National Academy of Construction
Recognizing Industry Leaders in Engineering and Construction Since 1999
Part 4 of the series integrates the discussion, providing a path forward. Action today can shape the future of the industry for generations to come. It is imperative for industry stakeholders-leaders, educators, and practitioners-to unite in their commitment to embracing technological advancements.
This third part in the series takes a brief but closer look at financial related risks. The discussion of each of these risks is designed to stand on its own so there will be some repetition of mitigation strategies across several risks.
The engineering and construction industry faces numerous technology adoption and deployment risks beyond those that can be simply ascribed to unfavorable risk/reward ratios. This second part of the series looks specifically at management risks related to technology adoption.
The engineering and construction industry has lagged in the development and adoption of new technologies. This first part of the series looks at technology-specific risks and rewards.
This Executive Insight provides a comprehensive overview of collaborative robots, commonly known as cobots, which are revolutionizing the engineering and construction industries.
This executive insight focuses on organizational and management considerations that E&C organizations should weigh as they consider digitizing QT operations by deploying artificial intelligence (AI) software.
Artificial Intelligence represents tremendous potential both within the E&C industry as well as society more broadly, with predictions that AI could drive a seven percent (or almost $7 trillion) increase in global GDP and lift productivity growth by 1.5 percentage points over a ten-year period.
The E&C industry is undergoing a significant transformation driven by technological advancements. Many of these advancements have been developed, are well-documented, and have been successfully adopted in other industries.
The engineering and construction industry is experiencing a transformative shift with the integration of AI. Applying AI in the industry is evolving rapidly, particularly with respect to construction safety.
This Executive Insight focuses on three broader innovation cycles (not engineering and construction industry specific), their impact, how the engineering and construction industry has capitalized on each cycle, and whether the industry was a leader or a laggard.
This Executive Insight focuses on broader, more systemic opportunities for innovation.
This Executive Insight illustrates the range of innovations that are possible.
All firms struggle with innovation, whether that innovation be incremental or revolutionary. In part, this struggle is due to the use of traditional, closed innovation systems.
Periodically it is necessary to question whether a current paradigm will suffice into the future.
This Executive Insight reflects the author's experience as a member of engineering, construction, and industry organizations focused on innovation within the E&C industry.
This Insight is written from a perspective of the connection of current events in social activity stemming from the COVID-19 pandemic and the phenomena of large-scale retirements.
AI makes it possible for machines to learn from experience, adjust to new inputs, and perform human-like tasks. Examples are computers learning to play chess or Jeopardy™ using AI, for intelligent assistants (Siri; Alexa), or for self-driving cars.
Artificial Intelligence (AI) enabled systems, machines, and algorithms undertaking cognitive tasks raise a myriad of ethical issues. The primary concern is to ensure that AI does not harm, directly or indirectly, humans or the environment.
The interest in the deployment of artificial intelligence (AI) into the management of projects, especially large complex projects, is growing. Other NAC Executive Insights1 highlight some of the limitations, cautions, and transparency required while at the same time outline the benefits available.
Project management AI is founded on predictive analytics. It reflects uncertainty, which is best described as a confidence level. Confidence will change over time as the project progresses and new data are considered by the AI model.
This Executive Insight looks at the cybersecurity landscape facing engineering and construction and is intended to provide a framework for discussion and action by engineering and construction leaders.
This Executive Insight looks at the emerging nature of Construction 4.0.
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