Industry Standards: Your AI-Era Legal Lifeline

Artificial intelligence is a process that has been generally described as developing systems to replicate the intellectual processes of human beings, i.e., thinking, analyzing and creating as if human. Within a very short time, AI has become ubiquitous. The public and private sectors are endeavoring to evaluate AI’s costs and benefits and how, once employed, it can be controlled. 

Initiatives to develop and expand the use of AI are seen in Executive Orders and the July 2025 White House Action Plan describing how incentivizing AI’s continued development and use will enable the U.S. to be the world leader in technology. While AI offers many opportunities, its increasing applications and use in manufacturing also have the potential to affect manufacturers’ responsibility for harm caused by AI-enabled or enhanced processes. 

AI use in manufacturing is increasing rapidly 

The National Association of Manufacturers published a 2025 report from the Manufacturing Leadership Council (a division of NAM) suggesting 51% of manufacturers currently employ AI. The report describes manufacturers anticipating increased use of AI by up to 80% in the next five years. Given this trend, manufacturers should consider how AI-produced results, be they quality assurance assessments or end-products themselves, will be judged. If AI is replacing the human element in the processes, then by what standards should the AI-assisted production be evaluated? If the process fails, then how will the process be judged and who will be responsible for those failures? 

AI is employed in robotics and automation to undertake repetitive tasks with the goal of increased precision, reliability and uniformity of results. AI predictive maintenance may monitor conditions posing wear and stress to equipment based upon sensor readings and data analysis, allowing for timely repair and replacement to avoid interruptions. Quality assurance and control may employ AI to detect anomalies and deficiencies approaching tolerance levels for early detection and correction. While these processes may not yet be completely given over to AI, the forecasts indicate they will become increasingly reliant upon developing more sophisticated AI. 

Adherence to standards critical for manufacturer responsibility 

As AI develops rapidly, so too have standards relating to AI’s deployment in manufacturing. Given that legal frameworks still include gaps pertaining to manufacturer liability for AI, it is best that companies adhere to existing standards while remaining informed about the changing AI landscape. The role of AI in the manufacturing process will certainly be scrutinized when legal claims are alleged to arise from that process. Industry standards have proven effective in providing guidelines and benchmarks by which manufacturers may establish compliance with the applicable “industry standard of care.” Product and component testing, approval, and certification provide industry imprimaturs of compliance with the applicable standards. 

The current state of standard-driven processes provides manufacturers with reasonable assurance that their materials and methods can be shown to have met expected levels of quality and performance. The legal system considers standards not only relevant and reliable but also sometimes determinative of a product’s soundness. As AI is increasingly relied upon, important questions relate to how AI might impact the standard of care analysis—the the legal process of evaluating whether a manufacturer’s actions and processes met the level of quality, safety and performance that the industry considers acceptable—and if so, what standards exist for the use of AI. 

AI-specific standards, and implications for manufacturing 

A March 2026 publication, “Standardization Environmental Scan: Artificial Intelligence (AI)” by the Advancing Standardization for Critical and Emerging Technologies’ Center of Excellence, is the first in a series of planned publications relating to critical emerging technologies. The ASCET AI report surveys the current developments of standards focused upon AI, describes the different types of standards, and outlines the progress and ongoing work of standards development and accreditation organizations like ASTM and ANSI. Because AI is applied in so many different contexts, the number and scope of standards already developed is impressive—333 AI-specific standards, according to the ASCET report. However, the report notes that coordinating independently developed standards adds yet another layer of complexity to achieving a goal of consistent standardization. The report contains a caveat that given the acceleration of AI advancements, standards organizations may have difficulty keeping pace with AI’s rapid evolution. 

The ASCET report also identifies areas of perceived gaps, such as a needed standard for human-AI interaction due to the prevalent use of AI in support roles, which may be addressed by developing standards. If AI is used for automation, predictive maintenance or to augment standardized quality assurance, filling this perceived gap with standard guidance will be of benefit to a manufacturer to establish industry practices for human-AI coordination. Another gap identified by a 2024 U.S. Senate Workshop Group stated that “Unclear legal frameworks make it difficult to assign responsibility for AI-caused harm.” Government and court intervention helping to clarify assignment of legal responsibility is an area requiring industry vigilance. If SODs may be challenged by AI’s acceleration, as ASCET warns, its speed may leave a deliberative body such as Congress far behind. 

Courts and legislatures that weigh the balance more in favor of consumer protection are likely inclined to endow the legal system with mechanisms to deal with the apparent complexities of AI-assisted legal liability by easing potential evidentiary hurdles to claims. Simply put, courts and willing legislatures may decide that AI processes may be judged differently according to newly enacted laws, regulations and rules. However, continuing the well-developed reliability of industry standards as benchmarks for manufacturing may be in the best interest of the private sector. Providing governments and judicial systems the option to rely upon consensus-driven industry standards may assist them in clarification of relative responsibilities in AI use. AI poses challenges given its rapid evolution but standards should continue to be developed for the use of AI to provide manufacturers with reasonable assurance that they may meet, and prove compliance with, an established “standard of care.”