The Role of Bots and AI in Project Management

Project Management is a specialist’s job. One that can be mastered only with years of practice. But by calling it a specialist’s job, I am in no way undermining the fact, that a typical project manager needs to wear multiple hats at work.

Essentially you are accountable for the success and failure of the project. So it is not just enough for you to have just the functional and domain knowledge, you need to be good with people as well.

To sum it up a Project Manager’s scope of work can be summarised across 3 broad areas:

  1. Planning and Strategizing: Define the scope, build an execution plan — prioritize and delegate accordingly and manage the budget.
  2. Managing the Team: Facilitating commitment and productivity, dealing with obstacles and motivating the team members.
  3. Managing Expectations: Aligning project to business goals, managing stakeholders and communicating project status.

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What is Project Management AI:

AI and bots are about reliably offloading a task from a human to a machine counterpart. AI is what makes machines intelligent, and a bot is simply the software that performs the task on the user’s behalf.

With that basic understanding, let us try to shed some light on what a Project Management AI system would be like.

Ideally, it should be able to handle the day-to-day management and administration of the project without any human input. It should be able to automate simple tasks and develop an understanding of key elements. Then use this understanding to uncover insights, make recommendations and perform more complex tasks.

Now here is the paradox, apart from the processes, Project Management has a strong human element to it, which in my opinion is the most critical part.

Considering this fact can AI and bots make inroads into a project manager’s life?

Gartner predicts that by 2030, as much as 80% of the routine work — which represents the bulk of human hours spent in today’s PPM disciplines, can be eliminated as a result of collaboration between humans and smart machines.

Today’s project management practices rely heavily on human input. All data points must be collated, organized and consumed by human beings.

But that’s not the optimum use of the human mind’s intuitive abilities. Innovation and critical thinking should be the key attributes of a project manager’s role as routine work gets managed by machines.

So humans need is not be apprehensive about machines replacing them, rather look at this as an opportunity to improve productivity.

While machines can tirelessly forage data, look for patterns and variances to offer data-driven actions and recommendations, humans can back this up with their intuition and soft skills to shepherd the team towards the project goal.

So how can this collaboration work?

Unlike before, a project manager’s responsibilities today are inclined towards that of a coordinator and coach and less of a dictator. This requires project managers to be proactive, and if they are alerted of an impending problem, they can stay way ahead of the game.

This is in contrast to the modern day project manager’s role, who spends most of his time defining and collating information for decision making. This information gathering role of the PMO should be reduced and replaced by smart machines that link goals, strategies and the potential and actual investments that support them.

Simple bots can perform a variety of tasks, like updating task sheets, setting up reminders, generating project reports and much more. However, add AI to the mix and you have a far more advanced system that can as well deliver advice and not just data.

Some of these use cases could include:

Project Collaboration:

Collaboration across various stakeholders is a major concern, especially in large teams and more so if the team is spread across different time zones.

Transparency on who is working on what, and being able to communicate across different groups add context to collaboration and scrape out inefficiencies. Such a setup gives the PMO a lot more control to ensure that nothing falls through the cracks.

So how can a bot help here?

Chatbots can help you stay in sync with your team. For example, a chatbot like Meekan can help you schedule team meetings. All you need to do is ask Meekan to book a meeting slot, and it will match everyone’s calendars and quickly find common free times.

Need to reschedule in case someone drops out at the last moment? Again you just need to ask and Meekan will help you find an alternate time. All this while avoiding the back and forth of emails. Plus the interactions are more fun and engaging.

Data Consistency:

The often unmentioned challenge with project teams in any organization is the suitability and quality of data.

Some teams enter minimal to no data, and even the most disciplined teams might make errors that render the data unreadable by machines.

Given the widespread usage of chat applications, chatbots can connect with team members at the end of their workday and gently ask them to input the status of the task assigned to them. Add to this a few layers of metadata, and the AI engine can check data consistency and provide meaningful advice to improve the quality of data an user is inputting.

For example, Ayoga ActBot powered by the Applozic chat framework sends timely alerts to project members getting them to fill timesheets, respond to RFIs and update their work progress through a familiar chat interface.

As an extension to this, the bot can collate all the entries and publish daily status reports with a breakdown of all the tasks the team members are working on and any major roadblocks they are facing.

Task Management:

Employees at SMBs are expected to handle different tasks according to the demands of the project. While juggling multiple tasks isn’t easy, it becomes all the more difficult when everything is done manually.

Without proper monitoring, employees moving in and out of tasks leads to loss of accountability and unplanned resource allocation. For instance, you wouldn’t want your key engineer to be pulled away onto other projects, nor would you want him to handle trivial tasks. Similarly, you would also want to know about the performance of every team member and how aligned their deliverables are to the overall project goal.

Now as AI develops an understanding of sprints and task descriptions, new metrics can be revealed that weren’t available earlier. For example, in software projects, bots can monitor every change made to the source code and link it to the developer and task involved. The bot can then report bugs in any line of code, the person who made the commit and the task that relates to it. This will allow for real, actionable indicators of individual and team performance.

Stratejos is a chatbot that can do most of these and assist you with team coordination. It can identify if a sprint or project is about to run into trouble and help you resolve this. It can also help you improve in real time by monitoring practices and providing training content for the problems that might occur.

Risk Predictions:

Remember the Tom Cruise starrer Minority Report? The movie is about a special police unit called “PreCrime” who could look into the future to detect a crime and then stop it from occurring.

Now imagine you have a list of likely delays, risks, and problems even before they occurred. Wouldn’t it make your life as a project manager a lot easier?

You might be thinking this is too far-fetched. Probably it is, but by no means is it improbable. It is only a matter of aggregating the right pieces of data and mine through it to predict the possible outcomes. A simple example is, monitoring the time spent on a certain task can help you predict whether it will meet the deadline.

As an extension of this, AI can unobtrusively collect metadata and look at how team members do their jobs. Many industries like credit scoring, counter-terrorism, banking, and finance are already doing it to predict events before they happen.

A lot of predictions can be made by analyzing your team’s behavior and their habits. These predictions can be purely operational like predicting likely delays, probable quality issues and otherwise as well, like low team morale, personal issues etc.

Exciting time ahead

The future is that of human-computer complementarity. A lot can be done just by getting the division right and automating certain processes and then training people to work alongside computers.

Imagine AI doing all the mundane tasks and then assigning the rest to the right team member based on their skills and expertise. It just doesn’t stop there, machines can predict shortcomings, generate actionable reports and share the best practices at every step. This will be so powerful and useful.

The best part, it is not really as far-fetched as it may seem. The recipe is simple, all this can be achieved with a mix of standard software development, opinionated views on how projects run and machine learning technologies.

Project Management AI is going to have a huge impact on how projects run and that is for the better. Teams taking advantage of this will definitely have an edge over those that don’t. And that’s something to be excited about.

Author Bio: Satadeep Biswas is a marketing and tech geek working out of Kommunicate’s Bangalore office. If you don’t find him in the corner cabin trying out the latest SaaS in the market, you might well find him at one of the football fields around the city. He covers topics about the good and bad of tech and its implication for businesses. You can find more articles by Satadeep on and

Originally published at on September 7, 2018.

The Role of Bots and AI in Project Management was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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