What’s In Store For The Future Of AI In Project Management?

Artificial intelligence is getting into every corner of work, project management is no exception. Gartner anticipates that it will eliminate 80% of today’s manual project management tasks by 2030. Meanwhile, the PMI has predicted that AI in project management will impact the field by increasing job opportunities for PMs. What’s next?

Traditional PM functions such as planning, data collection, tracking, and reporting, so important to the business health, will be taken over by smart machine learning algorithms. The good news is that the AI-powered platforms available on the market are starting to meet the requirements of digital business. Forecast, being the first in a class of its own to automate project planning, has just raised $5.5 million of investments to move the needle forward in this direction.

This very moment, Forecast has learned from more than 40,000 projects and helped make future estimates of task duration of more than a million tasks. What makes the platform stand out in the sea of software options is a set of algorithms that can learn and adjust for the future. Its main plus though is connecting all the bits and pieces into one unified solution to plan, budget, run, and track projects. All in all, you can manage a project from start to finish—AI in project management helps you become more accurate and precise with your project forecasts. Let’s take a proper look at the functions that have already been augmented and see what’s yet to come.

AI Provides Future Estimates Of Budget And Task Duration

In project management, even the smallest details like task estimates matter when they start piling up. Routine work like ballpark estimation ultimately affects the workflow, the budget, and the project’s health. This is where AI’s regression models come in especially handy. Eventually, whom would you trust making project estimates? Your gut feeling or artificial intelligence? Based on historical data from previous projects, Forecast suggests how many hours (or story points) a task might take to finish. Planning projects this way, managers have fewer budget overruns in the end because AI does the tricky prediction job for them.

Using AI in project management during the planning stage, you apply it straight into the decision-making process and eliminate the guesswork and risks associated with long-term planning. Professional service companies that want to become more data-driven and productive would benefit from giving AI a chance.

AI Issues Risk Alerts On Project Progress

During the execution phase of the project, you would like to know if the project is on track before it crosses the budget line. Data scientists at Forecast have figured out how to notify you if the project or budget starts to slip or if your resource allocations don’t match the workload. Every time something goes wrong in terms of estimates or time registrations, the anomaly is detected and the platform starts warning project managers of the potential threat in different places. CFOs can even see it in the newly released budget page as it affects the actual finances, compared to planned. Everyone in the company can benefit from the way AI augments work.

There’s the significant long-term value you can gain from artificial intelligence today even managing a single project. However, the above setup would be more relevant for program and portfolio managers who are more likely to get confused and disoriented among a ton of tasks they should keep an eye on across multiple projects. AI gives them confidence when they build synergies between projects and makes sure no shifts have been overlooked.

An example of AI in project management: Forecast software resource warnings.
Data scientists at Forecast have figured out how to notify you if the project or budget starts to slip or if your resource allocations don’t match the workload.

AI Automates Time Registrations

When it comes to the way employees work, they often spend plenty of time doing record-keeping and other remedial tasks. Passing those administrative tasks to AI, employees could focus even more time on deliverables and provide more value to the project. While AI helps management predict and execute more profitable projects, it also makes it easier for the teams to register time. Using the power of predictive analytics, teams working in Forecast can enable prepopulated timesheets with the suggested hours of work. It means that the automated time and task will appear in their time card. In this case, the AI learns from your previous week’s work to help a person log time faster. This way AI translates a routine, almost hated responsibility of registering time into a fun task to do at the end of the day.

Ai in project management: pre-populated timesheets with suggested work hours
In this case, the AI learns from your previous week’s work to help a person log time faster.

What’s Next For AI In Project Management?

As the need for human input has been slightly eliminated in the planning and execution phases of project management, there’s still much more to be done, and the next generation of automation is coming. In the not-too-distant future, augmented tools might move in the direction of changing the conversation around who should be doing what. Under this scenario, the AI will assist project managers at the beginning of the project lifecycle learning how to appoint the right team members to tasks. At this point, you should look for an available person with the right skill set to work on the approved tasks. In the future, you’ll be able to cut the time spent on such project management tasks in half. Optimizing dates and tasks to finish your project as fast as possible is another part of the AI game that is currently in development.

Business efficiency is highly dependent on how project management has been set up from the beginning. In short, AI in project management is an obvious asset because it provides guidance in managing complex project portfolios and makes sure you are on the right track from the beginning. It has visibility in places where project managers lack it and allows systems to track how and when the project is moving. Predictions, in turn, may help both plan the project and educate teams on how to work and register time honestly on the tasks. AI uncovers insights people can overlook when the projects shift because they can’t be seen directly. Luckily, augmented tools like Forecast have already got this challenge covered. You’re welcome to see it in action here.

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