APAC factories double down on smart tech to survive 2026

As Asia Pacific manufacturers grapple with economic uncertainty, supply chain volatility, and workforce challenges, Rockwell Automation's 10th Annual State of Smart Manufacturing Report reveals a surge in AI adoption, with 94% planning to invest in AI/ML over the next 5 years.

Key priorities include quality control (47%), cybersecurity (44%), and process optimisation (43%), while 55% pursue sustainability for efficiency.

Complementing these insights, IBM's APAC AI Outlook 2026 report emphasises AI as a revenue driver, with organisations directing 64% of AI spending toward core functions and 95% of global executives expecting generative AI projects to be self-funded by 2026.

For COOs and heads of manufacturing, the path to 2026 demands strategic integration of these technologies, balancing innovation with human expertise.

Leveraging AI for quality control and process optimisation

In high-volume sectors such as electronics and semiconductors—hallmarks of Asia's precision manufacturing—AI emerges as a game-changer for maintaining consistency and minimising defects.

Marcelo Tarkieltaub, regional director for Southeast Asia at Rockwell Automation, emphasises, "AI is transforming precision manufacturing by turning data into a competitive advantage. Across Asia, manufacturers are embedding AI to enhance quality, consistency and predictive decision-making."

He points to practical tools like FactoryTalk Analytics VisionAI, which enables real-time defect detection on production lines, such as identifying dents in canning operations to trigger early maintenance.

"The key lies in combining AI with human expertise. Rather than replacing skilled technicians, AI augments them. Simplifying decisions, improving yield and enabling teams to focus on higher-value innovation." Marcelo Tarkieltaub

Aligning with this, IBM Consulting APAC's Asia-Pacific leader for strategic engagements, Arun Biswas, notes that leading firms will "embed AI into design, engineering, operations, and supply chains—enabled by modern cloud, integrated data, and strong cybersecurity. This moves AI beyond incremental efficiency gains toward structural advantage through predictive maintenance, digital twins, computer vision, and self-optimising operations."

To implement, audit current data sources—38% globally plan to use existing data for quality monitoring—and invest in AI-driven systems with robust governance. This approach not only reduces rework costs but also enhances product reliability, which is crucial for a competitive edge in precision-driven markets.

Building resilient supply chains amid volatility

Ongoing trade uncertainties, reshoring trends, and geopolitical tensions demand intelligent supply chain strategies. The Rockwell report notes that external pressures like inflation and slow growth are the top obstacles for 34% of respondents, prompting a turn to AI for predictive analytics.

Tarkieltaub advises, "Resilience in today's supply chains is no longer about redundancy, it's about intelligence. Manufacturers across Asia are using AI to connect insights from the plant floor to the boardroom, anticipating risks and making faster, data-driven decisions."

He highlights how predictive analytics and machine learning applied to production and logistics data can forecast shortages and rebalance resources. "Equally important is the human factor. As automation expands, manufacturers are upskilling teams to interpret AI insights and coordinate cross-functional decisions. AI is not replacing supply-chain expertise, it's amplifying it."

Biswas reinforces this by advocating for "scaling AI into the digital core and across the value chain," including supply chains, to enable predictive capabilities.

Supporting these views, Raju Chellam, chair, cloud & data standards, IT Standards Committee, Singapore, states, "AI can be deployed for supply chain mapping and visibility, predictive analytics, and real-time risk monitoring. Supply chain disruptions occur every 3.7 years on average, costing companies nearly 45% of a year's profits over a decade, according to a report by Supply Chain Management Review."

He suggests companies focus on three key areas: "Use AI tools to map multi-tier supply chains by processing disparate data from orders, customs declarations and freight bookings. Implement digital twin technology and IoT sensors for end-to-end visibility. Combine AI with scenario planning to anticipate disruptions."

Referencing an article on SupplyChain247, Chellam also warns of "a shortfall of 2 million supply chain professionals by 2030," underscoring automation's criticality.

COOs should prioritise cloud-based systems—among the highest global investments—to integrate AI for real-time visibility. By adopting these strategies, manufacturers can mitigate risks from volatile global trade, ensuring smoother operations and reduced downtime through proactive, data-informed adjustments.

