Project management is critical to the success of any company. It ensures that deliverables align with the client’s strategic goals and objectives. Good project management can lower overall costs, manage risks, and control quality throughout the project’s lifetime.
However, like any other department in a company, project managers can run into problems and face their own challenges. For instance, if handled improperly, the risks surrounding a project can increase costs and cause delays that could jeopardize the entire endeavor.
Planning a project, setting deadlines, and coming up with a budget can be tricky, especially if the planner is inexperienced or is working with incomplete information.
AI project management is gradually presenting itself as a powerful tool for overcoming many challenges that would have hindered project management earlier.
Let’s take a closer look at AI and see what it can do for project managers.
What is Artificial Intelligence?
Within computer science, there is a field of study called artificial intelligence, or AI for short. This field is dedicated to finding different ways to teach computers how to think and solve problems typically reserved for humans.
The field of AI is a wide one, with several subfields:
- Statistical analysis represents one of the oldest ways to teach machines how to think. In a nutshell, you give the computer plenty of data. With the right statistical methods, you can find meaningful patterns within the data and make predictions with some degree of accuracy. Statistical analysis led the way to the current revolution of Big Data and analytics.
- Machine learning is the study of self-learning algorithms that can develop themselves through experience and learn from available data rather than rely on the help of a programmer.
- Deep learning is a smaller field within the subfield of machine learning that researches self-learning algorithms based on artificial neural networks.
- Artificial neural networks are structures loosely based on a model of how the human brain operates.
What can AI do today?
Before talking about what AI can do today, let’s distinguish between two things: Narrow AI and Artificial General Intelligence.
Narrow AI (also known as weak AI) refers to systems that can simulate human intelligence when it comes to a specific task yet fails to do so with any other tasks. These are specialists that operate under severe restraints and are dedicated to performing a single job. AI systems today are of the narrow kind.
Artificial general intelligence (AGI) is more concerned with replicating human intelligence in a much broader way. It can learn to perform multiple tasks and become proficient in any type of problem it faces. AGI is also known as strong AI.
What is AI project management?
Armed with a clear idea of what AI is and what it can do, we can now look at how AI can help project managers.
AI is supposed to integrate with the already existing software used in project management. It can perform some of the mundane tasks that would normally require a human to do them.
In addition to automating simple tasks, AI in project management should be able to pore over existing data and find useful patterns. With these new insights, project managers will be able to make better decisions while saving valuable time.
However, as things stand today, AI mainly plays an assistant’s role, one who manages very narrow areas of a project.
The role of AI in project management today
Each piece of AI project management software can perform a specialized task. Some tools combine different AI tools, but each tool is still considered narrow AI.
For instance, some software assistants that can recognize speech, take dictation, and perform basic routine activities such as scheduling, sending reminders, and even taking responsibility for follow-ups, all of which would have taken up the time of a human.
Besides saving time, AI project management tools ensure that every little detail is taken care of and that nothing slips through the cracks.
Other tools, such as Stratejos, help with budgeting and sprint management and integrate with other software platforms such as Slack. Some applications help manage the team’s knowledge, reducing the need for redundancies, and ensuring that everyone is on the same page.
None of this is to mention that some AI tools combine several AI functions into one platform.
Additionally, some AI systems specialize in handling large amounts of data, a feat we humans have a hard time accomplishing. Large data sets may cripple us and prevent us from extracting useful insights. However, the larger the data set for an AI system, the better the results will be.
Yet, we are still a little off from a time when machine learning algorithms will be able to observe a project and make useful predictions based on historical data.
The limitations of AI in project management
For starters, one of the biggest issues with AI project management, especially machine learning and deep learning algorithms, is their reliance on data. These algorithms require two things: copious amounts of data and for this data to be clean.
1. The need for large amounts of data
A machine learning algorithm trained on one million data points is bound to do better than an algorithm that has only been trained on ten thousand points. This need for training can be a bit of a hindrance and slow things down.
