Artificial intelligence (AI) is the branch of computer science focused on creating systems that can perform tasks that typically previously required human intelligence.
These tasks include learning from data, recognising patterns, solving problems, making decisions and understanding natural language. AI systems achieve this by using algorithms and models that can adapt and improve over time, often without explicit programming for each specific task (APM Project Data Advisory Group, 2023).
Definition from APM Body of Knowledge 8th edition
The primary benefit of AI in project delivery lies in its ability to process enormous quantities of data.
By analysing past and current project data, AI can enable more effective decision-making around project delivery – better predicting the future performance of a project by considering all the variables.
📖 Read: Getting started in project data
Popular AI-powered language models such as ChatGPT generate human-like text and responses. Day-to-day this can assist with time-consuming project tasks such as replying to emails, creating documents (user stories, consolidating research, end user docs, etc) and writing presentations.
Other AI tools
There are many other AI tools that are useful for project-based work.
Data intelligence expert James Garner told Project journal about the latest AI trends:
Microsoft has announced Copilot, an everyday AI companion designed to seamlessly integrate across Microsoft's most popular products, including GitHub, Microsoft 365, Bing and Edge, to offer a more tailored and efficient user experience.
GPT-4V has given ChatGPT the ability to analyse visual content. For example, GPT-4V can reconstruct website dashboards from screenshots, making the transition from design to prototype much quicker. It can also interpret and explain visual content like infographics.
📖 Read: How artificial intelligence is changing the game for project delivery
Expert systems
Expert systems is a term used for systems to support decision-making. These systems are stated to store “knowledge from experts”. Expert systems typically follow a rule-based approach and generally lack the ability to adapt and learn from previous data.
Machine learning progress
Machine learning tools are used to identify patterns and relationships in large data sets and are able to ‘learn’ from this data. A common machine learning tool is ‘neural networks’, which predict project success. Off-the-shelf solutions such as TensorFlow by Google and services by IBM Watson Studio have significantly increased the accessibility of these tools. However, research shows that the practical implementation of AI is often delayed due to managers being uncertain how it can be used in their organisation and the difficulty of reusing AI models for different purposes.
Deep learning
As a sub-set of machine learning, deep learning offers a more complex way of analysing data. The ‘black box’ phenomenon is often used to describe the difficulty in interpreting the reasons behind the output of deep learning models.
For anyone involved in project delivery across the public and private sectors, this research, Digital transformation and the AI imperative in public and private sector projects, offers clear, practical recommendations to help navigate digital change and lead with greater confidence.
Three key findings from the research:
AI has become a significant tool for project professionals when delivering projects. A report, Artificial intelligence in project management led by the University of Southampton explored the general perception of AI and the ease of use of AI technology within projects.
Six key findings arose from the research:
📖 Further reading: How we can learn to work with AI
How to write AI prompts for project management
This APM Learning module offers practical guidance on how project managers use AI, what prompt engineering is and why it matters.
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This APM report explores how human factors influence the integration of agile project management, digital tools and sustainability.
Based on surveys of practitioners based in North America, this research finds that trust, readiness and training are critical for successful adoption of AI and digital tools.
Methods and skills for project management
For anyone involved in project delivery across the public and private sectors, this piece offers clear, practical recommendations to help navigate digital change and lead with greater confidence.
This APM report explores how human factors influence the integration of agile project management, digital tools and sustainability.
Based on surveys of practitioners based in North America, this research finds that trust, readiness and training are critical for successful adoption of AI and digital tools.
Artificial intelligence (AI) is already having real-world impacts across the project profession. A growing number of organisations are considering implementing some form of AI to support project delivery, with some having done so already.
Association for Project Management (APM) has produced a series of case studies to help project, programme and portfolio professionals better understand the current impacts of AI and the journey towards adoption.
📖 Gleeds: A deep dive into success
📖 MIGSO-PCUBED: Predicting project outcomes with new AI capability, Intelligent Project Prediction
📖 Network Rail: Laying the groundwork for AI adoption with a data-first strategy
According to the APM research report Can Artificial Intelligence Learn to be a Project Professional? potential implications for the professional status of project management, no matter whether human project professionals or an AI tool are considered, there is no conflict in terms of the targets of human project professional learning and AI learning.
The fundamental target is to enhance project management performance and deliver project outcomes.
📖 Further reading: The future of artificial intelligence in project management 🔒 Member only
📖 Further reading: The AI project management driven revolution is here
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New technologies, and particularly Artificial Intelligence (AI) and Machine Learning (ML) are transforming all areas of project delivery in the engineering and construction sectors ... read more.
Recently, there has been a lot of interest in the potential of large pre-trained language models, such as OpenAI's GPT, to transform the field of project management. ... read more.
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