with historic data to run multiple scenarios and generate, assess and rank viable outcomes
• AI can enhance Human Capital Optimization (a new form of HRMS) by calculating the best allocation of resources, Identifying the right skill for the right job, pinpointing training needed for a specific employee, predicting resources excess or shortage, providing feedback about the project manager’s behavior and competency
• Can schedule a meeting and manage time
• Chat-bot can take over menial tasks such as organizing meetings, listening to meetings to assign tasks to people with target dates, send out actions and follow-up.
• Collects details from meeting and keep track of stakeholders
• Analyzing component data may also help to predict which parts are likely to fail quality control.
• Computer Vision can be used to monitor the progress of construction sites, monitor remote work force etc.,

AI Project Assistants

• (1st Gen) Narrow project assistants: Early project management AI will be a project assistant focused on a narrow area of managing a project or team. By focusing on supporting a team in one specific area rather than dealing with all the complexities involved in managing a project, project management AI will be useful to teams sooner rather than later.
• (2nd Gen) Expanding project understanding: As the assistants expand their understanding, new metrics will be revealed that weren’t previously possible, such as quality, performance, learning, change, and effort. With more data points about projects, predictions will become more reliable, more appropriate, and easier for PMs. to understand.
• (3rd Gen) Filling in the data gaps: With new meta-data, improved data suitability, and quality, as well as a broad understanding of the various problems on projects, project management AI will be able to deliver meaningful advice.” to help PMs.

Overview of IBM Cloud Pak for Data

IBM® Cloud Pak for Data [2] is a cloud-native solution that enables you to put your data to work quickly and efficiently.

Your enterprise has lots of data. You need to use your data to generate meaningful insights that can help you avoid problems and reach your goals.

But your data is useless if you can’t trust it or access it. Cloud Pak for Data lets you do both by enabling you to connect to your data, govern it, find it, and use it for analysis. Cloud Pak for Data also enables all of your data users to collaborate from a single, unified interface that supports many services that are designed to work together.

Cloud Pak for Data fosters productivity by enabling users to find existing data or to request access to data. With modern tools that facilitate analytics and remove barriers to collaboration, users can spend less time finding data and more time using it effectively.

And with Cloud Pak for Data, your IT department doesn’t need to deploy multiple applications on disparate systems and then try to figure out how to get them to connect.

Overview of IBM Maximo Visual Inspection

IBM Maximo Visual Inspection [3] , formerly PowerAI Vision, is a video/image analysis platform that offers built-in deep learning models that learn to analyze images and video streams for classification and object detection.

IBM Maximo Visual Inspection includes tools and interfaces that allow anyone with limited skills in deep learning technologies to get up and running quickly and easily. And because IBM Visual Insights is built on open source frameworks for modeling and managing containers it delivers a highly available platform that includes application life-cycle support, centralized management and monitoring, and support from IBM.

High Level Architecture — IBM Components

Conclusion:

A more complex potential with this is AI’s ability to monitor human beings and make predictions based off of the patterns that it sees. AI systems can observe projects and individual team member behavior, and can pick up on certain habits and nuances with team members that might be otherwise overlooked. This makes it possible for artificial intelligence to recognize when something is occurring that is likely to lead to scheduling conflicts and makes it possible to offer up suggestions on alternate completion dates if the scheduling is off track. It also means that the system may be able to help offer personalized coaching for employees based off of learned habits. These systems might even someday be able to account for the conflicts with a remote employee working in a different time zone and make educated adjustments based off of that. These systems can go so far as to identify when someone is doing something out of compliance, which opens them to the possibility of recognizing potential instances of fraud and other kinds of issues that might arise.

AI — A Virtual Partnership

Over time, it seems likely that AI-enabled project management systems will be able to make the science of human behavior more concrete in various ways. A system that is capable of analyzing someone’s every move is likely to be more reliable in predicting actions or potential needs than an individual person might be. AI holds the key to helping management understand the distinctive nuances that are likely to come with individuals who are working with their own patterns. In the same way AI can identify a user profile for a shopper and act accordingly, these systems can help provide customized aid to employees working on a project, as well as project managers. Overall, the potential benefits of bringing AI into the project management space are significant.

[1] https://www.forbes.com/sites/cognitiveworld/2019/09/17/the-seven-patterns-of-ai/?sh=2db6b88d12d0

[2] https://www.ibm.com/support/producthub/icpdata/docs/view/overview/SSQNUZ_latest/cpd/overview/overview.html?t=Overview%20and%20architecture&p=overview

[3] https://www.ibm.com/support/pages/ibm-maximo-visual-inspection#overview