Exploring the Types of AI in Project Management
Do you know the four main types?
Last week I broke down a presentation that was given by Lloyd Skinner at Greyfly.ai.
It showed how project management is progressing with the help of AI.
The days of endless spreadsheets, manual updates, and constant guesswork are being replaced by a new era of efficiency and precision, all driven by AI.
AI is becoming a powerful tool and can help take your project management skills to the next level, helping you save time, reduce risks, and make smarter decisions. AI can be used at any stage of the project and portfolio management (PPM) process.
As a refresher, here’s the chart from last week’s article that shows the AI in Project Management Classifications.
Essentially, this is a bolt on lesson to that presentation since it had a lot of impactful information.
Lloyd’s presentation mentioned how AI is transforming project management through four key technologies: Machine Learning, Natural Language Processing, Computer Vision, and Robotic Process Automation.
Let’s break those down and see how these technologies are impacting project management.
Machine learning is the predictive powerhouse
Machine Learning (ML) has quickly become the backbone of modern project management. As Greyfly’s “Predictive Engine” has shown it’s able to foresee potential pitfalls.
ML can predict resource shortages, budget overruns, or project delays—before they happen. That’s the kind of insight ML brings to the table.
By analyzing historical data and recognizing patterns, ML can predict risks and optimize resource allocation. It can tell you if every team member is in the right place on the project at the right time.
It's like having a crystal ball, but one based on data rather than hoodoo voodoo. It’s helping the project manager proactively preventing problems and stop reacting to them.
Want to know the real game-changer? ML-driven tools can automate routine tasks, which frees up project managers to focus on strategy and high-level decision-making.
Your role as the PM shifts from micromanaging details to guiding the project toward success with data-backed confidence.
These systems are adaptive systems and heavily leans into the “Insight and Foresight” quadrant. It also feeds into the next types of AI we will discuss below — NLP and computer vision.
Natural Language Processing (NLP) is making seamless communication possible
We’ve all been in projects where there are communication problems between teams causes some balls to the dropped at critical times. But with the help of Natural Language Processing (NLP) those problems can be avoided.
Greyfly has shown NLP can enable your project management software to automatically understand and interpret human language—through voice commands, emails, and meeting notes.
Global teams can use NLP to automate tedious tasks like summarizing meeting notes, managing emails, or even translating communications in real-time. With this powerful technology you can save time and keep everyone on the same page worldwide.
Sentiment analysis is a key feature of NLP — it can measure the emotional tone in any type of communication. This helps project managers identify potential issues before they escalate. NLP can detect dissatisfaction in a client email or recognizing team burnout in recent meeting notes. Some project managers are tuned into their teams and can anticipate problems — but for those who need some assistance NLP can provide a much needed second opinion.
NLP is key in the “Streamlining and Automation” and the “Virtual Assistant” quadrants. It is the backbone for Chatbots and uses Large Language Models (LLMs) for summarization and translation.
Computer vision is the eye that never sleeps
It may sound futuristic, but construction and manufacturing are starting to rely on computer vision to help with project management. AI tech enables machines to "see" and interpret visual data, just like a human—only better.
AI can monitor video feeds and images and identify potential issues like construction defects, safety hazards, or project delays in real time long before they become significant problems. The great thing about AI is that it never tires and is available 24/7 to alert project managers of any project problems.
The human eye and our perception is fallible — we miss things. AI can identify patterns and trends that aren’t apparent. It allows project managers to leverage these insights, refine processes, improve safety, and ensures that projects stay on track and within budget.
Computer vision is heavily used in the “Streamlining and Automation” quadrant since it records and dissects information faster than human operators.
Robotic Process Automation (RPA) is the ultimate virtual assistant
If you’re bogged down by repetitive, mundane tasks, Robotic Process Automation (RPA) is your new best friend. RPA is designed to handle rule-based, repetitive tasks.
It’s primarily used in data entry, report generation, or financial tracking. AI works at a speed and precision that humans can’t match.
Project managers can offload these tasks to RPA and get back to tasks that cater to their strengths. They can focus on strategic planning, risk management, and driving the project to completion.
If project managers put an RPA to work, they’re reducing the likelihood of human error, and it ensures the data is accurate and up-to-date.
Basic automation is just scratching the surface of RPA’s capabilities. It can also help project managers monitor project costs and resource allocation in real-time, giving them a live overview of the project’s financial health.
RPA keeps everything in check and ensures that resources are being used optimally throughout the project.
You’ll notice in the chart that RPA is bridging the quadrants of “Streamlining and Automation” and “Virtual Assistants”. It’s automating workflows and if you have tasks for entering data (entering schedules, task notes) it can help you remove these tasks from your plate.
I was hazy on how RPA was used, so I researched it further.
Toptal gives this example of what RPA is (link to article at the bottom):
An implementation of an RPA project example might look like this:
An RPA bot receives an email with a standardized Excel invoice request form.
The bot logs into an enterprise resource planning software SAP.
Extracts the data from excel and inputs it into SAP.
Creates the invoice in SAP and sends it to the requester.
The bot sends a confirmation email, showing that the invoice has been created and sent.
Closing thoughts
We’re getting close to a time where using AI is no longer a luxury for project managers — it’s becoming a necessity. Whether it’s the predictive analytics of Machine Learning, the seamless communication of NLP, the insightful monitoring of Computer Vision, or the time-saving automation of RPA, these technologies are reshaping how we manage projects.
Investing in AI-driven project management tools isn’t just about staying ahead of the curve — it’s about being the delivering projects more efficiently, accurately, and successfully.
Lloyd mentioned that project managers are supposed to be the visionaries and convince their companies to start to use AI. If you’re not pushing your organization to look into AI solutions, you may be left behind as the technology progresses.
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Cool ChatGPT Prompt for PMs
Communicating with stakeholders
As an experienced project manager, your task is to draft an email to the stakeholders of [project], providing them with a comprehensive update that includes both the [achievements] and [current challenges] the project is facing. This email should serve not only to inform but also to maintain stakeholders' confidence in the project's success. Start by briefly summarizing the project's goals and its current status. Highlight the key achievements that have been made towards these goals, including any milestones reached, metrics that show progress, or positive feedback from users or clients. Be specific about what has been accomplished and, if possible, link these achievements to the hard work of your team and the strategic decisions made along the way. Next, address the current challenges the project is facing. Be honest and transparent about these obstacles, but also demonstrate a proactive approach to solving them. Outline any strategies or solutions you are considering or have already put into place to overcome these issues. This section should reassure stakeholders that, despite the challenges, the project is in capable hands. Throughout the email, maintain a positive and professional tone. Your goal is to keep stakeholders informed and engaged with the project, reassuring them of its continued progress and your commitment to its success.
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