Management Summary Research Study “The Influence of Artificial Intelligence and Additive Manufacturing on Sustainable Manufacturing Practices and Their Effect on Performance”

This study explores the synergistic impact of Artificial Intelligence (AI) and Additive Manufacturing (AM) on sustainable manufacturing practices and overall firm performance, with a specific focus on small and medium-sized enterprises (SMEs) in the Czech Republic. Drawing on a survey of 267 firms and employing partial least squares structural equation modeling (PLS-SEM), the research investigates how AI and AM influence sustainable product design (SPD), sustainable manufacturing processes (SMP), and sustainable performance—encompassing environmental, social, and financial dimensions.

The findings demonstrate that AI has a significant and positive influence on AM, SPD, and SMP. AI enables better decision-making, predictive maintenance, and real-time process optimization, making manufacturing more resource-efficient and responsive. AM, on the other hand, supports waste reduction, energy efficiency, and customization through layer-by-layer production methods, facilitating localized and on-demand manufacturing. Importantly, SPD and SMP serve as mediating mechanisms—meaning the benefits of AI and AM are only fully realized when firms consciously redesign their products and processes with sustainability in mind.

This has critical implications for management. First, investing in advanced technologies is not enough—firms must align technological deployment with sustainability-focused design and operational strategies. Second, sustainable manufacturing is no longer a cost center but a source of competitive advantage. It enables compliance with tightening EU regulations, reduces exposure to resource volatility, and appeals to environmentally conscious consumers and investors.

For Czech SMEs in particular, this research underscores a strategic opportunity. While resource constraints can hinder the adoption of advanced technologies, targeted investments in AI-enhanced design and 3D printing can significantly improve operational efficiency and sustainability outcomes. Government incentives and EU funding for green innovation may help bridge the investment gap.

Policymakers should therefore focus on supporting AI and AM adoption among SMEs through funding, training, and regulatory alignment. Educational institutions must also evolve to equip future professionals with interdisciplinary skills—spanning data science, engineering, and sustainability management.

In conclusion, sustainable transformation in manufacturing depends not only on access to advanced technologies but also on the ability to integrate them into eco-innovative, performance-oriented business models. Firms that strategically link AI, AM, SPD, and SMP will be best positioned to lead in the green, digital economy of the future.

Implications for Managers:

Technology alone is not enough: Investing in AI and Additive Manufacturing (AM) technologies must be accompanied by deliberate changes in product design and manufacturing processes. Without such integration, the full sustainability and performance benefits may not materialize.
Sustainable design is a competitive lever: Sustainable Product Design (SPD) is not just an environmental concern—it drives product quality, innovation, and customer value.
Managers should incorporate eco-design principles from the earliest stages of product development.
Manufacturing efficiency and resilience go hand in hand: AI-enhanced Sustainable Manufacturing Processes (SMP) reduce waste, improve energy use, and boost operational flexibility—key to managing volatility in supply chains and regulations.
SMEs can compete through smart sustainability: Even with limited resources, SMEs can gain competitive advantage by adopting focused AI/AM solutions that improve sustainability performance and help meet rising market and regulatory demands.
Cross-functional collaboration is critical: Realizing the full value of AI and AM requires breaking silos between design, operations, and sustainability teams. Managers should promote integrated planning and data-sharing to drive systemic improvements.