Since the inception of time, humans have always presented with the challenge of managing people and projects and delivering these projects in good time. The field and industry of project management emerged as a way to maintain a collection of people towards an end goal. It is common for project managers to manage multiple teams and multiple projects at the same time and with the inclusion of AI into this field such as in Planless, it has become easier to manage teams effectively.
Artificial intelligence(AI) is deemed the driver of the new industrial revolution. It is the intelligence exhibited by machines and has numerous applications in the evolving tech space. This technology has been used to develop and advance various fields and industries ranging from healthcare to finance education, and transportation amongst others. Famous examples of AI from self-driven cars to chess-playing computers rely primarily on deep learning and natural language processing.
Over the years, the rise in technological advancement has augmented human capacities, making it easier for activities carried out by humans for eons to produce effectual output. Recent innovations in cloud computing, big data storage and analysis, AI is setting the pace for improving efficiency in different spheres of life. AI provides critical information necessary to foster growth in these industries.
AI is present in our day to day activities, including search engine assistants like Google and Siri, predicting favourite movies on Netflix, directing paid ads to likely customers and directing the best route or cab-hailing services, to mention a few. AI for project management is on the rise, and the way things are going, it’s going to help teams make smarter decisions and move faster. Let’s take a look.
Artificial intelligence is slowly finding its way into project management to handle everything from scheduling to analyzing the patterns of a working team and offering suggestions. These augmented tools make AI a distinct plus to project managers in the future.
Artificial intelligence (AI) uses machine learning to imitate human intelligence. It combines a large amount of data with fast processing and intelligent algorithms allowing software to learn automatically from patterns and features in the data. Several technologies enable and support AI; they include:
Machine Learning(ML): machine learning focuses on the development of algorithms that analyses data and make predictions. It is an application that provides computer systems with the ability to learn from experiences without being programmed automatically.
Deep Learning: Deep learning uses neural networks with numerous layers of processing units taking advantage of advances in improved training techniques to learn intricate patterns in large amounts of data. These multiple layers of the neutral network work together to determine a single output from many inputs, for example, a voice recognition application.
Neural Network: neural networks are computer systems modelled after neural connections in the human brain. The artificial equivalent of the human neutron is the perceptron. They enable deep learning.
Cognitive Computing: this component of AI seeks to imitate and improve the interaction between humans and machines. The goal of this component is to simulate human processes and through the ability to interpret images and speech and then provide a coherent response.
Computer Vision: Computer Vision is a technique that combines deep learning and pattern identification to interpret the content of an image. It plays an essential role in AI, enabling computers to identify, process and interpret visual data.
Natural Language Processing (NLP): NLP is the ability of computers to understand and generate human language, including speech.
There are new technologies that enable and support AI, such as Graphical processing units, the internet of things advanced algorithms, and application programming interface. AI works to provide human-like interactions with software and offer support for specific tasks, but it is not a replacement for humans.
Every sector, from software to health care, education and e-commerce, carry out projects that require planning, managing and monitoring. The tools for project management are often sophisticated and may not correctly maximize the risks of the project. The innovation of AI into managing teams and assigning tasks produces quality results. Here are the points to support the claim:
Intelligent Project Management Assistance
Artificial intelligence is being used to help with project organization on a collection of fronts. AI systems are able to effectively handle scheduling, reminders, and follow-ups to eliminate the need for human input. The innovative workspace provides timeless automatic assistance by providing tools that foster effective team work and productivity for every member of the team from the least skilled to the most. This is one of many effective ways that these systems are capable of saving humans time on their various efforts by helping to make sure that nothing is overlooked. These systems integrate with popular communication tools to make for a more efficient process when it comes to getting tasks resolved. In the near future, it will be possible for an AI bot to send you important reminders.
Predictive Analytics for Project Management
The ability of AI to manage complex analytics allows a system to observe the way that a project is moving and make educated predictions about the future of the project. While humans are more likely to get caught overlooking specific shifts in the project because they are not seeing them directly, AI can see through all of the moving parts and then make valuable predictions based off of what it is seeing. AI has the ability to monitor budgets and scheduling, and over time it can learn to identify potential impacts on these processes. Planless uses this innovation to predict the most suitable team member for a task and assign them with designated tasks.
This makes it possible for artificial intelligence to recognize when something is occurring that is likely to lead to scheduling conflicts and makes it possible to offer up suggestions on alternate completion dates if the scheduling is off track. It also means that the system may be able to help offer personalized coaching for team members based on learned habits.
Over time, it seems likely that AI-enabled project management systems will be able to make the science of human behaviour stronger in various ways. A system that is capable of analyzing someone’s every move is likely to be more reliable in predicting actions or potential needs than a person might be. AI is vital in helping managers understand the distinctive nuances that are likely to come with individuals who are working with their patterns. In the same way, AI can identify a user profile for a shopper and act accordingly; these systems can help provide customized aid to team members working on a project, as well as project managers. Overall, the potential benefits of bringing AI into the project management space are endless.