Addressing labour shortages and skills gaps

Asia's diverse demographics, from ageing populations in Japan and South Korea to burgeoning markets like India, exacerbate labour shortages and skills gaps. The Rockwell report reveals that 46% of APAC businesses believe AI/ML will help address workforce shortages, while 42% are introducing technology to create more engaging jobs.

Globally, 41% are combining AI/ML with automation to fill these gaps, and 83% prioritise analytical thinking and communication in recruitment.

Tarkieltaub notes, "AI and automation are helping manufacturers across Southeast Asia address workforce challenges by empowering them to work smarter and safer. In markets facing talent shortages and rapid industrialisation, this balance between technology and talent is critical."

He adds, "AI is acting as a talent multiplier, automating repetitive, data-heavy tasks so workers can focus on higher-value roles like problem-solving and optimisation. Technologies like digital twins, AR/VR-enabled training and low-code platforms are also closing the skills gap by making complex systems more intuitive and boosting digital confidence."

Biswas echoes the need to "evolve the workforce around human–AI collaboration. Sustainable adoption depends on reskilling and change management, with roles shifting toward higher-value activities such as problem-solving, supervision, and decision support. Manufacturers that invest early in AI literacy and cross-functional skills will scale faster and face less resistance."

Complementing this, Chellam recommends focusing "on strategic robot deployment and AI-assisted workforce augmentation as some countries are already doing. The World Robotics 2024 report says Singapore has 730-770 industrial robots per 10,000 employees and is ranked second globally in robot use. Japan is likely to face a shortage of 1.5 million workers by 2030, even with automation and expanded labour-force participation."

He suggests deploying AI in three phases: "One, automate repetitive manufacturing tasks first. Two, implement predictive systems for workforce planning. Three, develop comprehensive upskilling programs focusing on AI collaboration skills."

Strategies include reskilling programmes and low-code tools to democratise access to technology, fostering a more engaged workforce. This phased approach can help bridge gaps in ageing societies, turning potential shortages into opportunities for innovation and productivity gains.

Integrating AI into cybersecurity defences

As digitisation intensifies, cybersecurity ranks as the second-largest external risk globally, rising in priority. Per the Rockwell Automation report, 95% in APAC deem cybersecurity practices moderately to extremely important, yet 28% cite leadership underestimation as a challenge. Forty-four per cent of APAC manufacturers see cybersecurity as a key AI use case.

Tarkieltaub warns, "As manufacturers connect more systems across IT and OT environments, the attack surface has expanded dramatically. AI is becoming essential to build cyber resilience into the DNA of operations."

He explains AI's dual role: "AI-driven monitoring tools can analyse network traffic, detect anomalies, and respond automatically before disruptions occur. Predictive algorithms identify unusual patterns in machine behaviour or access activity, allowing companies to contain risks before they escalate into downtime."

However, "technology alone isn't enough. Cybersecurity must go hand in hand with workforce readiness. Simulation-based training and real-time threat visualisation empower employees to act as the first line of defence. True cyber resilience depends on people as much as platforms."

Biswas stresses to "integrate cybersecurity and AI governance from day one. As AI becomes business-critical, governance-first approaches—covering data integrity, identity management, model oversight, and auditability—are essential to manage risk and prevent 'shadow AI.'

Increasingly, this also requires investment in sovereign digital capabilities, including trusted cloud, data residency, and compliant AI infrastructure that meet national security and regulatory requirements across Asia."

Adding to this, Chellam suggests "implementing layered AI-powered defence with mandatory workforce upskilling. AI-driven cyberattacks likely surpassed 28 million incidents globally in 2025, up 72% over 2024. Manufacturing experienced 50% of all reported ransomware attacks in 2024, with industrial organisations seeing an 87% rise in ransomware attacks, according to an industry report."

"Deploy AI for real-time threat detection and anomaly identification. Implement zero-trust architecture with AI behavioural analytics. Make cybersecurity training mandatory for all staff, suppliers and channel partners." Raju Chellam

Fortify defences by integrating AI into IT/OT architecture—over a third globally plan to do so for positive outcomes—and conduct regular training to bridge awareness gaps. This comprehensive defence can protect dense networks from escalating threats, ensuring operational continuity.

