Fostering AI Adoption in SMEs: Key Insights and a Path Forward

Jun 28

By: Shree Parikh, Business Development Manager, US Center for Advanced Manufacturing

Inspired by the Industry Roundtable on AI by the US Center for Advanced Manufacturing and in partnership with Tulip in Boston

This report explores the challenges and opportunities associated with artificial intelligence (AI) adoption for small and medium-sized enterprises (SMEs) in manufacturing. The report aims to highlight the transformative potential of AI in enhancing product quality, operational efficiency, and overall business growth for SMEs. The report outlines key considerations and emphasizes the need for collaboration to address barriers and pave the way for widespread AI adoption within the manufacturing sector.

Introduction

The manufacturing landscape is undergoing a rapid transformation driven by technological advancements. Artificial intelligence (AI) is emerging as a powerful tool for businesses to thrive in this dynamic environment. While large enterprises have begun embracing AI, its widespread adoption among SMEs remains a work in progress. This report, inspired by the US Center for Advanced Manufacturing's recent roundtable on AI held in partnership with Tulip in Boston, sheds light on the key considerations for fostering AI adoption in SMEs, drawing on valuable insights from recent industry meetings and reports.

The Imperative for AI Adoption

SMEs in manufacturing face mounting pressure to enhance efficiency, improve product quality, and maintain competitiveness. AI presents a powerful solution to these challenges. Industry reports consistently highlight the transformative potential of AI in manufacturing, pointing to significant productivity gains, cost savings, and improved decision-making capabilities. For example, a 2023 McKinsey report cites successful "lighthouse" factories achieving a two to three times increase in productivity and a 50% improvement in service levels through AI implementation (McKinsey & Company, 2023). However, the same reports acknowledge challenges faced by SMEs, including resource limitations that can hinder AI adoption (McKinsey & Company, 2024).

Empowering SMEs through AI

Recent industry events highlight the growing focus on empowering SMEs to leverage AI. A key theme is the development of user-friendly AI tools with no-code interfaces. These tools democratize access to advanced technologies, enabling non-engineers to develop and deploy AI applications within their businesses (Deloitte, 2023). This can significantly lower the barrier to entry for SMEs and accelerate their AI adoption journey.

Challenges and Opportunities

Despite the compelling benefits, SMEs face challenges in adopting AI. A critical barrier often cited is the skills gap. The current workforce may not possess the necessary skills to work effectively with AI-powered technologies, requiring reskilling and upskilling initiatives (Boston Consulting Group, 2022).

Case Study: Outset Medical's AI-Driven Transformation

Outset Medical, a leader in dialysis technology, is deploying Tulip's AI Frontline Copilot® across its value stream to improve operational efficiency and quality control. The integration of AI has empowered operators with apps that enhance their troubleshooting capabilities by allowing them to quickly access manuals, operating procedures, and documentation to find the knowledge they need. This AI-driven approach makes root cause analysis accessible by searching historical data and identifying potential problems. As a result, operators can independently diagnose and resolve issues such as alarm codes, reducing downtime and improving operational speed with less supervision.

Tulip has enabled Outset Medical to quickly reduce non-value-added activities with accessible AI tools built into no-code apps. Generative AI helps Outset Medical respond more efficiently to FDA audits and paperwork, allowing the company to sift through large amounts of data and quickly extract specific answers. Implementing AI and no-code solutions makes data analytics accessible, lowers the barrier to entry, and transforms the way Outset Medical operates and makes decisions. Outset's success with Tulip and AI underscores its commitment to using cutting-edge technology to drive innovation and maintain a competitive edge in the medical device industry.

Analysis: Lessons from Outset Medical's AI Journey

Outset Medical's proactive approach to AI adoption serves as an inspiration for other SMEs. From the outset, the company prioritized technological integration, demonstrating that early commitment to digital transformation can yield significant competitive advantages. Outset Medical’s success highlights the importance of investing in AI tools and fostering a culture of innovation. For SMEs, embracing AI and collaborating with technology partners like Tulip can democratize access to advanced solutions, enabling operational excellence and sustained growthThe Road to Success: Collaboration is Key

Industry events consistently emphasize the need for a collaborative effort to support SME digital transformation. This involves creating a structured approach tailored for SMEs, with clear steps for initial assessment, implementation, integration, and continuous improvement. Leveraging the collective expertise and resources of industry leaders, technology providers, and policymakers is crucial. Additionally, fostering a culture of innovation and upskilling the workforce through targeted programs can empower SMEs to embrace AI with confidence.

Conclusion

AI presents a transformative opportunity for SMEs in manufacturing. By overcoming challenges and fostering a collaborative ecosystem, stakeholders can create a path for widespread AI adoption. This will empower SMEs to enhance product quality, optimize operations, and achieve long-term growth in the ever-evolving manufacturing landscape.

References

- Boston Consulting Group. (2022, June 14). Bridging the AI Divide in Manufacturing. Search for the report by title on BCG website or a general search engine.

- Deloitte. (2023). The future of manufacturing workforce. [Deloitte Manufacturing](https://www2.deloitte.com/us/en/pages/energy-and-resources/topics/industrial-manufacturing.html).

- McKinsey & Company. (2023). AI in manufacturing: The next frontier of performance in industrial processing plants [Report]. Retrieved from [McKinsey](https://www.mckinsey.com/industries).

- McKinsey & Company. (2024). How manufacturing's lighthouses are capturing the full value of AI [Report]. Retrieved from [McKinsey](https://www.mckinsey.com/capabilities/operations/our-insights/how-manufacturings-lighthouses-are-capturing-the-full-value-of-ai).

US Center Team