Need to Know: Artificial Intelligence

Headshot of Geetha Gopal

Geetha Gopal, PMP, explains how AI’s data-driven capabilities can help teams achieve outcomes more quickly—and with greater accuracy.

Amid a cascade of digital-driven new ways of working, organizations are steadily embracing—and harnessing—the power of artificial intelligence (AI). According to a 2022 global survey by IBM, 35 percent of companies are using AI, while an additional 42 percent are exploring AI adoption. It’s evolving from a nice-to-have tool to a business imperative: Half of organizations are realizing benefits from using AI, with 54 percent achieving cost savings and efficiencies.  

For project teams, turning over tasks to AI, machine learning or automation software is transforming how initiatives get delivered, says Geetha Gopal, PMP, Chief Operating Officer, Verdana, Singapore. AI integration also reveals new opportunities for project leaders to embrace the power of data. 

“The first thing an AI-based approach will do to an organization is to make them understand their own project data—and the need to generate more meaningful data,” Gopal says. “This thought process is a transformation in itself. Clean project data can increase the quality of outcomes, boost adherence to project plans, increase stakeholder satisfaction and better transition to operations.”  

Gopal shares four things project professionals can achieve with AI’s data-centric capabilities: 

Reduce the element of surprise.
The correlation capabilities of AI and machine learning help mitigate time and budget risks. If a project has a good tracking mechanism for generating quality data, we can build machine learning algorithms that can correlate multiple criteria and proactively identify gaps, send warning signals on potential roadblocks, identify their percentage of occurrence, and generate specific and timely reports. In complex project cost management, when we rely only on human intelligence to track cost overruns, this process is tedious and is also prone to errors. The best way forward is to combine AI-generated, correlated insights with human intelligence in making informed decisions to control costs. 

Become a bias buster.
There’s plenty of academic research to suggest projects are prone to cognitive biases, especially at the planning stage. By using historical data and processes like reference class forecasting, we can estimate realistic project values. When making key decisions on project investments, leaders can turn to historical data to avoid planning biases. With the right data, logic and training, AI and machine learning algorithms certainly help reduce biases in planning, estimating and decision making. Especially when there are several criteria to be correlated, AI can help.  

Create more time to flex power skills.
Generating reports takes up a lot of time for project managers. Yet several AI-based tools can provide instant, on-demand reporting in just a matter of minutes—and that frees up more time for project managers to strategize and lead. With the freed-up time, project managers will have more time to build better relationships with stakeholders, focus on strategic planning, review and validate controls, and pursue higher-quality standards. 

Accelerate decision making.
Project managers will find it easier to handle difficult problems with supporting data. AI accelerates decision making by complementing project objectives with data-driven recommendations. AI and machine learning algorithms can guide project managers to ask questions like: What is the next high-impact milestone that is expected to be missed? What is the percentage of occurrence of a 20-percent cost overrun in the next two months? What is high on the priority-urgency matrix? Data-driven insights improves decision-making time, which in turn increases productivity and steers projects toward better outcomes. 


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