The Latest Ai In The Steel Industry Statistics Explained
Capgemini’s research found that, AI-enhanced predictive maintenance of industrial equipment could potentially save $600 billion by 2025 in the steel industry.
This statistic indicates that implementing AI-enhanced predictive maintenance in the steel industry has the potential to bring about significant cost savings of up to $600 billion by the year 2025. Predictive maintenance involves using artificial intelligence technology to predict when equipment failures are likely to occur, enabling proactive maintenance instead of reactive repairs. By preventing unexpected downtime and equipment failures, companies can reduce maintenance costs, improve productivity, and lengthen the lifespan of their industrial equipment. The research conducted by Capgemini highlights the substantial financial benefits that can be realized by harnessing AI technologies in the steel industry to optimize maintenance practices and ultimately drive cost savings on a large scale within a relatively short timeframe.
An analysis by the McKinsey Global Institute found that nearly 70% of companies in the steel industry are piloting the use of AI in some form.
The statistic indicates a significant trend within the steel industry where a substantial majority of companies, close to 70%, are currently experimenting with the implementation of Artificial Intelligence (AI) in their operations. This suggests a widespread interest and investment in leveraging AI technology to enhance processes, improve efficiency, and drive innovation within the steel sector. The findings by the McKinsey Global Institute point towards a growing recognition among steel companies of the potential benefits and competitive advantages that AI can offer, leading to increased adoption and exploration of AI solutions across various aspects of their business operations.
Accenture reports that nearly two-thirds of industrial firms in the steel industry are planning to implement AI within the next three years.
The statistic provided by Accenture indicates that a significant proportion of industrial firms in the steel industry have plans to incorporate artificial intelligence (AI) technologies into their operations within the next three years. Specifically, almost two-thirds of companies in this sector are looking to leverage AI tools and applications to enhance various aspects of their business processes, production efficiency, and decision-making capabilities. This proactive approach towards adopting AI demonstrates a growing recognition within the steel industry of the potential benefits that advanced technologies can bring, such as improving productivity, reducing costs, and staying competitive in a rapidly evolving market landscape. This statistic highlights a trend towards embracing AI-driven digital transformation initiatives among steel companies to drive innovation and achieve strategic objectives in the near future.
A study by PwC found that 80% of leaders in industrial manufacturing, including the steel industry, expect their workforce and machines to be digitally connected by AI by 2020.
The statistic from a study by PwC indicates that a large majority (80%) of leaders in the industrial manufacturing sector, particularly within the steel industry, anticipate that both their workforce and machines will be digitally connected using artificial intelligence (AI) technology by the year 2020. This suggests a significant trend towards the integration of AI-driven solutions in the manufacturing sector, with decision-makers foreseeing a future where digital tools and machine learning capabilities play a crucial role in driving efficiency, productivity, and innovation within their operations. The statistic highlights the growing importance of AI technologies in transforming traditional manufacturing processes and underscores the strategic focus on digital connectivity as a key driver of competitiveness and success in the industry.
According to Boston Consulting Group, using AI models in the steel industry can improve yield predictions by up to 3%.
This statistic from the Boston Consulting Group indicates that incorporating artificial intelligence (AI) models in the steel industry can lead to a significant improvement in yield predictions. Specifically, the use of AI can enhance the accuracy of predicting yields in the steel manufacturing process by up to 3%. This means that by leveraging AI technology, steel manufacturers have the potential to better forecast the amount of usable steel that can be produced, which can have positive implications for production efficiency, cost reduction, and overall operational performance within the industry. By utilizing AI models, steel companies can not only optimize their processes but also potentially increase their overall economic output through improved yield predictions.
A report by Steelcase found that AI technology used in the steel industry has experienced a growth rate of about 14% since 2017.
