11 Impacts of Artificial Intelligence on Project Management


Artificial Intelligence Project Management

What is Artificial Intelligence?

Artificial intelligence is a branch of computer science that aims to create intelligent machines and it has become an important part of the technology industry. Majorly, Artificial Intelligence must have access to objects, properties, categories and relations between all of them to implement knowledge engineering. Although, initiating a common sense, reasoning and problem-solving power in a machine is a very difficult and tiresome work. The computer has to learn how to respond to certain actions and so it uses algorithms and historical data to create something called propensity model. Therefore, machine learning is also a core part of Artificial Intelligence. Artificial Intelligence mimics human intelligence by use of machine to learning. Researches associated with artificial Intelligence are technical and specialized.

Generally, there are three types of Artificial Intelligence:

Artificial Narrow Intelligence (ANI): It is a type of AI that is prominent in performing a single task with smartness. The single task is performed efficiently and with smartness (intelligence) and is considered as the basic concept of Artificial Intelligence. It includes the following:

  • Speech recognition
  • Voice assistant

Artificial General Intelligence (AGI): This type of AI as the name suggests, it is general purpose and its efficiency and smartness could be applied to do various tasks as well as learn and improve itself. It is also as intelligent as human brain. However, unlike ANI, it can learn and improve itself to perform various tasks. Examples include AlphaGo

Artificial Super Intelligence (ASI): This more powerful and sophisticated type of AI as compared to ANI and AGI than human’s brain. Super Intelligence can surpass human intelligence and it can think about abstractions which are impossible for humans to think.

In relation to Project management there is project management AI which is a system that can perform the daily activities of management and administration of projects without requiring human input. It does not only automate simple tasks but also develop an understanding of key project management. It can then use this understanding to perform more complex tasks, uncover insights to make recommendations and decisions sometimes in ways that people can not do today. Ultimately, the AI system will save you time while improving outcomes for your projects and team.

11 Impacts Of Artificial Intelligence On Project Management:

Cost Reduction: This is achieved by incorporating a sophisticated Artificial Intelligent powered software. The potential savings that can be attributed the proper utilization of Artificial Intelligence far outweigh its cost. Artificial Intelligence can automate and streamline many repetitive tasks allowing both team members and project managers to focus on the more complex activities involved in the project. In this case, it increases the quality of work while reducing the cost of labor. Generally, cost reduction seems to be the main reason for Artificial Intelligence adoption. The baselines for Artificial Intelligence are obviously automation and integration in cost reduction.

Predictive analytics (Predicting and experimenting): Predictive analytics through Artificial Intelligence involves combining through the specifics of past projects to find out what worked and what did not. Basically, Artificial Intelligence can “predict” a given project’s future and improve its visibility for project teams and managers. It also gives warnings if a project is going off the track with respect to time and budget or can give intelligent advice on budgeting, scheduling, potential risks etc. Artificial Intelligence has helped in predicting everything in sales. Predictive analytics enhance decision-making for the users of project management tools equipped with Artificial Intelligence.

Actionable Insights from desperate data: Apart from automation, another prominent function of Artificial Intelligence is to provide actionable insights into the project by sorting through and collating data from array of sources. Artificial Intelligence is capable of finding connections in data that would not be visible to even the most trained human eye. Furthermore, Artificial Intelligence can provide actionable insights into a multitude of aspects relating to the project allowing project teams to get around complicated problems. Artificial Intelligence does the job of structuring the data, finding its patterns and inconsistencies where applicable. This allows it to harness insights from even the densest masses of data and transforming it into something that project can use to better their project processes.

Eliminate repetitive administrative tasks: For instance, when the bulk of administrative tasks are passed on to Artificial Intelligence, project managers have more time and energy to focus on real work. Through this they can add value to the project with their unique interpersonal and judgmental skills, which will become more important as Artificial Intelligence becomes prevalent in business. In fact, no software or line or code that could ever replace a human being’s judgement and empathy.  Therefore, as Artificial Intelligence and its applications in project management grow more prominent, the project manager’s role in strategy, motivation, innovation and judgement in general will be priotized.



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Enhancing visibility for early risk date: Artificial Intelligence unlike human beings, it is much better at performing mundane and repetitive tasks. Through this feature, it allows for better administrative control and enhanced visibility in projects that require it. Artificial Intelligence software will enhance visibility for projects across spectrum, which enables detection of risks early on so they can be handled before they pose a threat to the completion or quality of the project.

Help interpret project management data: Artificial Intelligence software is able to handle large swaths of data. Based on various data sets, Artificial Intelligence system can warm the managers before things go wrong. In that way, project managers can study the problem and hopefully take a preventive or corrective measure. Again, the project management Artificial Intelligence system can also give project managers advice based on skills of a particular team or an individual need to be trained.

Task priotizations: Although, it is not easy to priotize tasks especially when working in teams. Artificial Intelligence males it easier to make an assumption with regard to the available data and thus help the team better understand their actual priorities or focus on a particular task.

