影响下一代全球价值链的五大趋势 - 世界经济论坛
调查结果显示，全球价值链的重组速度慢于预期。地缘政治紧张、劳动力短缺、通货膨胀和网络风险等因素导致供应链中断更加频繁和严重。在此背景下，领先的 ...
64%
尽管 <anchor>64%</anchor> 的受访者认为 AI 是改进供应链的关键，但只有1%表示AI已经能够淘汰手动工作；文化惯性以及旧系统的规模和复杂性仍然是一大挑战。为了管理风险，几乎所有的运营高管都同意对其供应商上游（直至原材料）保持可见性。然而，在现实中，很少有企业大规模实现了完全的可见性。那些成功的公司利用AI筛选大量数据，并与相关的供应节点建立联系，从而实现了跨越式发展。面对不明朗的未来，所有供应链都必须实现端到端的可见性。但公司如何克服旧系统的挑战呢？
Here's how generative AI can transform industrial operations | World Economic Forum
# Beyond the status quo: How generative AI will transform industrial operations

Jun 23, 2023

A futuristic architect, Businessman, Engineer manager using tablet with icon network, Industrial robotics, Automation robot arms machine in intelligent construction site. Construction technology concept

Generative AI can help manufacturers unlock their full potential.Image: Getty Images/iStockphoto

##### Kyriakos Triantafyllidis

Head of Growth and Strategy, Centre for Advanced Manufacturing and Supply Chains,World Economic Forum

##### Daniel Kuepper

Managing Director & Senior Partner,BCG (Boston Consulting Group)

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#### Advanced Manufacturing and Supply Chains

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- Manufacturers are increasingly employing cutting-edge technologies powered by artificial intelligence to address challenges like supply chain disruption.
- Technological breakthroughs such as generative AI look set to enable industrial companies to open up even more of their potential.
- The World Economic Forum and partners, including BCG, invite manufacturers to join the AI-powered Industrial Operations to collectively accelerate the transformation towards AI-powered industrial operations.

Recent challenges such as supply disruptions, price volatility, talent shortages and the sustainability imperative, are increasing the complexity of industrial operations. To address these challenges and unlock the next wave of value, leading manufacturers are employing cutting-edge manufacturing technologies powered by artificial intelligence (AI).

These technologies present industrial companies with fresh avenues to navigate their way through turbulence and offer opportunities to substantially boost their operational performance.

At the same time, technological breakthroughs continue to emerge and recent developments, such as in generative AI, open up even more potential.

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What is AMNC, the World Economic Forum's meeting in China?

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The global economy is approaching a soft landing per the latest forecast from the International Monetary Fund (IMF), as growth recovers and headline inflation eases, and the rapid pace of innovation and development in technology and artificial intelligence pushes industries forward. Yet, risks and tensions remain, and the present juncture necessitates the buy-in of all stakeholders to ensure a transition into a period of sustained progress. Only with the right levels of cooperation can the next frontiers for growth be unlocked.

To respond to the fast-evolving global landscape, the World Economic Forum will convene the 15th Annual Meeting of the New Champions in Dalian, People’s Republic of China, on 25-27 June 2024. The event will gather over 1,500 high-level leaders from business, government, civil society and international organizations, as well as prominent entrepreneurs, innovators and academics to generate collective insights and deployable solutions.

Meeting in Asia, which continues to drive two-thirds of all global growth, will give leaders the opportunity to collaborate and foster ways to spur and maintain positive economic momentum.

For more information on the event, see here.

While some leading manufacturing companies have already successfully implemented a variety of AI applications, many others are only at the beginning of their AI journey.

To shed light on where manufacturers stand with AI today, Boston Consulting Group (BCG) analysed insights from almost 1,800 manufacturing executives worldwide in their 2023 study AI-Powered Industrial Operations.

For manufacturers just starting their AI journey, these insights offer a window into the potential impact of AI and the typical implementation challenges.

Here is what the results reveal:

## AI is penetrating industrial operations worldwide

Simply put, manufacturing executives are very optimistic about AI. A striking 89% of executives see AI as essential to their operations and plan to incorporate it into their production.

This commitment reflects a broader understanding of AI's promise – roughly two-thirds (64%) of executives perceive a high potential for AI applications to drive production efficiency improvements.

Beyond being a means for productivity, many executives also view AI as promoting substantial opportunities for sustainability (53%), production flexibility (52%), and workforce support (47%).

And this isn't just talk either – progress is already under way as 68% of executives have already fully implemented at least one AI use case.

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Given the wide array of AI applications within industrial operations, many executives are looking to understand what the most promising use cases and the most value-adding ones for their context are.

While there is no universal answer, applying AI in quality control – such as computer vision-based applications – is the most mature and relevant use case today.