If a company doesn’t have the minimum amount of required data points to train an AI, it might not be a good idea to develop a machine learning algorithm in the first place. The algorithm will be so inaccurate that it won’t justify the costs of developing it.
One way to bypass the need for training is to use a pre-trained algorithm that has already been trained to perform a specific function. For example, a company might decide to use an image recognizing AI that has already been trained with millions of images pulled from an academic institution’s library.
Even though the pre-trained method might seem to bypass a serious hurdle, it still faces challenges of its own.
For one, the company might have to acquire the license to use this pre-trained AI. If the AI was trained using proprietary data, this will be all the more difficult.
Another problem is that since this will be a generic AI, its predictions might lose some accuracy because it wasn’t trained on the company’s specific data. Also, there are functions and roles where companies will not be able to find pre-trained AI solutions, forcing them to develop their own.
2. The need to clean the noise
Of all the tasks data scientists have to perform, cleaning and preparing the data is both the most labor-intensive and the most time-consuming. It is estimated that cleaning and preparing data for AI constitutes around 70 percent of the total required work.
Several different types of machine learning algorithms, such as unsupervised and anomaly detection algorithms, will only be successful if the data presented to them is clean and well-formatted.
What role will AI play in project management in the future?
The world of AI is continuously advancing. Here are some benefits this progress is bringing for project management:
1. Giving better analysis
As time passes, companies and institutions generate more and more data, which is fodder to feed to AI and machine learning systems. In the future, AI project management systems will be more accurate, and their predictions will be more reliable.
2. Being more intelligent
AI is expected to play a wider role as opposed to its rather narrow function today.
For instance, an AI project management system could process and learn from task descriptions. It could also learn from previous historical data to make predictions about the future of a project.
This will be all the more possible because future AI systems will be able to monitor different gears and cogs in any given project, regardless of size, giving them a clear view of the bigger picture.
Such a task is difficult for a human because the more details there are in a project, the harder it becomes to see the forest for the trees.
An AI project management system that makes predictions would be able to tell if a project were about to go over budget or not from the available data. It might send the project manager a notification that due to this week’s weather forecast, there is a 45 percent chance that the project will go over the deadline by at least a single day.
It could keep a close watch on the supplies and materials, noticing any possible shortages long before they happen.
3. Predicting human behavior
What will even be more impressive is when the AI system can predict human behavior based on past experience. Some AI systems do this today, but, in the future, the AI won’t be limited to the individual’s online presence.
Instead, it will learn from actual observed behavior. The AI system will learn from information fed via a camera, a microphone, or any other kind of sensor. It will be able to integrate this information with the data that is entered by human beings.
Once the AI project management has a lock on each team member’s habits, nuances, and other behavioral patterns, it will be able to tell when a problem might be brewing or when the project might get sidetracked for any reason.
For example, the system might notice that the key engineer is getting distracted from their main job due to having less experienced team members. Better yet, this system will be able to offer suggestions on how to remedy this problem.
4. Coaching employees
Speaking of inexperienced team members, AI systems in the future will be able to offer each team member necessary coaching tailored to help them grow and complete their tasks more efficiently.
This coaching will also factor in each member’s learning habits, ensuring that the coaching sticks for as long as possible.
5. Filling in missing data
In the not too distant future, AI will be able to go even a step further and start filling in missing data. Once the AI systems have been trained well enough, they will spot gaps in data sets and make excellent assumptions about what should be in those gaps. As a matter of fact, AI is already being used to clean data and format it correctly.
The benefits of AI in project management
Having seen the different functions and roles of AI in project management, we are better positioned to talk about the benefits of having AI systems fill these roles.
Here are some ways AI is helping project managers of today reach their goals:
1. AI project management systems can save time and money
Project managers spend, on average, half of their time working on routine and administrative tasks such as managing updates, filling in timesheets, and dealing with check-ins.
