Project Management Institute (PMI) released its 2019 Pulse of the Profession In-Depth Report: AI @ Work: New Projects, New Thinking. The report, a companion piece to AI Innovators: Cracking the Code on Project Performance, explores how artificial intelligence (AI) is changing the way projects are managed and delivered globally.
As AI projects become the norm, project managers need to better understand what technologies will help them streamline and improve their AI-based project work — or they risk being left behind. The new report highlights the top AI technologies project leaders are currently leveraging to boost project management productivity, and how to incorporate AI technologies into their overall project work.
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While project leaders are tapping into AI technologies to boost project productivity and quality, unlocking AI’s full potential requires building and constantly refreshing knowledge of emerging technologies. In fact, the report finds that organizations and their project leaders will need a high Project Management Technology Quotient (PMTQ) – a way of evaluating an organization’s ability to manage and integrate technology based on the needs of the organization or the project at hand – to turn AI strategy into reality.
“In today’s increasingly project-based economy, the most forward-thinking organizations know that the success of their strategies hinges on how well they can execute projects. And the race toward AI mastery is no exception,” said Michael DePrisco, vice president of global solutions at PMI. “As we see AI technologies continue to be integrated into organizations, the research indicates that project managers, especially those with a high PMTQ, are well prepared to play an integral role in implementation.”
Of the respondents to the study, 50 percent reported a high PMTQ (Innovators) and 10 percent reported only sometimes or never practicing the principles of the PMTQ (Laggards).
A majority of both groups say their project management skills and experience are a good foundation for managing AI. But the Innovators have the upper hand: 74 percent of Innovators say they’re confident their current skill set enables them to work with AI, compared with 51 percent of Laggards.
Even more so, Innovators cite having more awareness and experience with several AI technologies, including knowledge-based systems, decision management, speech recognition, and expert systems. These respondents also report delivering better outcomes when using AI technologies, including a decreased amount of time spent on activities like monitoring progress, managing documentation, as well as activity and resource planning.
The top technologies respondents cite as enhancing productivity are:
- Robotic process automation: Technology that mimics and automates human tasks to support corporate processes.
- Machine learning: Technology that allows computers to learn by employing pattern detection for improved decisions in subsequent situations.
- Reinforcement learning: A machine learning technique that enables software to learn in an interactive environment by trial and error using feedback from its own actions.
The top technologies respondents identify as increasing quality are:
- Anti-bias solutions: Technology that automatically identifies bias in a range of AI algorithms.
- Expert systems: Technology that emulates and mimics human intelligence, skills or behavior and usually offers expert knowledge in a particular field, topic, or skill.
- Knowledge-based systems: Technology that understands the context of the data being processed to help problem-solve procedures and support human learning, decision making, and actions.
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