Toronto, 27 May, 2019. Hammerkopf today released its CxO Survey focused on ‘AI in Manufacturing in Asia’. The study is a comprehensive, sweeping view of the C-Suite view on AI, and their perceptions around AI use cases in their specific industry sector.
Manufacturing companies as well as new age startups are at various stages of AI deployment, with an intent to increase business efficiencies, identify trends, and predict risks. Amongst those surveyed, 40% had an AI policy strategy and action framework formulated, while close to 60% had a mix of pilot AI projects, or AI solutions already in place.
The key takeaway is that while AI use cases are still experimental in the manufacturing sector, there is a clear recognition of the disruptive potential of AI, when combined with sensor data emanating from Industrial IoT (IIOT).
Commenting on the survey results, Namagiri Anand, Managing Partner, Hammerkopf, said, “In the age of disruption and creative chaos, manufacturers everywhere are under more pressure, than ever before, to out-innovate and out-grow. With the advent and growing maturity curve of Artificial Intelligence applications, enterprises are seeing positive outcomes, whether it be in reducing operational costs, enhancing productivity, or positively transforming customer experiences.”
When it comes to championing AI initiatives in manufacturing enterprises, CIOs take the lead. Of those surveyed, roughly 85% were CIOs, while around 15% were CEOs.
CxO Perspectives on AI
In terms of CxO outlook on AI, respondents were bullish about AI, and recognizing that its key for a future defined by Industry 4.0. In addition, there is a clear expectation that AI will contribute to supply chain efficiencies being realized, alongwith enhanced quality improvements, and reduction in machine downtime.
AI Use Cases
The key use cases that CxOs identify for AI in manufacturing include predictive analytics (55%), supply chain forecasting (50%), and demand forecasting (48%).
AI-related Challenges
For manufacturing companies everywhere, the upmost challenge is to identify the right AI vendor (66%), finding the right skill-sets, and talent (55%), and convincing the top management of RoI on AI related projects (45%).
“AI has the potential to positively impact the manufacturing industry, enabling key enterprises to operate at unprecedented speed and scale, while overcoming legacy challenges. Going forward, those deploying AI in manufacturing will need to develop and refine their capabilities across the value chain,” added Namagiri.
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About the Study
The AI in Manufacturing Study from Hammerkopf, covered 250 enterprises from across Asia, operating in the manufacturing industry, and including, among others, automotive OEMs, chemicals, consumer durables, plastics, food and beverages, and steel.