However, with the right bot, a project manager can get rid of these time-consuming, straight-froward tasks and pass them off to an AI system that will do the job quicker and with fewer mistakes.
This saves the manager’s time and enables them to direct more of their attention towards pressing strategic and creative issues that an AI system might be unable to solve.
Additionally, managers will have more time to dedicate to their employees. In turn, employees feel more empowered and cared for, increasing their efficiency and becoming more productive.
2. AI can improve the decisions managers make
With machine learning, AI systems should be able to go beyond just making predictions. They should be able to offer advice based on these predictions.
AI systems might not be at that level today. Nevertheless, they can still make decent predictions with the use of predictive analytics.
Even though these prediction models need a lot of data to offer anything actionable or insightful, companies that keep harvesting past data will soon be able to enjoy the benefits that come with strong, reliable predictive models.
3. AI systems can be more efficient than people
Concerning specific tasks, AI project management systems are faster and more accurate. This enables project managers to have more faith in the work done and not feel the need to subject the work to constant revision.
AI systems are always objective, following strict, rule-based workflows. And they are tireless. For example, an AI system will neither feel burned out nor complain that it has too much work on its plate. Instead, it will work diligently, and the quality of its work will remain constant throughout.
The future of AI project management
Business technology is rapidly changing processes across all levels and stages of a business. Here are a few benefits looming on the horizon:
1. AI systems will increase the overall efficiency of a project
Here, it’s not just the quality of the AI’s work that’s at stake; it’s what the AI can do.
For example, AI systems will be able to track different resources and make sure that they are allocated to the tasks that will benefit from them the most.
Moreover, the AI system will detect when a piece of equipment is about to break down or fail for any reason and send a timely notification to the project manager.
To achieve this, AI project management systems will need to integrate with other advanced technologies such as cloud computers and IoT devices. This is why the world has a lot to look forward to with industry 4.0 on the horizon.
When it comes to resource allocation, AI systems will be able to take things even a step further by allocating tasks to individual team members based on their capabilities, strengths, and overall ability to comply.
This will reduce the overall idle time spent by each employee and ensure that the work assigned matches the employee’s energy level.
AI will also help in selecting team members for a specific project. Not only will this increase the revenue per employee, but it will decrease the turnover of the entire company. This is not to mention how helpful the people in HR will find this.
2. AI can help a company manage its risk
In any project, countless risks abound. From creeping scope and inflated costs to workplace safety, project managers have to track many nitty-gritty details to ensure that the entire project sails by smoothly. Fortunately, AI can help.
As mentioned, AI can provide project managers with accurate forecasts, reducing uncertainty, and providing some clarity to a hazy picture. This means that AI systems can be perfect for aiding managers in handling risk.
Most risks are probabilistic in nature, i.e., we never know for sure that something bad is going to happen; we only know that it might.
However, we, as humans, are lacking when it comes to thinking in terms of probabilities. We tend to be overly optimistic when we shouldn’t, and we have a habit of overestimating or underestimating the likelihood of something happening regardless of the actual data.
These are all reasons that make AI well-suited to taking over the task of risk management.
How can companies prepare today?
With all these benefits, it should come as no surprise that several companies are scrambling to incorporate AI into their project management processes.
But, before a company can jump in and start trying to get AI into everything, it should take the time to figure out whether it needs this technology in the first place.
This means asking questions such as which tasks need to be automated? How much data is available for machine learning algorithms? Are there simpler algorithms that can perform the same task but would be cheaper to develop?
Once a company has decided that it wants to go with AI, it should start slow and small. The idea is that overinvesting in this technology might lead to waste.
Companies need to take their time to experiment and figure out which areas benefit the most from the use of this fascinating new technology.
Heather Redding is a content manager for rent, hailing from Aurora. She loves to geek out writing about wearables, IoT and other hot tech trends. When she finds the time to detach from her keyboard, she enjoys her Kindle library and a hot coffee. Reach out to her on Twitter.