Project management had always been practiced informally but has recently emerged as a formal profession due to the demand for specific skills and domain knowledge required for project management.

Today, project management has come a long way. Long enough to warrant discussions about the impact that Artificial Intelligence (you can’t escape it) could have on the domain. By now, most industries have accepted that Artificial Intelligence and Machine Learning are not dystopian nightmarish technologies that will steal their jobs but are in fact amazingly useful.

Artificial Intelligence engenders productivity by automation of mundane routine tasks (which previously consumed a huge chunk of time) and allows managers to focus on things such as analysis, decision making, and providing insight. Which is incidentally what they were hired for. It has opened up a brave new world for managers, especially for Project Managers.

Project management is an extremely dynamic function. It involves more than simply planning the phases in advance because once the execution of the pData Accuracyhases starts, there is a multitude of external and internal variables that come into play. Project Managers generally plan the schedule, estimate cost of resources and then monitor the deployment of personnel and tasks. There are changes, updates and rescheduled tasks at every stage of a project because of the ever-changing business environment.

This is how Artificial Intelligence can come in and revamp Project Management.

  1. Improve Learning Capabilities in Project Management
    AI could potentially be used for deploying the right person for the right project. Depending on employees’ past performance in different projects, Machine Learning could ascertain the suitability of their selection for a particular project, keeping in mind their specific skills and strengths. In addition to this, by taking into account external factors that are difficult to predict, the use of AI can improve completion rates significantly. Project Managers can use this knowledge to estimate the kind of roadblocks and possible setbacks the project could face in its normal path. It improves the learning capabilities of both the team members and the Project Managers on how best to go about a project the next time.
  2. Many teams have trouble maintaining data for their projects in a systematic and structured manner. More often than not, there are gaping holes in the data entered by teams into their project management software. The result is an incomplete, unstructured mess of data. Artificial Intelligence can fill in these data gaps. Eventually, they can prompt users to adopt better data entry practices and work with them to improve the quality of data entered.
  3. Early Problem-Detection
    Many times a project may be derailed due to a small problem that puts a spanner in the works. It may be that somehow the possibility of such a problem slipped the minds of the team members as well as the Project Managers; they are only human, after all. Artificial Intelligence employs metadata and data analytics to predict problems based on external variables as well as on past performance and behavior of team members in similar projects. Thus the Project Managers receive detailed knowledge on the kind of obstacles/roadblocks that the project is likely to face. They can take the appropriate measures to tackle the same in the early stages or to obviate the need to confront these obstacles altogether.
  4. Better Communication
    This is not a direct impact of the use of AI in project management but is a by-product. As a routine, non-essential tasks are automated, Project Managers can direct their powers of persuasion where they’re really needed: in better, more effective communication with team members, employees and project stakeholders. Project stakeholders do not want to be reassured by a chatbot spewing a pre-written script. Nor do team members want to be given a pep talk by a humanoid robot. The fact remains that human qualities such as empathy, emotional intelligence, diplomacy, and communication will remain significant for ages to come. And it’s the job of a project manager, or any manager, to embody these qualities and add value to the organization by doing so.
  5. Improve Assessments to Identify Risks
    In Supply Chain Management, AI is being used to provide real-time tracking updates on drivers and tasks. Any shipping errors or discrepancies are visible in advance and can be handled better. AI can do the same for project management. Clickup is a recently launched project management tool whose algorithms can revise time estimates and predict deadlines that won’t be met. Basically, Project Managers could receive a checklist of risks that could potentially arise, giving Project Managers ample time to assess the scenarios and devise solutions for the same.
  6. Improve Productivity
    Positive transformation is all about productivity. Improved learning, reduced idle time, and automation of routine tasks all add up to the improvement of productivity of the entire workforce or team. AI-driven solutions such as sort through communication across various channels and consolidate relevant information from all your apps. Team members will do more in less time, and they will do it better. With increased knowledge and risk aversion techniques available at their disposal, Project Managers will also be able to be more productive, provide better insights, and deliver better quality projects to the company.
  7. Taking Over Administrative Tasks
    Project management AI will be instrumental in removing the mundane, routine tasks from a project manager’s itinerary. Instead, it will automate these tasks, and administrate without the need for human input. By removing these administrative tasks, Project Managers can add more value to the project and get more work done at the same time.

Final Thoughts
It is apparent that Artificial Intelligence has an immense scope for application in project management. We have seen the benefits that it can bring to Project Managers as well as team members by reducing the time taken and improving productivity. AI could serve as powerful virtual assistants to Project Managers in the form of chatbots such as Dialogflow. Apps such as Forecast and Clarizen help them learn from their mistakes, avoid common pitfalls, and improve the quality of projects. What’s more, it allows for a greater focus on the human aspects of project management. One wonders if all the AI skeptics and naysayers are simply opposed to a progressive way of working.

Remember the recent Elon Musk and Mark Zuckerberg clash on the future of Artificial Intelligence? So, my colleague and I were discussing the topic and after a while she said she doesn’t understand machine learning & Artificial Intelligence fully.

Are you one of those, who understand the basics of AI, the robots and more; yet when it comes to deep and in depth technical understanding, it suddenly becomes confusing? If yes, worry not for you have landed at the right place. We’ll try to understand Machine Learning like a beginner.

The Beginning

Let’s start one thing at a time, beginning with an algorithm. So what is an algorithm? “An algorithm in simple words is a step-by-step detailed instructions to do a particular job.” In computing, it is a set of simple rules that instructs a computer how to perform a task. Generally, we need to program our computer on how to carry out a task and this is the building block of Machine Learning. In 1959, Arthur Samuel sparked the discussion on Machine Learning (ML), stating that ML gives, “computers the ability to learn without being explicitly programmed.”


The above image explains the evolution of Machine Learning over the years. But to simplify things further, we need to know the terms that are thrown in passing when we study this concept.

Artificial Intelligence in simple words is the simulation of human mind where machines work and act like humans do. Over the years, it has always been a part of our world and is not at all a new concept, flying cars in cartoons like The Jetsons to Wall – E in recent times.

AI evolved further giving birth to a new concept, Machine Learning, where machines were fed data and instructions to execute tasks. But what about behaviour or how our brains respond? How do machines take a decision? Knowledge is the building block and an integral part when it comes to learning. This is where another algorithmic concept called Artificial Neural Networks and Deep Learning came into being. ANN enables the machine to form connections much like our brains form them with the help of neurons and deep learning helps in better prediction. Today, various applications run on the learnings of deep learning and have improved significantly.

What is Machine Learning

Now and Tomorrow

But the bigger question is how does all this affect us? Does it only stay confined to the textbook theories and fantasies of an advanced future or is it deeply embedded in our lives? The answer lies within, we are surrounded by Machine and Deep Learning and we don’t even realize. From Google translate, predicting cancerous tumors in patients, MRI scanning, e-mail spam filters and even the ride sharing feature on Uber and Ola, all these things have been made possible with Machine Learning. Social networking, online shopping and even smart assistant devices on mobile phone are some of the examples of Artificial Intelligence.

All the distant fantasies created by AI are now coming to reality thanks to advancements in Machine Learning. AI is said to be the future of the human civilization, and the days of smart cities and self-driven cars may not be far behind. But more important than anything else is to understand the difference between the three concepts. Although they are interlinked to each other, they are in a nutshell a separate entity that operates individually.

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