AI beyond the buzzword

Antonio Nieto-Rodriguez & Ricardo Vargas

Originally published on APM

Artificial Intelligence is no longer a distant concept confined to sci-fi movies or elite tech companies. Today, some organisations are already leveraging AI to navigate their unique project management challenges. AI-powered tools address issues from resource allocation to risk mitigation, ushering in a new era of efficiency and effectiveness.

AI is set to revolutionise how projects are executed and managed, from bolstering decision-making capabilities to optimising resource allocation. Here are some concrete examples and data, underscoring the potential and tangible value that AI can bring to the project management field:

  1. Enhanced decision-making: AI’s ability to handle vast amounts of data at high speeds allows for real-time insights and predictive analyses. Accenture reported that 79% of executives agree that AI is instrumental in creating new insights and better decision-making processes. For instance, Rolls-Royce uses AI to analyse data from its aeroplane engines, enabling it to anticipate problems and make informed decisions that could save millions in potential repairs and downtime.

1.Increased efficiency: AI’s automation capabilities can handle routine tasks and free up team members to focus on more strategic tasks. According to a report by McKinsey, AI has the potential to automate about 50% of the activities employees are paid to do, leading to significant time and cost savings. In project management, IBM has been leveraging its AI platform, Watson, to automate routine tasks and project monitoring activities. By employing natural language processing to handle communication and documentation, and machine-learning algorithms for risk prediction and task prioritisation, Watson has reportedly improved productivity by up to 20%.

1.Improved risk management: AI’s predictive capabilities can identify potential risks ahead of time, allowing for proactive risk mitigation. A report by PwC suggested that AI could reduce project cost overruns by up to 10%. In a different application, KPMG’s AI platform, KPMG Clara, uses machine learning to perform risk assessments. This helps identify financial irregularities and other potential risks before they escalate, allowing teams to mitigate them and proactively reduce project overruns.

1.Optimised resource allocation: AI can forecast future resource needs, leading to optimal resource allocation. An illustrative example can be found in the construction sector, where ALICE Technologies has developed an AI-driven platform. This platform uses AI to plan, schedule and manage complex construction projects, predicting the resources needed for different tasks and phases of construction. This predictive capability enables more effective resource allocation, with users reporting efficiency improvements in resource deployment of up to 15%.

1.Enhanced stakeholder communication: AI can generate tailored, up-to-date reports for different stakeholders. This capability enhances transparency and communication, significantly improving stakeholder satisfaction and trust. Microsoft’s Project Cortex, for instance, uses AI to provide personalised, timely updates to team members, improving communication and collaboration. Learning and continuous improvement: AI’s ability to learn from past projects and continuously improve future performance promises a step change in project outcomes. AI-powered project management tool ClickUp has a feature that learns from past task estimates to predict future task durations, enabling better planning and scheduling. …

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