Microsoft Asia and IDC Asia/Pacific today released findings specific to the manufacturing sector for the study, Future Ready Business: Assessing Asia Pacific’s Growth with AI.
The manufacturing sector, which contributes to a significant proportion of Asia Pacific’s GDP, continues to face rising competitive pressure due to growing costs and lower margins. Manufacturers are increasingly turning to emerging technologies to stay ahead of the competition. Those organizations that have started to adopt Artificial Intelligence (AI) believe it will nearly double their competitiveness (1.8 times) in the next three years.
“Manufacturers in Asia Pacific are slowly, but surely, seeing the importance of adopting a digital strategy and latest technologies. The Study found that 76% of manufacturing business leaders agree that AI is instrumental to their organization’s competitiveness in the next three years,” said Scott Hunter, Regional Business Lead, Manufacturing, Microsoft Asia. “To achieve supply chain excellence, and even develop new business models to address changing customers’ needs, integrating AI for their business is a must. Organizations which fail to adopt an AI-first strategy risk being left behind in today’s competitive market landscape.”
“However, 59% of manufacturers have not adopted AI as part of their business today. This is a worrying sign for the industry that needs to thrive on innovation,” added Hunter.
For manufacturers that have started their AI journeys, the top three business drivers to adopt AI include higher margins, higher competitiveness and business agility, as well as better customer relationships and outcomes.
They are already seeing business improvements in the range of 17% to 24% today, and further improvements are anticipated in three years by at least 1.7 times. The biggest jumps are expected in driving accelerate innovation (2.0 times), and higher margins (1.9 times).
One example is Piramal Glass, a leading glass packaging manufacturer in India, which has turned to AI, Internet of Things and advanced data analytics on the cloud to drive operational efficiency, enhance customer experience and generate new revenue models. Their in-house solution, RTMI, offers advanced insights in real-time that led to 5% reduction in defects, 40% reduction in manual data gathering and 25% improvement in employee productivity.
“The identified business drivers are a clear sign of how technology such as AI can create improved value by helping organizations gain insights, and better manage their operations in a highly complex environment,” said Stephanie Krishan, Research Director, IDC Manufacturing Insights. “In fact, according to IDC FutureScape for Manufacturing and Implications for Asia Pacific (excluding Japan), half of the top 10 predictions are driven by data and AI-centric solutions or use cases, such as creating new ecosystems for automation, or even to put data at the center of their processes to drive speed, agility and efficiencies. This only points towards the fact that the future of manufacturing will be built upon data in order to deliver scalable and accelerate growth for the industry.”
The Study also evaluated six dimensions contributing to the sector’s AI readiness. “The manufacturing sector is lagging behind in Culture, Data and Strategy, compared to Asia Pacific’s overall readiness. Business leaders must focus on those areas to stay competitive,” said Krishan.
1. Strategy: Manufacturers need to have an AI strategy in place, and support a more distributed workforce
“By adopting AI industry players will accelerate their transformation and enjoy higher benefits. To succeed in an increasingly digital environment, Manufacturers need to have an AI- strategy in place, including workforce transformation,” said Hunter. Close to half of business leaders polled see a shift towards a more distributed and flexible workforce due to AI in the next three years.
2. Data: Manufacturers need to work on availability, quality and governance of existing data
There is no surprise that manufacturers need to have a more robust data strategy in place in order to train task-based AI solutions. Today, manufacturers in the region are still dealing with a data structure where it can only be accessed by a centralized analytics team. The quality and timeliness of data are still major issues that are being addressed on an ad-hoc basis. There is also no extensive enterprise data governance program in place.
3. Culture: Traits required for AI adoption lacking in manufacturing organizations
More than half of the manufacturing workers, and nearly half of the business leaders polled believe that cultural traits and behaviors are not pervasive in their organization today. For example, 63% of workers and 57% of business leaders do not agree that employees are empowered to take risks, and act with speed and agility within the organization.
“Manufacturers in the region must work on better integration of AI into their existing operations, including how data is used and processed. They need to build an AI-ready workforce that is agile and empowered to innovate,” said Krishan. “Only when manufacturers nail down its strategy and skills capabilities they can fully harness the full power of AI for their organization.”
Dairy enterprise ACM’s newly opened high-tech milk processing and manufacturing facility in Victoria, Australia is leveraging state-of-the-art intelligent technology to better manage costs via a rich data approach. By introducing machine learning capabilities, ACM is able to reduce human errors from contaminating organic milk with conventional milk, which also minimizes wastage. In addition, by introducing automation for production planning, logging and quality assurance; as well as factory maintenance with the help of CRM and AI solutions, ACM has been able to rein in weekend overtime costs of AU$100,000 annually.
Skills for an AI-Ready Workforce
The good news is that majority of business leaders and workers in the sector believe that AI will have a positive impact on their jobs. 62% of business leaders and 77% of workers believing that AI will either help do their existing jobs better or reduce repetitive tasks.
However, according to business leaders, the skills required for an AI future are in shortage. Communication and negotiation skills, entrepreneurship and initiative-taking as well as adaptability and continuous learning are the top three skills identified in which demand will outstrip supply in the next three years. At the same time, business leaders believe that the demand for basic data processing, literacy & numeracy and general equipment operations and mechanical skills will decrease in three years. Those skills are broadly available today, and already now the supply is higher than the demand.
The disconnect comes with employers’ perception of their workers’ willingness to reskill. “Business leaders are aware of the massive reskilling efforts required to build an AI ready workforce. However, 22% of business leaders felt that workers have no interest to reskill, but only 8% of workers feel the same. In addition, 48% of business leaders feel that workers do not have enough time to reskill, but only 34% feel the same way,” shared Hunter. “Business leaders in this space must prioritize reskilling and upskilling, dedicating employee’s time for this to address skills shortage. Even as it may result in short term productivity impact as building an AI-ready workforce will result in greater gains in the future.”
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