GuShiio.com Article source: Xin Zhiyuan
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As the wave of science and technology surges forward, artificial intelligence (AI) has been deeply integrated into all aspects of social economy from cutting-edge concepts and has become the core force in promoting industrial transformation and innovative development.
In this context, the World Economic Forum (WEF), in conjunction with Accenture and KPMG, released a report, which undoubtedly provides us with an authoritative perspective on the future development of AI.
This report brings together the wisdom of many parties. Through in-depth industry research, cutting-edge technical analysis and accurate grasp of global trends, it provides us with a comprehensive presentation of the opportunities and potential of AI in the future.
Whether they are practitioners who are concerned about technological innovation, financial people seeking investment directions, or the general public who care about social development, they can all draw inspiration from this report, make arrangements in advance, and meet the infinite possibilities of the AI era.
Report 1: AI in Action: Beyond Experiments to Transform Industry 2025
Artificial intelligence is developing at an unprecedented rate, especially in areas such as natural language processing (NLP), computer vision and generative artificial intelligence.
The report “AI in Action: Beyond Experiments to Transform Industry 2025”, co-authored by the World Economic Forum (WEF) and Accenture, explores AI’s opportunities, adoption status and future potential in 2025, aiming to provide organizations with a responsible and transformative AI adoption framework.
Report link: www.weforum.org/publications/industries-in-the-intelligent-age-white-paper-series/cross-industry/
The following are the core points of the report:
Opportunities for AI
- Efficiency and cost savings:Generative AI not only optimizes workflow and costs, but also significantly improves productivity. For example, a virtual engineer developed by a technology provider optimized building management through real-time data, reducing HVAC energy costs by 25% and reducing maintenance planning time by 90%
- Revenue growth:Companies that pioneered Ai already have 15% higher revenue than their peers, and are expected to double by 2026. Generative AI helps designers quickly generate diverse patterns through personalized design tools, which directly drives sales and revenue growth.
- Customer experience improvement:AI has transformed from a unique differentiation factor into a basic requirement for all companies to remain competitive. For example, the London Stock Exchange Group used AI-driven Question and Answer Service (QAS) to reduce the resolution time of customer inquiries by 50%.
AI adoption status
- Industry adoption:The telecommunications, financial services and consumer goods industries are leading the way in AI adoption. Generative AI is particularly prominent in industries that rely on human capital, such as healthcare, financial services, and media and entertainment.
- Function adopted:Marketing and sales, product and service development, service operations and risk management are the functions with the highest AI adoption rates. These functions often generate or digitize large amounts of structured and unstructured data, allowing AI models to be trained and scaled more effectively.
- Organization adopts:Despite the surge in AI investment and use, AI adoption is still in the early stages of most organizations. 74% of companies report challenges in adopting AI at scale, and only 16% are ready for comprehensive AI-driven reforms.
The future potential of AI
- Comprehensive automation of complex tasks:AI agents can work together to achieve comprehensive automation of complex and repetitive tasks, allowing humans to focus on more advanced tasks. For example, by 2028, industries such as manufacturing and financial services will see significant benefits from AI agents managing production lines, optimizing supply chain operations, and handling customer support.
- More situational and personalized decision-making:Integrating advanced reasoning capabilities into generative AI applications will make AI systems more effective in assisting humans in navigating complex environments and making context-aware decisions. For example, in the healthcare industry, AI will support personalized treatment options.
- Enhance personal efficiency and capabilities:AI-integrated handheld devices, advanced edge AI, and compact language models have the potential to revolutionize the way things work by automating tasks, managing schedules, and providing real-time information.
The foundation for successful AI implementation
- Ecosystem cooperation:Companies are increasingly working with cloud providers, AI technology companies, start-ups and public agencies to gain resources and expertise.
- Stakeholders ‘trust in AI:Trust is the key to AI success. 61% are hesitant about relying on AI systems, mainly due to concerns about data security and third-party participation.
- Industry self-governance:Organizations are creating self-governance frameworks to supplement regulations and ensure AI deployments are consistent with company values and regional regulations.