The statistic presented in the report by Steelcase indicates that artificial intelligence (AI) technology utilization within the steel industry has been steadily growing at a rate of approximately 14% since 2017. This growth rate suggests that the steel industry is increasingly adopting AI technologies to enhance and optimize various processes such as production, quality control, and resource management. The significant increase in AI usage signifies a substantial shift towards automation and innovation within the steel sector, potentially leading to improvements in efficiency, productivity, and overall competitiveness of companies operating in this industry.
According to McKinsey, AI-based forecast improvements in the steel industry could result in a 2% to 3% reduction in raw materials cost.
The statistic indicates that utilization of artificial intelligence (AI) in forecasting within the steel industry has the potential to offer significant cost savings. Specifically, the forecast improvements enabled by AI technology could result in a 2% to 3% reduction in raw materials cost for steel production. This suggests that AI algorithms and predictive analytics can enhance the accuracy of demand forecasting, inventory management, and resource allocation in the steel sector. By leveraging AI-based forecasting tools, steel companies can optimize their raw materials procurement processes, minimize wastage, and ultimately drive down operational costs, leading to improved efficiency and competitiveness in the industry.
IDC reports that 30% of G2000 companies will have AI embedded within their supply chain operations by 2022, impacting various sectors, including the steel industry.
The statistic from the IDC indicates that by 2022, 30% of the top 2000 companies globally are expected to integrate artificial intelligence (AI) into their supply chain operations. This strategic move is anticipated to have wide-ranging effects across different industries, notably impacting sectors like the steel industry. By incorporating AI technologies into their supply chain processes, companies aim to enhance operational efficiency, optimize inventory management, improve forecasting accuracy, and streamline production processes. This statistic underscores the increasing trend towards digital transformation and the adoption of cutting-edge technologies to drive innovation and competitiveness in the business landscape.
A report by Forrester found that AI can help identify energy waste and inefficiency in the steel industry, potentially reducing energy costs by up to 20%.
The statistic implies that the application of artificial intelligence (AI) technology in the steel industry can lead to significant improvements in energy management. The report by Forrester suggests that AI algorithms have the capability to analyze vast amounts of data to pinpoint instances of energy waste and inefficiency within steel manufacturing processes. By identifying and addressing these inefficiencies, the steel industry has the potential to reduce its energy costs by up to 20%. This statistic highlights the transformative impact that AI can have on enhancing operational efficiency and sustainability in the steel sector, ultimately leading to cost savings and environmental benefits.
KPMG estimates that by 2022, more than half of all additional investments in the manufacturing sector, including steel, will be focused on applications that enhance intelligence and predictability.
The statistic provided by KPMG suggests that by the year 2022, over 50% of the increased investments in the manufacturing sector, particularly within industries like steel production, will be directed towards advancements in intelligent technologies and predictive analytics. This indicates a growing trend towards leveraging data-driven insights and automation to improve efficiency, quality control, and overall operational performance within the manufacturing sector. Companies are increasingly recognizing the value of incorporating intelligent systems and predictive capabilities into their processes to gain a competitive edge, drive innovation, and meet the evolving demands of the market, thereby highlighting the importance of embracing technological advancements to stay ahead in the manufacturing industry.
ABI Research predicts that by 2023, over 20% of the global industrial base in sectors like steel would use AI technology for maintenance purposes.
This statistic from ABI Research forecasts that by the year 2023, more than one-fifth (20%) of the worldwide industrial sector, particularly in industries such as steel production, will incorporate artificial intelligence (AI) technology for maintenance activities. This prediction suggests a significant shift towards the adoption of AI-driven solutions in industrial settings, highlighting the growing importance of leveraging advanced technologies to improve operational efficiency and enhance maintenance practices. By embracing AI tools, companies in sectors like steel manufacturing can streamline maintenance processes, reduce downtime, optimize resource allocation, and ultimately enhance productivity and competitiveness in the global market.
Tekla notes that integrating AI with Building Information Modelling (BIM) could help reduce steel wastage by 15-20% in constructions.
