Predictions like “AI will take our jobs” sound scary. However, long before our jobs as project managers are taken, AI will help us. In fact, it already is, and we don’t think about it much. While writing this article, AI in Microsoft Word and the add-in Grammarly helped protect you, from the bulk of my spelling and grammar mistakes. This is how AI will help us first, by doing small things we are error-prone with, before tackling larger tasks.
Like me, do you spend time booking meetings, finding rooms, and distributing information? Do you analyze backlogs and scope outlines for potential risks, or review estimates for commonly missed activities? Artificial Intelligence (AI) can help with these tasks and many more.
Imagine having a non-judgemental expert monitoring everything you do (and do not do) at work and making helpful suggestions to you in private. This expert is constantly learning, is plugged into all the latest research and works for free. This is the not too distant future of AI assisted project management.
June was Technology month at Project Management.com, and there have been a few articles about AI taking away project management jobs. This article focusses on ways AI can help project managers which will happen as AI develops and before it can replace jobs. It deals with automating the process and science parts of project management, leaving people more time to focus on the relationships, leadership, storytelling, empathy and emotional intelligence side of projects that are harder to tackle and are (currently) best done by people.
AI has come a long way since Microsoft rolled out the annoying and not so helpful “Clippy” Office Assistant tool in 2003. It was never tuned for project managers, but it if were it might have looked something like this:
Instead, AI is becoming more sophisticated and useful. Gmail will remind you to attach a file if you mention “attach” in the text of an email that has no attachment. Most people use personal assistants like Siri and Cortana on their phones, or Alexa in their homes. Voice recognition and comprehension are steadily increasing. Google recently demonstrated their new Google Assistant calling and interacting with a hair salon to book a haircut. Clearly, these tools will soon be ready for prime time and their use will be widespread.
Kevin Kelly, futurist and founding executive editor of Wired magazine, says in his TED talk: “Everything that we have electrified, we are now going to cognify”. In other words, we will add intelligence to devices and products. Kelly went on to say, “I would suggest that the formula for the next 10,000 start-ups be very, very simple: take X - and add AI.”
To understand how AI can help project managers, let's examine its basic capabilities.
Knowledge Based Expert System (KBES) – these work from decision trees of IF - THEN statements to provide expertise. Gmail’s attachment reminder works with similar IF body_text includes “attach” AND Attachment = False THEN issue a warning.
Artificial Neural Network (ANN) – these systems model our real brains and consist of networks of weighted connections. They can be programmed to learn, recall, generalize and apply fuzzy logic. So, if we teach it someone 4ft high is Short and someone 6ft high is Tall it can generalize that someone 4ft 6 is “Not very tall”. Being able to make these types of generalizations are important for realistic interactions with people, such as Google Assistant making a hair appointment.
Machine Learning – this builds on Knowledge Based Expert Systems and Artificial Neural Networks to create predictive analytics that can provide validation and advice. In the project management space, this is the technology that can help with checking for missed risks, rebaselining plans, recalculating the Cost of Delay for waiting initiatives, etc.
Chatbots - AI powered programs designed to simulate a conversation with humans. Chatbots use artificial neural networks and machine learning to combine domain intelligence with natural language processing. This gives the impression of interacting with a (currently somewhat) knowledgeable person.
If these technologies sound far-fetched in the project management field, consider the quote “The future is already here — it's just not very evenly distributed”. Agile tool vendor Atlassian, already provide project assistants that help with budgets, estimates, and sprint management. They also have chatbots to share project information and remind team members for estimates and status updates.
Moving forward, these tools will be expanded to help check our work for common mistakes, just as Word checks for common spelling errors. Every industry has catalogs of defect origins and removal methods (here is one for software projects) AI assistants can apply this knowledge and suggest steps to help avoid or reduce these risks. It is not an exact science and as a project manager, I may choose to dismiss potential risks flagged. However, having assistants available to highlight these risks or list the top 10 estimation omissions in my field is probably better than not having them.