Help sustain holistic and Nano project management: Down the line of project execution, the project management expert is faced with a number of responsibilities. However, Artificial Intelligence algorithms has made it easier for project managers to delegate hundreds of tasks to various people in a team. Ultimately, the system helps the manager to maintain a holistic view of the projects and the teams. Generally, the accuracy with which these systems perform the tasks is comparable to the Nanotechnology-an Artificial Intelligence -based cancer diagnosis technology that analyses billions of cells in the body to detect the cancerous cells with a 95.5% accuracy. Therefore, this is the kind of the accuracy and precision that business wants especially when they are racing against time pursuit of potential constraints and bottlenecks that might hinder the progress of the project. It is much easier for project managers when using project management Artificial Intelligence technology to quickly release bottlenecks.

Re-planning project: Due to complexity of tasks especially when dealing with thousands of tasks which human brain cannot manage, the Artificial Intelligence capacity can be used in re-planning of the project. In this case, we do not need project managers to re-plan but the system will do it better.

Better and efficient analysis, insights and prediction: With gigabytes of data, it is beyond human beings to go through such information, analyze it and use it to make predictions. However Artificial Intelligence based tsk tracking software will not only help analyze it but also offer useful insights that can be used to predict the future.

Resource matching:  For efficient resource allocation, it is very important to avoid a miscarriage of a project along the course of execution. With this, project management Artificial Intelligence system’s learning capability helps bring forth local knowledge. Based on this knowledge, the project manager can easily deduce the areas that have enough resources and where there are drawbacks. In that way, it is much easier for the project manager to make a better decision. The Artificial Intelligence system also performs non-biased priority checks based on the set of rules the project manager or developer sets. Therefore, the resource assignments become easier, the manager can determine the capacity levels of the employee and also get the feedback on the employee’s behavior.

Artificial Intelligence for Risk Management

Clavero(2018) defined Artificial Intelligence as an amount of information that the human mind can process which is limited by time and space. However, Artificial Intelligence captures a big quantity of data to analyze the information for trends and patterns. Essentially, Artificial Intelligence uses the machine’s power to model the human natural intelligence. For instance, the machine learning (ML) is used by Artificial Intelligence to accomplish tasks and solve problems with superior speed and precision. Despite the growing interest, Artificial Intelligence and machine learning are not new at all. In fact, they have been in existence since 1970s and 80s (Van Liebergen,2017). Johnsonbabu (2017) stated that Artificial Intelligence improves the risk assessment through understanding the risk emergence in a specific project context. The combination of machine learning with Monte Carlo simulation can help risk managers to improve the evaluation and simulation of risk. Therefore, fuzzy logic is used for assessing risks in construction projects to shape the likelihood distributions (Johnsonbabu,2017).  Intelligent systems help project managers by providing them with them on downstream hindrances and upstream opportunities through real time analysis data of projects data (Johnsonbabu, 2019).

The Concept of Fuzzy Logic

Fuzzy Logic is a rule based system which can depend on an operator’s practical experience, mainly beneficial for capturing practiced operator knowledge.  The emerging of fuzzy logic was noticeable in 1956, as Lofi Zadeh introduced the Fuzzy sets theory. Fuzzy Logic includes a method that can make certain decision based on ambiguous and inaccurate data input. Fuzzy logic broadly existed in control system applications, as it closely related looks like human in making decisions but in much faster way. Moreover, Digne (2011) declared that fuzzy logic is not as many people think and has been used silently behind the scenes in several places along more than 20 years. Since fuzzy logic is implementing a form of decision making, it can be considered as an Artificial Intelligence software toolkit.

The Fuzzy-Based Risk Management Methods

Shan et al. (2015 defined Fuzzy set Theory as a research method that deals with problems relating to ambiguous, im[precise judgements and subjective and it can quantify the linguistic facet of available data and preferences for group or  individual decision making. Tylan et al (2014) stated that construction projects in nature contain a large amount of vagueness and uncertainty, thus this led to the fuzzy concept application. However, Islam et al. (2017) declared that many drawbacks of fuzzy approaches have been highlighted leading to the need to use  hybrid approaches for risk analysis. Fare and Zayed (2010) classified the basic fuzzy methods are considered as the representative of fuzzy logic as well as fuzzy set theory. While the extended methods contain adapted algorithms regarding fuzzy theory but adapted by other independent methods.

Summing it Up

Despite the slow adoption of Artificial Intelligence, a lot of companies are slowly realizing the importance of tracking software AI when it comes to management of the projects. Artificial Intelligence is helping managers make better resource allocations and delegate takes and view the project holistically as it rolls a down the path of execution. Artificial Intelligence is soon becoming the best engine that helps project managers deliver better results, efficiently and within the specified time frame. The capabilities of Artificial Intelligence have great potential to step project management up a gear. Therefore, Artificial Intelligence assistants can assist project managers in a variety of tasks, from developing a list of project concerns to determining team training needs.

BIBLIOGRAPHY

Kerzner, Harold. Project management Best Practices: Achieving Global Excellence. Hoboken: John, Willey & Sons,2018

 Mateo,Jose R. Management Science, Operations Research and Project Management: Modelling, Evaluation, Scheduling, Monitoring. London Routledge,2016

Petridge, Derek,  and Khateeb M. Hussain. Artificial Intelligence and Business Management.Intellect Books,1992.

Rezakhani, P. (2012). Current state of existing project risk modelling and analysis methods with focus on fuzzy risk assessment in construction. Computer-Aided Civil and Infrastructure Engineering.

Chaudhary, P. Singh D. and Sharma, A. (2016). Classification of Software Project Risk factors Using Machine Learning Approach Intelligent Systems Technologies and Applications:Springer.

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