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Analyzing the Role of Artificial Intelligence in Project Management: Pros & Cons

role of Artificial Intelligence in Project Management

Understanding Artificial Intelligence (AI)

AI refers to a field of computer science dedicated to finding efficient solutions to problems that would otherwise merit human intervention and intelligence – for example, pattern recognition, data analytics, insight learning, and generalization.

To clarify the inherent distinction between Machine Learning and Artificial Intelligence, it is imperative to not to miss the woods for the trees. ML denotes a program’s ability to learn, while AI encompasses learning along with other functions. 

An Insight Into The Role Of Ai In Various Spheres Of Life In General And In It Specifically

There is a lot of ambiguity surrounding the efficacy of the use of artificial intelligence in project management. Take a quick public survey regarding people’s views on stuff like “whether AI is ethical?”, or “how exactly AI may change the world we are accustomed to?” and you will come across answers as varied as chalk and cheese. This blog aims to familiarize readers with the pros & cons of AI based project management software.  

When we consider the effect of introducing artificial intelligence in the realm of fields like online shopping, the implications have been truly revolutionary. If we were to consider IT project management specifically, traditionally the DevOps teams or app development companies are responsible for information analysis of various software development projects. 

With the advent of AI which helps conduct analytical calculations without human participation, the scenario seems on the verge of undergoing a sea-change. Let’s look into the opinion of several IT giants before we make our way towards an in-depth analysis of the merits and demerits of using AI in project management. Hop on the bandwagon for a nail-bitingly engaging read that follows peeps!

Mind Speak Of It Firms On Whether Ai Is A Boon Or Bane In The Field Of Project Management

1. According to Gartner, by 2020, AI is projected to generate 2.3 million jobs, reimbursing the 1.8 million that it will replace, and generate $2.9 trillion in business value by 2021

2. Google’s CEO, Sundar Pichai, is of the opinion that, “AI is one of the most important things humanity is working on. It is more profound than electricity or fire.”

With the aforementioned insights, it is clear that the world landscape is experiencing a revolution of sorts, and it becomes all the more imperative for PMs to grasp the opportunity and brace themselves with the requisite tools to adapt to the fast-changing AI-based environment. 

Shedding Light On The Merits & Demerits Of Ai In Project Management

Accelerated Data ProcessingNascent Development Stage
Reduction in Project CostResults are unpredictable


1. Accelerated Data Processing Capabilities

In today’s fast-paced digital world with a perennial time crunch, data is as much a king as the consumer. Because if you can analyze your data well enough, more than half of the battle is won! 

Online retail therapy is something that we all are guilty of indulging in from time to time. Have you been wondering about the ads that keep popping up while browsing which is akin to your last searched for an item in any shopping app? Seems like a head-scratcher? Well, it really ain’t my friend! AI is pretty much your knight in shining armor with unprecedented data crunching capability. 

Time saved is money earned and DevOps teams the world over are warming up to the idea of using AI for crunching complex calculations and other mundane time-consuming tasks. Let’s hear it straight from the horse’s mouth, “Using AI for data analytics and machine learning cloud computing could help project managers hone their project plans to be more efficient based on past performance. AI can also identify risks, indicators, and trends that could threaten the success of the project.” says Jayne Groll, CEO at DevOps Institute.  He also throws in a word of caution by stating, “AI should in all circumstances serve as a ‘trusted advisor’ but not as the actual project manager.”

So to summarize, AI and ML help managers to:

a. Use past results to refine their project plans.

b. Highlight the risk factors that may threaten the successful implementation of projects.

2. Using AI-based apps can substantially reduce project costs

Ensuring that teams don’t go over budget is a nail-biting endeavor that keeps all project managers virtually on the edge. According to the findings of research conducted by Accenture, using AI can virtually halve the administrative tasks of any project manager, which currently stands at 54%. 

AI can also expose hidden bottlenecks and visualize data that may escape human notice.


1. Improperly Trained Ai May Result In Erroneous Conclusions

Taking into consideration the above graphical analysis, Gartner is of the opinion that the top obstacle managers may face by adopting AI is facing erroneous outcomes due to insufficiently trained algorithms, data, or the team handling them.

Project management requires the expertise of scientific handling and balancing the nuances of intricate artwork. Thereby it is imperative that companies using AI invest sufficient time in cleaning and training the data. 

2. Ai Tools Used For Pm Are Still In Nascent Development Stages

Change ain’t all that easy to embrace and it remains a task for tech leaders to convince their superiors to invest in an AI-based PM tool. Also, the prototypes haven’t reached a fully-fledged readiness stage.

Therefore the ball lies in the court of the DevOps team to make the final choice between, either taking the path of AI testers for project management or wait for the time when the apps have reached the zenith of successful development and their work will be free of unforeseen errors. 

Answering the multimillion question which is to go for it or chuck it? Well, it is imperative to understand that even the best-trained algorithms in AI solutions for project management do not guarantee seamless operations. Hence employees need to monitor the data AI consumes to eliminate result distortions. 

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