Comprehensive approaches for resilience and sustainable growth

Sustainability is no longer optional; 55% of APAC manufacturers pursue it primarily for operational efficiency, a 16% increase from last year. Globally, 43% prioritise product quality/safety in sustainability programmes, aligning with AI-driven improvements. The IBM report highlights AI's role in tracking emissions and optimising resources in manufacturing.

Addressing the question of comprehensive approaches combining AI adoption, workforce evolution, cybersecurity, and sustainability for long-term resilience by 2027, Tarkieltaub envisions, "Sustained competitiveness will depend on how effectively manufacturers can connect technology, people and purpose. It is about building intelligent, adaptive and responsible operations that can thrive in uncertainty. Across Asia, AI is being embedded into core production and supply-chain systems, turning data into real-time insights for quality, energy and asset performance."

He adds, "Our report shows that 55% of manufacturers now pursue sustainability primarily to improve efficiency - reduce emissions, minimise waste, and lower operating costs."

Biswas, drawing from the IBM report, states, "Asian manufacturers can secure long-term competitiveness by treating AI as a whole-of-enterprise transformation rather than a set of isolated pilots. To succeed, they must make four key shifts."

These include scaling AI across the value chain, evolving the workforce for collaboration, integrating cybersecurity and governance early, and embedding sustainability into operations.

"Finally, embed sustainability into operations and ecosystems. AI can optimise energy use, reduce waste, improve monitoring, and extend sustainability standards across supplier networks—turning sustainability into a performance and growth lever." Arun Biswas

He concludes, "Together, an AI-ready core, empowered workforce, security-by-design governance, and sustainability-led innovation will define resilient Asian manufacturers through 2027."

Chellam advocates "integrating four pillars simultaneously: AI-driven operations, workforce transformation, cyber-resilience, and sustainability metrics. By 2027, 60% of manufacturers will leverage hyperscaler ecosystems to build, deploy, and scale new AI solutions, notes IDC."

His suggested approaches include: "Embed AI across the value chain. Microsoft says AI adoption in China reached 75% in 2024, with 70% of organisations expecting Agentic AI to disrupt business models within 18 months. Prioritise sustainability integration. Science Direct reports that Chinese manufacturers using AI achieved efficiency increases of 8% and fuel reductions of 10%. Develop collaborative ecosystems such as Singapore's AI Verify Governance Toolkit."

Adopt AI for energy optimisation and waste reduction, combining with cybersecurity for secure innovation. By weaving these pillars together, manufacturers can achieve holistic resilience, driving sustainable growth amid evolving challenges.

The evolving role of humans in a digital-first workforce

Smart manufacturing amplifies human potential rather than diminishing it. The Rockwell report shows smart transformations require more skilled people, not fewer, with organisations planning to hire and retrain.

Tarkieltaub describes, "AI is reshaping the relationship between people and production. It gives workers better insights, faster decision-making tools and safer, more meaningful work. On the factory floor, AI takes over repetitive, data-intensive tasks such as inspection, scheduling or process adjustments, allowing workers to focus on strategic functions like optimisation, innovation and maintenance, where human judgment and creativity remain irreplaceable."

In APAC, "a 'digital-first' workforce blends technical fluency with adaptability. Workers are increasingly expected to interact with smart systems, interpret data dashboards and collaborate with connected technologies. Tools like digital twins, AR-based maintenance training, and low-code automation are making this transition easier, even for non-technical teams."

This evolution underscores the need for ongoing investment in human capital, ensuring technology serves as an enabler rather than a replacement.

As Asia's manufacturers gear up for 2026, the synergy of AI, human ingenuity, and strategic investments is unmistakable, as posited by associate professor (Dr) Sheeba Armoogum (PhD in cybersecurity), University of Mauritius & professor (Dr) Vinaye Armoogum (networks and telecommunications), University of Technology, Mauritius. By heeding these comprehensive approaches, COOs can navigate uncertainty and bolster resilience and sustainable growth.