A startup called greyfly.ai, which offers delivery intelligence to boost project performance, has revealed that its Intelligent Project Prediction (IPP) technology outperforms human project managers in foretelling project outcomes and spotting underlying hazards. It has been discovered that the tool can yield capital savings of up to 20% by using artificial intelligence (AI) and a few data points to create predictions. This may help organizations choose the initiatives they should pursue more wisely and save time for executives.
The largest professional organization for projects (PMI, 2021) reports that project performance hasn’t improved, with at least 35% of projects on average falling behind schedule, over budget, or experiencing scope creep. This is highlighted when projects get larger and more complex. According to the government’s Infrastructure and Projects Authority annual report 2021 on major projects, 135 (or 73% of the 184 projects with a total cost of £542 billion) were classified as Red or Amber (where there are at least significant issues), and data indicates that the situation is getting worse.
Research indicates that AI use will rise, and according to APM (2022), another project professional group, 76% of survey respondents said they will use AI to analyze the vast amounts of data in complicated projects to aid in project decision-making.
Greyfly.ai is utilizing AI to raise the probability that projects will be successfully completed. Even in situations where a project has not even begun, IPP ingests project data to forecast future project performance. The system is independent of the tools a business currently employs and collects information from several sources. After data preparation, it is sent to the AI analytics engine where machine learning algorithms and predictive analytics are used to uncover hidden patterns, explain future performance, and identify potential dangers.
IPP and the use of machine learning may be the answer to help leaders boost performance if a firm with a big portfolio experiences uneven project costs and delivery.
The first step in implementing AI in project management is to evaluate the data and its predictive power. Lloyd Skinner, CEO, of greyfly.ai stated, “Data benchmarking can be undertaken swiftly and surprisingly few data points are required to enable prediction with relatively high levels of confidence”.
