The Future of Product Development: How AI & Automation are Changing Design

Product development is undergoing a major transformation, driven by the rapid advancement of artificial intelligence and automation.

Traditional design workflows are shifting away from manual iterations and siloed systems toward intelligent, automated, and cloud-connected solutions. Companies embracing this evolution are achieving faster innovation, lower costs, and more sustainable outcomes.

AI plays a central role in this digital shift, empowering designers and engineers to focus on innovation while optimizing manufacturing through deeper insights into production processes. By adopting AI technologies, organizations can stay agile in a competitive market and realize key benefits such as:

• Improved Efficiency: AI accelerates the entire product development cycle, from design to production, by automating repetitive tasks and enabling manufacturing-optimized designs.
• Cost Reduction: Enhanced efficiency, reduced waste, and minimized downtime lead to significant operational cost savings.
• Quality Control: AI-powered machine vision detects defects and inconsistencies in real time, improving product quality and reducing errors.
• Sustainability Optimization: AI helps mitigate supply chain disruptions and optimize resource usage, driving more sustainable and resilient production processes.

By leveraging these capabilities, businesses can not only keep pace with change but lead the future of product development.

Understanding AI: Key Concepts & Use Cases

Artificial Intelligence (AI) refers to computer technologies designed to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. While the growing popularity of chatbots like ChatGPT and Google Gemini has brought attention to generative AI, these tools represent just a fraction of AI’s full potential. In the context of product design and manufacturing, AI encompasses a wide range of applications that are reshaping how products are imagined, created, and delivered. Let’s take a closer look at the key categories of AI and their impact on product development.

Generative AI: Pushing the Boundaries of Design Innovation

Generative AI leverages large datasets to produce new content, ideas, patterns, and solutions—reshaping how products are conceptualized and developed. By automating complex design processes and optimizing for performance and manufacturability, Generative AI empowers engineers to work more efficiently and creatively.

With this technology, product designers can:

• Automate Tedious Tasks: Quickly generate 2D documentation, create interactive manufacturing files, and build part assemblies for 3D CAD models.
• Accelerate Creative Exploration: Rapidly visualize and iterate on design concepts, enabling teams to explore a broader range of innovative ideas in less time.

Generative Design: Algorithmic Design Optimization

Often mistaken for Generative AI, Generative Design is a broader algorithmic approach that uses real-world simulations to deliver optimal design solutions for specific engineering challenges. By inputting key parameters such as materials, manufacturing methods, and performance goals, engineers can generate and evaluate a wide range of design variations optimized for strength, efficiency, and manufacturability.

Key benefits of Generative Design include:

• Accelerated Design Exploration: Rapidly analyzes thousands of potential solutions, allowing engineers to identify the most effective options while significantly reducing design time.
• Performance-Driven Results: Considers stress loads, weight distribution, and material use to produce designs that are both lightweight and highly durable.
• Sustainability and Cost Savings: Optimized designs often require fewer raw materials, resulting in lower production costs and a smaller environmental footprint.

Machine Learning: Enhancing Manufacturing Processes

Machine Learning is a branch of AI in which systems learn from large datasets to identify patterns and make predictions without being explicitly programmed. In design and manufacturing, Machine Learning is transforming workflows through predictive analytics, automation, and smarter decision-making. Its applications in product development are both broad and impactful:

• Predictive Maintenance: Machine Learning algorithms analyze sensor data from equipment to anticipate failures before they happen. This reduces downtime, extends machinery lifespan, and boosts overall productivity.
• Quality Control: AI-powered visual inspection systems use cameras and image analysis to detect defects with greater accuracy and speed, improving product quality while reducing waste.
• Design Optimization: Advanced algorithms evaluate a wide range of design permutations by factoring in material properties, fabrication methods, costs, and time constraints. This enables engineers to deliver innovative solutions that are already optimized for efficient manufacturing.

Deep Learning: Advanced AI for Complex Problem Solving

A specialization of Machine Learning, Deep Learning incorporates multiple layers of data and analysis and machine learning algorithms with biologically inspired logical structures called “artificial neural networks.” Commonly used for facial recognition, speech recognition, and bioinformatics like DNA analysis, Deep Learning has useful applications in product development:

• Autonomous Manufacturing: AI-driven robotic systems can perform and adapt to new production tasks without complex reprogramming.
• Visual Inspections: Deep learning algorithms interpret images and precisely detect defects in the manufacturing process. By assisting in scheduling preemptive repairs, Deep Learning technology helps manufacturers avoid costly downtime.

How Leading Design & Manufacturing Organizations Use AI

Organizations are continuing to uncover valuable AI applications, with uses ranging from automated transcription of meeting minutes to assistance laying out factory floors. According to the 2024 Autodesk State of Design & Make Report, manufacturing business leaders are approaching, or have already achieved, their goal of incorporating AI into their processes and workflows. Of those surveyed for the report, 78% believe AI will enhance their industry, while 66% believe that within the next 2-3 years, AI will be an essential industry wide tool.

The goal of implementing AI is to improve overall productivity – but what does that look like? For industry leaders in segments like Automotive, Building Products, and Life Sciences Manufacturing, AI is improving productivity through these use cases:

• Automating mundane, repeatable tasks
• Billing analysis
• Identifying product/asset performance gaps
• Producing informed design options
• Supplementing a skills gap
• Workplace safety and risk analysis

Autodesk Fusion offers powerful, integrated AI tools in a single solution for product designers and manufacturers that streamline the product development process and free up more time for innovation:

• Generative Design: While Generative Design leverages generative AI, it is a broader algorithmic process in which software runs real-world simulations. It is one of the most exciting advancements in product development; instead of designers manually iterating designs, they simply input a set of parameters, and the software generates multiple iterations of manufacturing-ready designs. Design outputs are high-performance solutions optimized for weight reduction, material efficiency, and manufacturing costs.
• Automated Modeling: Automated Modeling is a new feature in the Fusion Design Workspace. In combination with generative design technology, it automates the process of exploring and creating new design concepts, helping designers uncover new possibilities in how to approach a given design challenge.
• Automated Toolpaths: Available in the Autodesk Fusion Machining Extension, Automated Toolpaths automate repetitive CAM tasks; programming tasks with strategies and estimations that would normally take days are instantaneous with Toolpath Automation.
• Automated Drawings: Drawing Automation streamlines time-consuming drawing tasks, saving designers significant time. Fully customizable to suit your preferences, it automates creating and laying out drawing sheets for model components, placing sheet metal patterns and bend tables, placing parts lists and balloons for assemblies, rotating components to the best orientation for documentation, and more.

Embracing AI as a Strategic Advantage in Product Development

The future of product development is being redefined by artificial intelligence and automation. These technologies are no longer optional; they are essential for companies looking to stay competitive in a rapidly evolving market. From generative design and machine learning to fully automated workflows, AI is transforming every stage of the design to manufacturing process.

Solutions like Autodesk Fusion unify these powerful tools, helping teams work smarter, accelerate innovation, reduce costs, and improve product quality. As AI continues to evolve, the organizations that fully embrace it as a strategic advantage—not just a productivity tool—will lead the next era of design and manufacturing excellence.

Ready to take the next step? Contact Hagerman & Company to learn how we can help you implement AI-driven solutions tailored to your product development goals.