There’s been a lot of talk about Artificial Intelligence (AI) in the project management space but many still remain in the dark about the actual technologies available, their capabilities and their potential. We’ll give you the realistic rundown of the five prominent AI technologies for project management and how their impact on the field. Get started on your journey of leveraging AI for project management.
What is Artificial Intelligence?
Gartner defines artificial intelligence as the application of ‘advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and take actions.’ They take many different forms with some of the most prominent being machine learning, artificial neural networks and deep learning.
Far from the dystopian all-seeing capabilities we often see on television, AI is bound to strict logic and rules-based frameworks that make processing nuanced and complex situations and data difficult. Though they have a massive potential, current forms of AI are still highly dependent on human input and can only work as well as the framework it is built upon.
Project Management and AI
Project management is a sphere that will see drastic change with the introduction and integration of AI, with reports suggesting that 80% of current project management activities will be taken over by AI by 2030. These statistics have often engendered reactions of either fear and excitement for project managers. The critical difference between the two reactions is often a matter of the degree of understanding of AI’s genuine capacity, not simply its rose-coloured projections in the future. We’ll give you a realistic and in-depth look at the prominent AI technologies and how their genuine impact on the project management space.
AI for Project Management: Top 5 AI technologies
The PMI report, ‘AI Innovators: Cracking the Code on Project Performance’ gives us valuable insight into the current and future impact of AI technology on project management.
1. Machine Learning
Machine Learning is a branch of artificial intelligence and computer science that emphasizes the use of data and algorithms to imitate human intelligence and learning processes. It gradually improves its accuracy through access to extensive historic data and consistent experience with real-world settings. One of its key benefits is pattern identification, analysis and estimations.
Machine learning is one of the major components of other AI technologies within the field, especially those on this list. In the project management sphere, it is still at its preliminary stages but is nonetheless already making a significant impact. The PMI report suggests that 31% of organisations have already been impacted by machine learning, with the figure set to grow to 69% in the near future.
2. Knowledge-based systems
A knowledge-based system (KBS) is a form of AI that combines machine learning and natural language generation to capture the knowledge of human excerpts to support the decision-making process. Rather than having to constantly refer to experts for the same topics to make similar repetitive decisions, KBS learns from a wide range of previously executed projects and project management artifacts to provide accurate estimations and reliable recommendations to project managers.
It takes data from all aspects of project management, from communication, risk management, cost management, resource management and more to gain a holistic understanding of the nature of projects. In the near future, the report suggests the impact of KBS is set to grow from 37% to 71% in organisations.
3. Artificial Neural Networks
Artificial Neural Networks (ANN) are computing systems designed to replicate biological neural networks and allow for independent decision-making based on mass data analysis. ANNs key benefit for project managers is in its estimation and calculation capacity. By analyzing massive amounts of data, studying historic project execution and pulling layers from different sources make for more accurate estimations than ever before. ANNs are ‘data-hungry’, meaning the more data you feed it, the more accurate it gets.
4. Deep Learning
Deep learning is a subset of machine learning that applies artificial neural networks inspired by human learning processes to create algorithms that can learn from a wide quantity and variety of data. Deep learning has the capacity to ‘learn’ from various data sources such as images, videos, and audio that make it particularly inept for speech and conversational systems.
Chief data officer at PMI, Mark Broome says, “Advanced forecasting and deep learning models will assist in predicting work effort activities, tracking project progress and updating forecasts as the project progresses.”. Though yet to achieve full widespread implementation, deep learning models are already impacting 21% of organisations and expected to impact a further 63% in the near future based on the PMI report.
5. Robotic Process Automation
Robotic Process Automation (RPA) can be seen as the easiest gateway for AI into project management. RPA is a form of business process automation that deploys metaphorical ‘bots’ to perform specific tasks through a defined set of instructions. These instructions are typically limited to frameworks built on ‘if, when, else’ statements to complete tasks.
RPA is currently already taking over many menial administrative tasks of project managers from invoice approvals to reporting. This will significantly lift the load off project managers and allow them to focus on more important value-adding activities such as ideation, communication and strategic planning. At its current state, RPA has already impacted 21% of organisations and is slated to make moderate to high future impact on 62% of organisations.
What does AI in project management look like?
All this talk about AI technologies and their capabilities, but what will it realistically look like when it is rolled out in our organisations in the near future. Like any other revolutionary change, AI will come in stages and most organisations will not be able to fully harness its potential in one full sweep. Make sure to check out our post on the evolution of AI in project management to get a realistic image of how AI will be integrated into your everyday activities.