- Talent and Organization:Organizations need to prioritize employee development so that employees can respond to technological changes and lead AI-driven value creation.
- Cybersecurity:AI-driven cyberattacks such as deep counterfeiting, targeted phishing and data breaches are emerging threats. Organizations need to incorporate AI cyber risks into cross-organizational risk management.
- Digital core:Deploying a scalable AI strategy relies on building a strong digital core, including AI applications and digital platforms, data and AI “backbone”, and physical and digital infrastructure.
Report 2: Blueprint for Intelligent Economies
Artificial intelligence is driving the fourth industrial revolution, boosting economic growth and driving innovation in various industries and societies.
However, many countries may not be able to enjoy the economic and social benefits of the intelligent era due to a lack of energy-intensive AI infrastructure, advanced computing power, high-quality data and AI skills. Without intervention, technological innovation may not only fail to benefit the world equally, but may also aggravate the existing digital divide.
Report link: www.weforum.org/publications/blueprint-for-intelligent-economies/
Blueprint for Intelligent Economies, co-written by the World Economic Forum (WEF) and KPMG (KPMG), aims to create inclusive growth through a comprehensive collaborative approach.
The blueprint is divided into three interrelated levels:
- Build the foundation:This includes sustainable AI infrastructure, high-quality data sets, responsible AI models and effective capital investment channels.
- Developing a new smart economy:Reimagine core activities across industries by embedding intelligent applications, workflows, devices and robots.
- People-oriented:Enhance human potential through high-quality education, skills development and workforce training and establish moral, safety and safety guardrails.
The blueprint proposes three strategic goals:
- Building sustainable AI infrastructure
- Challenge:High energy consumption, large-scale investment needs, insecure AI supply chains, digital divide, high-cost Internet equipment.
- Success Cases:Microsoft signed a deal with the United States to buy carbon-free energy and reopen the Three Mile Island nuclear power plant to provide green energy to its data centers. The World Bank has launched a $10 billion renewable energy plan that aims to add 15 gigawatts of renewable energy capacity.
- Key competencies:Sustainable and responsible green energy, secure networks and resilient AI supply chains, high-speed connections, scalable and affordable computing power, AI-ready devices.
- Plan for diverse and high-quality data sets
- Challenge:Acquisition of high-quality data, data inequality, data ownership, progress in AI technology, trust in AI.
- Success Cases:Japan’s Fugaku LLM is a large open source language model, and at least 60% of its training data comes from Japan. The United Arab Emirates government has partnered with the G42 to develop the LLM “Jais” based on modern standard Arabic.
- Key competencies:Available and accessible data, diverse and inclusive data, data ownership and sharing, data protection and privacy, data lifecycle management.
- Establish ethical, safety and safety guardrails
- Challenge:Reduce bias, respond to the changing regulatory environment, ensure AI security, implement responsible AI practices, AI intellectual property and legal uncertainty.
- successful cases: The European Union’s Artificial Intelligence Act divides AI applications into risk levels and sets requirements for high-risk areas. The United States and the United Kingdom have collaborated through the AI Security Institute to develop a shared AI model testing framework.
- Key competencies:Ethical guardrails, responsible use guardrails, safety and safety standards, AI regulations, legal frameworks.
WEF
The World Economic Forum (WEF) is an international non-governmental organization headquartered in Davos, Switzerland. Because it was held for the first time in Davos, Switzerland, it is also known as the “Davos Forum”. The World Economic Forum is committed to promoting sustainable global economic, social and environmental development through public-private partnerships.
As the forum’s influence continues to expand and the level of participants increases, the World Economic Forum has been regarded as the “unofficial international economic summit.” It is the most important unofficial gathering place for world politicians, business people, and leaders of civil and social groups to discuss world economic issues. The corporate members participating in the forum include more than 1000 major companies and enterprises from more than 70 countries and regions around the world.
References:
https://www.weforum.org/publications/industries-in-the-intelligent-age-white-paper-series/cross-industry/
