Transforming Manufacturing Operations Through Technology

Manufacturing leaders are increasingly focused on developing strategic data activation frameworks that align insights with business objectives, delivering measurable value across the production cycle. However, significant barriers persist, including organizational resistance, skills gaps, and the need for advanced automation, AI-driven decision-making, and robust cybersecurity measures. Overcoming these challenges requires a holistic approach that integrates cultural change, cutting-edge technologies, and cyber-physical security strategies, experts say.

One of the most significant obstacles to digital transformation is organizational resistance. Around 70% of digital transformation initiatives fail due to misalignment with corporate culture, and 80% of manufacturers cite a lack of in-house expertise as a major barrier. "Our company, focused on process implementation, has experienced resistance. Without a commitment from upper management, we find their teams are similarly disengaged,” said Eduardo Rius, Country Sales Manager Mexico, Bizagi.

This highlights the need for reskilling programs and change management strategies to support adoption, which require strong communication with the tech provider and the potential user to identify the ways it can enhance adoption. "When clients have specific future production goals, present actions become crucial. A client with 50 largely manual production lines values handcraftsmanship. We are developing an AI solution to support their philosophy. Initial change resistance gave way to worker enthusiasm when they understood how it would improve their manual tasks. This shift, championed by leadership, has positively impacted the workforce,” said Daniel Argüello, Vertical BD EBG Director, Hikvision.

Leonardo Vieira, Co-Founder and CEO Mexico, TRACTIAN, says that when implementing technology, leaders must identify whether it increases profits, reduces costs, or mitigates risks. If it achieves one of these three outcomes, the technology should be implemented. He notes that in an environment with tariff pressures and uncertainty, flexibility in technology adoption is important, but it is also essential to know what will truly contribute to the organization.

Meanwhile, supply chains are rapidly evolving with the integration of AI-driven automation. By 2030, AI is projected to generate US$3.3 trillion in annual economic value for manufacturing. Moreover, 95% of supply chain leaders plan to invest in predictive analytics to enhance resilience, and companies leveraging AI-driven risk management have reported a 40% reduction in supply chain disruptions, underscoring its importance in mitigating operational risks.

Julio Hernández, Director General and Country Manager, BAIC Trucks Mexico, notes that one of the main problems faced in the company’s operations is the illegal extraction of fuel. He notes that in this operational aspect, technology can also help identify when fuel levels in tanks drop drastically. “We had cameras inside the operator's cabin, which allowed us to generate data. Now, with the integration of AI, we can act on that data and pinpoint the specific situations in which these cases of extraction occurred,” he said.

Beyond automation, manufacturers are increasingly adopting real-time decision intelligence to boost efficiency. Research shows that implementing real-time data analytics can result in a 30% increase in productivity and a 50% reduction in downtime. By transitioning to predictive and autonomous decision-making, companies can proactively identify inefficiencies and bottlenecks, ensuring a more agile and responsive production environment.

However, increased connectivity comes with heightened cybersecurity risks. The manufacturing sector is the most targeted industry for cyber threats, with 50% of industrial cyberattacks aimed at this sector. The global cost of cybercrime is projected to reach US$10.5 trillion by 2025, prompting 70% of manufacturers to increase investments in cyber-physical security solutions. Integrating IT and operational technology (OT) security measures is critical to safeguarding digital assets and production continuity. “In the adoption of technology, it is crucial to inquire with the provider about their ISO 27001 certification, their SOC 2 compliance, the available integration tools, and whether their APIs are open. These factors are decisive in determining potential cybersecurity risks,” Vieira added.

By addressing these key challenges, cultural resistance, AI-driven automation, real-time intelligence, and cybersecurity, manufacturing leaders can establish a data activation framework that ensures long-term competitiveness and resilience. "It is important that companies set the goal of generating efficient production chains. The rapid development of AI is positive, and finding ways to apply it and help other smaller companies apply it is crucial. We must share knowledge," Argüello added.