The statistic suggests that incorporating artificial intelligence (AI) technology with Building Information Modelling (BIM) systems has the potential to significantly decrease steel wastage in construction projects. Specifically, the integration of AI with BIM could lead to a reduction of steel wastage by 15-20%. This improvement is based on the ability of AI algorithms to optimize designs, enhance efficiency in material usage, and minimize errors in construction processes. By harnessing the power of AI in conjunction with BIM, construction companies can streamline their operations, make more informed decisions, and ultimately contribute to a more sustainable and cost-effective construction industry.
Deloitte projects that by 2021, 20% of large manufacturing firms, including those in the steel industry, will have integrated AI with their industrial safety systems.
This statistic from Deloitte predicts that by the year 2021, approximately 20% of large manufacturing firms, particularly those in the steel industry, will have incorporated artificial intelligence (AI) into their industrial safety systems. This suggests that a significant portion of industrial companies are expected to leverage AI technology to enhance safety measures within their operations. By integrating AI into safety systems, organizations can potentially improve risk management, prevent accidents, and optimize overall workplace safety protocols. This projection underscores the growing trend of digital transformation and the adoption of cutting-edge technologies within the manufacturing sector, highlighting the increasing importance placed on utilizing AI to drive improvements in safety and operational efficiency.
A study by Accenture shows that AI could potentially increase profitability rates by over 38% in the steel industry.
The statistic provided indicates that according to a study conducted by Accenture, the implementation of artificial intelligence (AI) has the potential to significantly improve profitability rates within the steel industry. Specifically, the study suggests that AI technologies could lead to a substantial increase of over 38% in the industry’s profitability. This implies that AI could offer valuable opportunities for steel companies to enhance operational efficiencies, optimize production processes, reduce costs, and potentially generate higher revenues. The statistic highlights the transformative impact that AI can have on the steel industry, potentially driving significant financial gains for those who leverage these advanced technologies effectively.
According to Infosys, 70% of manufacturing firms, including steel industry companies, will invest in AI-powered predictive analytics by 2025.
The statistic provided by Infosys indicates that by the year 2025, 70% of manufacturing firms, specifically those in the steel industry, are projected to invest in AI-powered predictive analytics. This suggests a significant trend towards adopting advanced technologies within the manufacturing sector to leverage predictive analytics capabilities driven by artificial intelligence. Such investments are indicative of a proactive approach by these firms to enhance decision-making processes, anticipate market trends, optimize operations, and ultimately improve efficiency and competitiveness in the industry. The increased focus on AI-powered predictive analytics reflects a recognition of the value these technologies can bring in driving innovation, streamlining processes, and gaining a competitive edge in the evolving landscape of manufacturing industries.
McKinsey Global Institute estimates that AI could potentially unlock $13 trillion in global economic activity by 2030, with its application in various industries, including steel.
The statistic from McKinsey Global Institute suggests that the widespread implementation of artificial intelligence (AI) has the potential to significantly impact and revolutionize global economic activity by unlocking an estimated $13 trillion by the year 2030. This estimation includes the application of AI technology across a wide range of industries, such as steel manufacturing, where AI can optimize processes, enhance productivity, and drive innovation. By leveraging AI in industries like steel, companies can improve efficiency, reduce costs, and create new opportunities for growth and development, ultimately contributing to the overall economic advancement on a global scale.
References
0. – https://www.www.abiresearch.com
1. – https://www.www.steelcase.com
2. – https://www.www.capgemini.com
3. – https://www.advisory.kpmg.us
4. – https://www.www.tekla.com
5. – https://www.www2.deloitte.com
6. – https://www.www.bcg.com
7. – https://www.www.pwc.com
8. – https://www.www.infosys.com
9. – https://www.www.forrester.com
10. – https://www.www.mckinsey.com
11. – https://www.www.idc.com
12. – https://www.www.accenture.com
