New roads and new… worlds are being “unlocked” by Artificial Intelligence with industry, manufacturing, construction and agriculture reaping the rewards of growth as they take advantage of the endless possibilities provided by the most advanced form of AI, Productive Artificial Intelligence which is able to create text, images or other media using generative models.
The spread of Artificial Intelligence is expected to be rapid in the near future, putting countries’ economies in front of key challenges that “require” digital answers. Industry, manufacturing, agriculture, construction are some of the sectors that will be at the “edge” of PTN development with the data changing at a frenetic pace.
It is estimated that Artificial Intelligence can add more than $120 billion dollars to each country’s GDP, about $250 billion over a 15-year period. It becomes clear that artificial intelligence can, under certain conditions, be a “gold mine” for the economies of the countries that will use it, contributing tens of billions of dollars annually to their GDP.
1. Innovative and Sustainable Buildings “Architected” by Global Artificial Intelligence (GAI)
GAI has the potential to bring change to the construction industry by optimizing planning, scheduling and project management. GAI’s algorithms can help architects and engineers create innovative and sustainable building designs, taking into account factors such as local climate and available resources. Through predictive analytics, GAI can help identify potential cost overrun issues or delays in construction projects, enabling better risk management.
GAI is expected to affect constructions as well. Design aid models, efficient analysis and summarization of extensive documents such as contracts, specifications and reports, as well as assimilation of knowledge derived from the business world are just some of the areas where GAI can be used.
Finally, the utilization of GAI can contribute to the capture of digital twins of structures and further assist the work of engineers.
2. New products in industry – processing with the help of GAI
Opportunities at multiple levels can be brought by GAI to the manufacturing sector as it presents many possibilities
a) in the creation of new products,
b) to improve employee training,
c) in quality control,
d) in product design,
e) in logistics, and
f) to improve supply chain processes.
In particular, GAI through blockchain and smart contracts promise to increase data security, traceability and transparency while simultaneously reducing costs and management time. GAI is set to further accelerate the transformation of the manufacturing and industrial sector through algorithms that can create new content or designs from scratch, based on a set of rules and inputs, thereby enhancing innovation, efficiency and sustainability.
3. Ten times more investments in GAI applications in agriculture
The agricultural sector, a mainstay of most economies, stands to benefit significantly from the spread of GAI. In fact, estimates show that investments in GAI applications in agriculture will almost increase tenfold within the next decade, thus highlighting the main direction of innovation in this field.
One of its key applications is crop yield forecasting, where it leverages data and predictive models to provide farmers with valuable information about future crop production. In addition, GAI can contribute to resource conservation by helping farmers to efficiently allocate resources such as water, fertilizers and pesticides to maximize yields and minimize waste. Soil analysis is another area where GAI contributes, as it can assess soil health and composition, guiding farmers on best planting and cultivation practices.
The global size of GAI in agriculture was estimated at USD 238.06 million in 2022 and is expected to be worth around USD 2,287.84 million by 2037. An ally in food security and sustainable agriculture in the near future, which can help maximum farmers to adapt to the constantly changing environmental conditions, in terms of developing new seeds and plants resistant to climate change.
Finally, the synergy between GAI and Digital Twins in agricultural practices offers a promising avenue for precision agriculture. By creating digital replicas of agricultural crops, farmers can simulate various scenarios and test alternative strategies to boost productivity, conserve resources and optimize crop management. This blend of GAI and digital twins is poised to reshape the agricultural landscape, making it more sustainable and efficient.