AI assistants can also alert project managers to slowly developing trends that might otherwise go unnoticed. The old saying that projects become late one day at a time is very true. Optimistic project managers with “Can-do” attitudes often underestimate the impact of small setbacks and or hope that teams will “catch-up” later. This hardly ever happens, and AI assistants can be programmed to alert early and avoid hope-based-planning.
There is a risk that with expert knowledge systems, organizations may be tempted to use inexperienced project managers. Or project managers become reliant upon these tools and not think as deeply as they may otherwise. Like any technology, a fool with a tool is still a fool. However, tapping into standard risk lists from your industry, that gets augmented with those from previous projects in your organization is a smart move.
Having calculators has likely reduced our ability to perform long division calculations manually. However, I don’t want to go back to self-calculation just because I fear an over-reliance on technology. Instead, I want to use technology where I can and free up my time and mental capacity for other work.
Higher Value Work
The PMI Talent Triangle is a good model for thinking about all the work a project manager does. It includes: 1) Technical Project Management – the project mechanics described in the PMBOK Guide and Agile frameworks, 2) Strategic and Business Management – your industry-specific work, and 3) Leadership – the people dynamics of projects.
If we squash the triangle out and lay the pieces in order of how much impact the project manager’s contribution has towards project success we get: Technical, then Strategic, and then Leadership. By this sequence, I mean that if the basics of Technical Management are met then Strategic and Business Management work is more significant. Furthermore, good Leadership has an even greater impact on overall project performance than Strategic and Business Management Work, and Technical Project Management.
This sequence is shown below:
The good news for us as project managers is that (currently) AI is best suited for the lower value end of this work spectrum. It is already capable of assisting and saving us time with Technical Project Management work. Next, it should soon be commonplace to get AI assistance with Strategic and Business Management tasks. This will involve accessing machine learning focussed on our industry domains, like ROI models, common risks, and estimation omissions.
The last area AI will move into is the Leadership domain. Machine learning requires deep data sets in a consistent form to draw reliable conclusions. The people dynamics of motivation, conflict management, and negotiation are harder to classify and rank. Currently, most people would rather work with a real person to solve issues or discover their calling. Who knows, maybe in future people will prefer to interact with chatbots who’s decision parameters can be shown to be neutral and fair. This might be preferable to dealing with people with all their inherent bias and gaps in knowledge.
All I know for now is that I currently welcome any AI assistance I can use. It is likely to safeguard me from making basic technical project management errors or omissions. It should also be helpful soon in providing industry knowledge and best practice – like having a seasoned professional in the industry available to look over your work. However, AI tools will check in real-time before you commit that decision or share a plan.
This leaves me more time to focus on the people. The people sponsoring the project, those working on it, and those who will be impacted by it. They will have their own AI assistants too. Booking meetings, getting rooms, and sharing ideas should become frictionless leaving us to work on the more significant issues.
My recommendation is to stay abreast of AI developments and remain open to trying the tools as they emerge. Standing still in an environment that is moving forward has the effect of moving backwards -which is not good. Where I should probably be more worried is in writing articles like this. It seems like a blend of domain-specific Strategic work with some Leadership based storytelling. Likely a candidate for an AI takeover long before the project manager. (My plan is to get in on the research and get a Chatbot writing this stuff for as long as I can get away with it!)
- How AI could Revolutionize Project Management, CIO Magazine, Mary Branscome, January 12 2018
- 3 ways AI will change project management for the better, Atlassian Blog, April 7, 2017
- Artificial Intelligence in Project Management - Is Your Company Ready for it?, Teodesk Blog, Minja Belic, January 22 2018
- AI will Transform Project Management. Are You Ready?, PWC White paper, Marc Lahmann, et Al, 2018
- Artificial Intelligence in Project Management, Khaled Hamdy, March 2017
[Note: I wrote this article for ProjectManagement.com, it first appeared here – free membership required.]