On average, only 35% of the projects are completed successfully nowadays. One main reason for this displeasing rate is that the technologies accessible for project management have lesser levels of maturity. But this is almost to transform. Researchers, innovating organizations, and startups have started to apply machine learning, AI, and other up-to-date technologies in project management. By 2030, the project management field will experience major shifts. Very soon, technology will improve project prioritization and selection, monitor progress, facilitate testing, and speed up reporting. Aided by the virtual project assistants, the project managers can focus more on stakeholder management and coaching than on manual tasks and administration. This article shows how companies that need to reap the usefulness of technologies of project management should commence now by gathering and then cleaning the project data, training their team, and dedicating the necessary resources for driving this transformation.

How Project Management is today and way ahead

Roughly $48 trillion is funded in projects every year. Yet, as per the Standish Group, just 35% of the projects have been considered successful. The unrealized benefits and wasted resources of the remaining 65% are mind-blowing.

Research says that a very low level of advancement in the technologies available for project management is one of the major causes of the poor success rates of the project. Most of the project leaders and organizations are still using slides, spreadsheets, and many different applications that haven’t been developed much in the past few years. These applications are sufficient when you are estimating the success of the project by deadlines met and the deliverables. However, they lack in a setting where initiatives and projects are constantly adapting and changing the business continuously. There is improvement in the applications of project portfolio management, but team collaboration capabilities, planning, “intelligent” features, and automation are still falling short.

If the application of AI and other latest technological innovations in project management could enhance the project’s success ratio by only 25%, it would be equal to billions of dollars worth of value and help individuals, societies, and organizations. 

When will AI & new tech revolutionize project management?

Gartner’s research shows that this change will be coming soon, predicting that by 2030, around 80% of the tasks of project management will be regulated by Artificial Intelligence (AI), boosted by Machine Learning (ML), natural language processing, and big data. Few researchers and startups have already developed algorithms to use AI/ML in project management. When we adopt these tools of the next generation, then we can see radical transformations.

AI disrupts 6 areas of project management!

These coming developments in technology are an opportunity that we have never experienced before. Project leaders and organizations who are most ready for such instances of disruption will abide to reap the benefits. AI transforms EVERYTHING in project management: planning, processes, & people. We shall understand the six key areas below:

  • Reasonable selection and prioritization

Prioritization and selection are a kind of prediction: what type of projects will fetch the most worth to an organization? When the data is available correctly, ML will detect patterns that won’t be discerned by any other means and will vastly exceed the accuracy of humans in making predictions. This ML-driven prioritization soon results in:

  • Quicker identification of projects that are ready to launch and have correct fundamentals in place.
  • Choosing projects that have a greater success rate and deliver the maximum benefits.
  • Finer balance in the portfolio of the project and overview of the risk in the company.
  • Removal of human preferences from making decisions.
  • Support for PMO (Project Management Office)

Automation and data analytics startups are currently helping organizations optimize and streamline the role of PMO. These latest intelligent tools will radically transform the way PMOs will operate and enact with:

  • Monitoring in a better way the progress of the project
  • The capability of anticipating potential crises and addressing a few simple ones spontaneously 
  • Automated preparation and allocation of the project reports and then gathering of the feedback
  • Greater refinement in choosing the best methodology for every project.
  • The compliance monitoring for policies and processes
  • Automation, through virtual assistants, for supporting functions like risk assessment, stakeholder analysis, and status updates
  • Faster, improved project definition, planning, reporting

Project management automation is taking risk management to a new level. New applications leverage machine learning and big data to empower project managers and leaders to foresee risks that might otherwise slip through the cracks. These tools can not only recommend mitigating actions but will soon be able to automatically adjust plans to circumvent specific types of risks.

Similar approaches will facilitate the planning, definition, and reporting of the project soon. These exercises are currently mostly manual, repetitive, and time-consuming. Plain text output, natural language processing, and ML will lead to:

  • Improved scoping of the project by automating the most time-consuming analysis and collection of user stories. All these tools will indicate potential problems like duplicates, omissions, complexities, inconsistencies, and ambiguities.
  • Tools for facilitating scheduling processes, drafting detailed strategies, and resource needs.
  • Automated reporting is built with less labor, and it supersedes today’s reports – which will usually be weeks aged– with real-time data. The tools will drill deeper than what is currently possible, demonstrating the project status, potential slippage, benefits achieved, and sentiment of the team in a clear, factual manner.
  • Virtual project assistants

ChatGPT reversed the world’s insight into how AI analyzes massive collections of data and results in immediate and novel understandings in plain text—tools like these power “virtual assistants” or “bots” in project management. Recently, Oracle announced a new digital assistant for project management, which provides status updates instantly and enables users to update the time and the task progress via chat, voice, or text.