One in four of the surveyed executives report using AI in their quality control processes in some way. But other AI use cases are gaining traction as well, such as robotics and production automation, production alert systems and inventory optimization. Each of these is used already by about one in five respondents.

Taking a look at different industries, electronics and technology equipment, with 83% AI adoption, leads the way by a significant margin, followed by energy at 72% and process industry at 68%.

Share of companies having fully implemented at least one AI use case in their production (today) or plan to (further) implement AI in the near future (ambition) across industries 

Share of companies having fully implemented at least one AI use case in their production (today) or plan to (further) implement AI in the near future (ambition) across industries. Image: BCG

## Scaling AI in production is a universal challenge

Early adopters have confirmed the potential of AI in the industrial context, realizing, on average, 14% savings on addressed manufacturing costs to date.

However, many companies struggle with successful AI implementation, especially when scaling AI within their production network. Only 16% of respondents have achieved their AI-related targets, and nearly all respondents (98%) cited scaling AI as particularly challenging.

The issues highlighted in this context can be grouped into two categories of enablers – organizational and technological.

- 92% of respondents stated that insufficient organizational foundations hinder the scaling of AI and obstruct them from achieving their AI-related goals. Within this category, a scarcity of digital skills and capabilities (39%) and the absence of an AI strategy and roadmap (33%) are the predominant challenges.
- 88% of respondents mentioned a deficient technology foundation as a significant impediment. Inadequate data processing and data visualization infrastructure are the top challenges, each cited by 34% of respondents.

Share of companies facing specific challenges for scaling AI through out their production network.

Share of companies facing specific challenges for scaling AI through out their production network. Image: BCG

## How generative AI transforms industrial operations

While industrial companies seek to overcome the obstacles to capturing AI’s full potential, the technology continues to evolve. Innovations, such as large language models and their application in the context of generative AI, have revealed new opportunities. How does this advanced technology promise to transform industrial operations?

Three main types of generative AI applications in the manufacturing environment:

Providing information support: In the industrial context, well-established generative AI models and tools operating like ChatGPT can be used to automatically generate text to support operations. Applications include, for example, supporting equipment maintenance by generating maintenance instructions for remote support or creating standard operating procedures.

Converting information to output: Generative AI applications able to convert text to code or images allow companies to accelerate manufacturing related processes for instance in process automation by creation of programme code based on text input.

Enhancing robotics : Generative AI in robotics holds the promise of enabling robots to automatically act on, for example, voice commands without the need for task-specific training and regular retraining. This facilitates new application areas for robotics in industrial operations, such as automated material or tool supply, which would allow companies to increase production efficiency while reducing engineering costs and ramp-up times.

##### Have you read?

Although most of these applications are in the early development phase and have yet to be widely implemented, leading manufacturing companies are seeking to understand how they can use generative AI in operations, what possibilities it might unlock and how to implement it.

However, as with the introduction of AI in general, it is imperative to overcome the organizational and technological challenges outlined above to benefit from these developments. Without a comprehensive implementation approach as well as solid organizational and technological foundations, companies will struggle to move beyond piloting use cases and to realize AI's full potential in industrial operations.

## A joint initiative to support manufacturers

To support manufacturers on their journey towards capturing the full potential of AI, the World Economic Forum in collaboration with BCG, Tuv Sud, and the Centre for the Fourth Industrial Revolution in Türkiye has launched the global initiative AI-powered Industrial Operations.

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How is the World Economic Forum contributing to build resilient supply chains?

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The Global Rewiring report highlighted that collective thinking on global value chains is changing due to increasing disruptions driven by geopolitical tension, climate change, and technological shifts.

The World Economic Forum’s Centre for Advanced Manufacturing and Supply Chains is at the forefront of future-proofing the global manufacturing industry. It supports sustainable growth by fostering innovation and accelerating the adoption of inclusive technology.

Learn more about our impact:

- The Global Lighthouse Network: We have brought together 132 manufacturing factories from various industries who are applying advanced technologies to boost productivity, enabling them to scale and replicate innovations.
- Circular value chains: We actively support manufacturers in incubating new pilots that reinforce trust in circular value chains, such as authenticating fashion products in second-hand markets and exchanging CO2 footprint data across supply chains.
- Resiliency: In partnership with Kearney, we developed the Resiliency Compass to help guide companies in navigating supply chain disruptions and enhancing their resilience.

Want to know more about our centre’s impact or get involved? Contact us.

The initiative seeks to raise awareness about the potential of future-oriented AI applications, co-develop with its community an educational guidebook on implementing and scaling AI in industrial operations, and deep dive into the importance of AI quality in ensuring successful sustainable outcomes. It is also incubating collaborative pilots on new AI applications.

The World Economic Forum invites manufacturing companies to join this initiative to collectively accelerate the transformation towards AI-powered industrial operations.

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The views expressed in this article are those of the author alone and not the World Economic Forum.

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