Questioning Reliability of AI in a Product's Journey from Development to Consumption
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Artificial Intelligence (AI) is making a significant impact on the engineering field, transforming design processes and product operations across various industries.
At the NVIDIA GPU Summit, a series of 2025 SBCs showcased the potential of AI hardware in the engineering sphere. A video series, including demonstrations of NanoEdge AI Studio, highlighted how AI could revolutionize the design process, raising questions about the trustworthiness of AI in circuit design and embedded systems.
The series delved into the role of AI in the tech industry, its impact on chip design workflows, and its potential in CAD tools and PCB stators. It also explored AI's role in IoT, test and measurement, and embedded hardware in a trusted AI ecosystem.
In the design process, AI acts as an intelligence layer that integrates with domain-specific tools like CAD, CAE, and PLM, transforming disconnected applications into cohesive, adaptive systems. AI automates high-effort, low-value tasks like drawing validation and rule enforcement, increasing throughput and consistency without increasing staffing. It captures expert logic to preserve and share engineering knowledge across teams, reducing dependency on individual expertise and supporting compliance across geographies and product lines.
In manufacturing and product operation, AI leverages machine learning and advanced algorithms to analyze real-time production data, optimize machine parameters, and streamline workflows, boosting throughput while reducing energy use and waste. AI-powered simulations enable virtual testing of production scenarios before physical implementation.
In creative industries, AI tools accelerate and broaden the design process, helping designers craft trendy, diverse styles more efficiently. AI has evolved from basic automation like resizing photos and color grading to powering smarter and faster design creation, increasing the market value of design AI technologies.
In process manufacturing, AI strengthens operations by enabling agility in managing shifting variables, providing decision support to offset loss of experienced personnel, and automating option generation for process design. AI virtual advisors help newer operators explore adjustments to improve safety, efficiency, throughput, and sustainability through natural-language interaction with large databases.
However, trust in AI remains a contentious issue. In a small software design group, the owner demanded that all developers use AI to augment their work. One senior software developer refused, claiming they could write better code. Despite their importance to the team, the owner allowed the senior developer's refusal initially. However, over time, AI boosted the accuracy and output of junior developers. The owner then demanded the senior developer to use AI, but they refused, leading to the senior developer's termination.
For those interested in learning more about AI's role in product lifecycles, an eBook titled "AI and Product Lifecycles: It's a Matter of Trust" is available for download. The eBook aims to answer whether AI can be trusted along the product lifecycle path.
In conclusion, AI's impact spans improving design efficiency and innovation, enhancing quality control and operational precision, supporting knowledge retention, and enabling more adaptive, data-driven product operations in various industries. The AI Takeover Week, which explores AI in the process of design, manufacturing, and operation of products, underscores the potential of AI to transform the engineering field.
Artificial Intelligence (AI) not only transforms design processes in various industries but also embeds technology within systems, such as embedded systems, through AI hardware like NanoEdge AI Studio showcased at the NVIDIA GPU Summit. Moreover, AI's role in the tech industry extends beyond circuit design and embedded systems, as it also influences chip design workflows, CAD tools, PCB stators, and IoT, eventually shaping the future of engineering.