Project planning data, past time entries, and overall context feed into the digital assistant’s learning process. This allows it to tailor interactions and cleverly capture crucial project information. PMOtto, a virtual project assistant powered by machine learning, exemplifies this approach. Imagine you tell PMOtto, “Schedule Albert to paint the walls this week, and give him the task full-time.” The assistant might respond with, “Previous similar tasks assigned to Albert suggest he needs two weeks, not one, to complete this. Should I adjust the schedule accordingly?”

  • Enhanced testing software and systems

Testing is another vital task in most of the projects. Project managers should test often and early. It’s rare nowadays to find a notable project without any multiple systems and kinds of software that have to be tested before it goes live. Shortly, advanced testing systems only feasible for specific megaprojects will become available widely.

The Crossrail project in the UK involved building the Elizabeth Line, a complex railway system with entirely new tracks, infrastructure, trains, and stations. To guarantee reliability and safety, every component of this project underwent a rigorous commissioning process and testing. The project’s unique blend of software and hardware presented unseen challenges. However, the project team rose to the occasion by developing the Crossrail Integration Facility. This fully automated offsite testing facility has demonstrably improved the system’s efficiency, resilience, and cost-effectiveness. Additionally, the facility conducts rigorous audits 24/7, eliminating the potential for operator bias.

For software projects, automated and advanced system testing solutions will soon let the early self-correcting process and detection of defects. This will greatly reduce the reworks in number, reduce the time spent on the cumbersome testing activities, and ultimately deliver bug-free and easy-to-use solutions.

  • The new role for project managers

For most project managers, computerizing a substantial part of their everyday tasks might feel scary, however, successful ones learn to take advantage of these tools. The project managers aren’t going away. However, they should embrace these transformations and then take advantage of new technologies. We think about cross-functional groups of a project as a team of individuals, but soon, we might think about them as a team of robots and humans.

With the transition away from administrative tasks, the future project manager has to cultivate leadership capabilities, business acumen, soft skills, and strategic thinking. They need to focus on the provision of expected gains and their order with the strategic goals. Project managers also require a better understanding of these tools. Some companies have been assembling AI into their certification programs and education in project management already. Northeastern University has been including AI in its curriculum and teaching project managers to utilize AI to improve and automate data sets and enhance investment values.

Data and people will make the future into reality. 

How to make sure that your company is ready for these tools even though the tools are already ready for the organizations? An AI adoption process will begin with the data. However, it would help if you didn’t fail to prepare the people, too.

Large amounts of project data are essential to train AI algorithms for project management. While your organization likely has a wealth of historical project data, it’s probably scattered across various systems, duplicated in thousands of copies, and stored in a multitude of formats. This data could be outdated, have gaps, contain outliers, or use inconsistent classification systems. A significant portion of the time spent preparing the machine learning (ML) algorithm for use (roughly 80%) will involve collecting and cleaning this data. This means transforming unstructured and raw data into a structured format suitable for training the ML model.

In the absence of properly managed data, AI transformation in your organization will never happen. However, AI transformation will not succeed if you don’t prepare yourself and the members of your team for this transition.

Lead Teams with AI

The rise of AI project management tools isn’t just about technology – it’s a complete overhaul of how we approach projects. Project managers will need to coach and train their teams, focusing on human connection. Identifying skill gaps in new technologies is crucial to address.

Project managers must also prioritize creating high-performing teams equipped with the right tools to excel. Here’s a self-assessment to see if your company is AI-ready:

  1. Can you dedicate resources to data collection and cleaning?
  2. Are you prepared to create an accurate, up-to-date project list?
  3. Will you invest in training your team on this new technology?
  4. Are you ready to ditch outdated practices like monthly reports?
  5. Can your company embrace change and adapt to new technology?
  6. Is your project management team comfortable shifting their approach?
  7. Does strong leadership exist to guide this transformation?
  8. Are you willing to allow for AI learning through potential mistakes?
  9. Can senior leaders wait for automation’s long-term benefits?

Answering “yes” to all these questions is key for a smooth transition. AI in project management automates low-value tasks, freeing project managers and leaders to make better decisions.

As we have understood, the AI application in the field of project management brings significant benefit in the low-value and administrative tasks’ automation, comprising AI and the other troublesome technologies in the toolbox to help your company, project managers, and leaders select, implement, and define the projects more successfully. For more insights and resources on project management careers, visit Shri Learning