Outline
How AI and RPA Enhance Productivity
The Crisis and Opportunity Brought by Automation
Insights from KSCC
In this era of data-driven and rapidly evolving technology, Artificial Intelligence (AI) and Robotic Process Automation (RPA) have become indispensable elements of corporate strategic planning. Market analysis indicates that the AI industry, with a market size of nearly $100 billion in 2021, is projected to grow to nearly $2 trillion by 2030. This significant growth suggests that AI will play an increasingly important role in various areas such as supply chain management, marketing strategies, product manufacturing processes, research, and data analysis. For corporate executives, human resources, and information departments, starting to plan and adopt AI and RPA now is not only to maintain competitiveness but also to establish a competitive edge that is difficult to replicate.
1、How AI and RPA Enhance Productivity
When exploring the impact of AI and RPA on corporate productivity, it is essential to understand how these technologies affect labor efficiency and output. Research data indicates that from 2022 to 2040, companies adopting generative AI in the early stages will have a significantly higher Compound Annual Growth Rate (CAGR) than those adopting later, as AI can redirect labor time to more efficient purposes.
Particularly in the US market, the adoption of generative AI can double productivity growth. The same situation also occurs in Germany and France, where early adopters of AI technology see significantly higher productivity growth than those who lag behind. For businesses, this means that early investment and adaptation to AI technology can not only accelerate productivity growth but also maintain a competitive advantage in the long term.
In terms of data management, generative AI is expected to significantly improve data processing and collection efficiency by 2023, with an automation rate expected to exceed 90%. At the management level, the integration of AI will increase the potential for automation by more than three times. This demonstrates the tremendous potential of AI in improving operational efficiency for businesses.
2、The Crisis and Opportunity Brought by Automation
Facing the impact of automation, a double-edged phenomenon can be observed in administrative and legal fields. On the one hand, positions in these fields face a high risk of automation due to their process-driven and clearly defined work characteristics. On the other hand, positions requiring attention to rich details, such as machine installation, have a lower likelihood of automation due to their high degree of individualization and unpredictability. In the Eurozone, administrative support personnel are considered the most likely group to be automated due to the specificity and precision of their work.
In the US, the situation is similar to their counterparts across the Atlantic. Process-oriented jobs that are simple and easy to automate, such as office and administrative support, legal, and engineering fields, are the most likely to be automated. Conversely, positions like professional installation and building maintenance have a relatively lower likelihood of automation due to their uniqueness and complexity. Additionally, certain tasks within households, such as shopping and grocery purchasing, may reach a 15-25% automation level in the next five years. However, tasks related to childcare and upbringing are less likely to be automated due to psychological factors where people are less willing to accept machine involvement in early childhood life.
These changes present businesses with a dual challenge of internal technology and labor. Business leaders show both anticipation and caution in pursuing measurable value from new technologies. Nearly half of the respondents believe that transforming operational models to support new business visions is a significant challenge, which involves not only financial investment but also comprehensive adjustments to corporate culture, organizational structure, and process reengineering.
It is worth noting that over half of the respondents believe that retraining existing employees to adapt to new technologies is a significant challenge. This highlights the importance of talent re-education and skill updates for businesses in today’s increasingly prevalent automation and artificial intelligence era. As the labor market’s demands for skills evolve rapidly, businesses must provide platforms for continuous learning to ensure that employees’ skills remain up-to-date, thereby maintaining a competitive advantage in the fierce market competition.
Additionally, 49% of respondents believe that striking a balance between short-term cost reduction and long-term investment promotion is also a challenge in the business transformation process. This involves a delicate balance in corporate strategic planning—how to maintain financial health while investing sufficient resources to seize the growth opportunities brought by technology.
Regarding the relationship between corporate culture and innovation, 45% of respondents believe that company culture is not conducive to innovation. This indicates that businesses need to establish a more open and flexible work environment, encourage innovative thinking, and achieve widespread participation from management to grassroots employees. In adapting to geographical changes, 46% of respondents see it as a challenge, pointing out that in the tide of globalization, businesses must pay more attention to the flexibility of their market positioning and supply chain configuration.
3、Insights from KSCC：
In today’s data-driven environment, corporate interest in integrating AI and RPA is growing. The Leading Think Tank provides the following three-stage action plan, which helps corporate executives and relevant departments to realize this transformation:
Stage One: Formulating AI and RPA Integration Strategy
1.Identify Application Areas: By comprehensively analyzing corporate needs, determine the most suitable application areas for introducing AI and RPA.
2.Establish Integration Plan: Develop a clear integration plan with specific goals and timelines.
Stage Two: Enhancing Data Management and Operational Efficiency
1.Optimization of AI and RPA Applications: Introduce digital tools to optimize high-repetition processes such as data processing and collection, which will effectively improve efficiency and reduce human errors.
2.Management-Level Applications: Integrate AI technology at the management level to enhance decision-making speed and accuracy, optimizing processes and resource allocation.
Stage Three: Employee Retraining and Skill Updates
1.Assess Employee Needs: Regularly assess the skills of employees to determine areas that require retraining. Pay particular attention to skill enhancements in data analysis, RPA, and AI applications.
2.Develop Retraining Plan: Develop specific retraining plans and provide corresponding training resources and support. Through training, ensure that the team can smoothly adapt to changes in new technologies and workflows.
The above action plan helps corporate executives formulate strategies and execution plans for AI and RPA integration. In addition, detailed cost analysis, risk assessment, and technical support plans supplement information that enhances the comprehensiveness and effectiveness of decision-making, enabling businesses to smoothly realize data-driven transformation and meet future challenges.
KSCC is a management consulting company in Taiwan. Our services include corporate in-house training, consulting, and leadership management.For more information about our corporate services, please feel free to visit our website: https://kscthinktank.com.tw/custom-training/