Industrial Transformation Unveiled: End User Insights on Smart Manufacturing

Executive Overview

ARC Advisory Group conducted an online survey in Q4 2024 with the participation of 591 global respondents. The respondents were end users with influence/decision making power and/or knowledge of their industrial organization’s adoption and use of smart manufacturing/digital transformation, industrial artificial intelligence (AI) and energy transition initiatives and technologies.

The survey results provide valuable insights into the progress, challenges, priorities and outcomes associated with these efforts. Key findings from the survey demonstrate significant strides have been made in the evolving landscape of industrial transformation:

• Digital Maturity Assessment:  Conducting a digital maturity evaluation provides a clear understanding of current capabilities and identifies critical gaps. This foundational step enables the development of a tailored transformation roadmap, ensuring competitiveness, efficiency, and compliance. Without this assessment, organizations risk inefficiencies, missed opportunities, and regulatory challenges, making it essential for driving sustainable growth. 
• Strengthen AI and Cloud Adoption: Accelerating AI and cloud adoption is essential for enhancing scalability, agility, and data-driven decision making. Cloud-based AI solutions enable real-time insights, improve operational efficiency, and support seamless collaboration across systems. By leveraging these technologies, organizations can drive innovation, optimize resource utilization, and stay competitive in an increasingly digital landscape.
• Data Quality and Governance: Establishing strong data management frameworks is critical to ensuring the accuracy and reliability of AI-driven insights. Prioritizing data quality enhances decision making, while robust security protocols address privacy concerns and regulatory compliance. A strong focus on data governance builds trust in AI systems and safeguards both organizational and customer data.
• Energy Transition Alignment: Integrating decarbonization, ethical sourcing, and circular economy practices into your strategy not only ensures regulatory compliance but also enhances brand reputation. Leveraging AI-driven efficiency solutions and smart manufacturing can further reduce costs and environmental impact, positioning your organization as a leader in sustainable innovation.

ARC Survey Methodology and Demographics

ARC Advisory Group conducted an online survey between November and December 2024 with the participation of 591 global respondents. The respondents were end users with influence/decision making power and/or knowledge of their organization’s adoption and use of smart manufacturing/digital transformation, industrial artificial intelligence (AI) and sustainability/energy transition initiatives and technologies.

AI and Cloud Adoption Drive Transformation

The survey results highlight the impact of AI and cloud infrastructure adoption as the cornerstone to industrial transformation. With 54 percent of respondents identifying AI & ML as the most impactful technology, it is clear that industrial industries see intelligence driven automation as a game-changer. This is not just for efficiency but also for innovation and decision making. However, AI adoption does not exist in isolation – its success is tied to cloud infrastructure and edge to cloud integration, underscoring the growing need for scalable, high performance computing environments to manage massive data flows.

Another takeaway is the dual emphasis on clean energy technologies, reflecting a growing urgency to align digital transformation with environmental responsibility. This approach not only helps organizations meet regulatory requirements but also drives innovation and efficiency alongside energy transition.

Technologies, such as physical robots, digital twins and the Industrial Metaverse are expected to have a significant impact in the next three years. This suggests that while the industry recognizes their long-term potential, many companies are still prioritizing core digital capabilities – such as AI, cloud infrastructure, and automation, before scaling into more advanced and specialized innovations. As these foundational technologies continue to mature, adoption of next-generation solutions like digital twins is likely to accelerate.

Table of Contents

• Executive Overview
• ARC Survey Methodology and Demographics
• AI and Cloud Adoption Drive Transformation
• AI Implementation: Navigating the Roadblocks
• Most Organizations Still in Early to Mid-Stage of Digital Transformation
• Top 2025 Initiatives Driving Industrial Investments
• Recommendations
• Appendix

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