ChinAI #80: A Peek at the Robotic Process Automation Landscape

"Testing the Waters" of Digital Transformation

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Feature Translation: China’s Position in the RPA Market

This week we’re taking a peek into the landscape of Robotic Process Automation (RPA) — a process that involves using software to automate repetitive, rule-based processes (e.g. entering data into a form and transferring it to a CRM). The article comes from Yiou Intelligence, a think tank/consulting shop that operates as a “innovation service platform” that connects entrepreneurs, hosts summits, and gets funding from VCs.

Key Takeaways:

  • The RPA market is small now but has great potential: RPA software revenues are the fastest growing part of the global enterprise software market, and the Asia-Pacific region’s expected growth rate in RPA of 181% in 2021 will be 3x the global rate. Plus, the integration of AI and RPA technology (think: using natural language processing to automate the writing of reports) will grow the AI market.

  • The Chinese market, specifically, has a lot of space to grow: Close to 50% of Chinese companies are bystanders amidst the overall drive toward digital transformation. Total spending on IT in China in 2018 was about 1/5 of that in the United States.

  • American firms dominate the RPA market: Yiou compiled an inventory of 40 firms competing in the global market — though there were a good number of Chinese companies on the list, the top 5 companies were all U.S. companies and they accounted for 47% of the global market (UiPath, Automation Anywhere, Blue Prism, NICE, and Pegasystems).

  • What will the diffusion pathways of automated systems look like? Many small and medium-sized enterprises may not want to make “earth-shaking changes” to their business processes and are highly sensitive to short-term returns. Thus, RPA may be “their first stop in ‘testing the waters’ of digital transformation.”

FULL TRANSLATION: Five US RPA companies have grabbed half of the global market, does China still have a chance?

ChinAI Links (Four to Forward)

Must-read: The Question of Comparative Advantage in AI

By CSET researchers Andrew Imbrie, Elsa B. Kania, and Lorand Laskai — a superbly well-researched and comprehensive effort to tackle the state of play in AI between the United States and China. I really liked the framework that separated core elements of AI capabilities, critical enablers of AI development, and systemic drivers of national competitiveness in science and technology.

Should-read: The Design and Implementation of XiaoIce, an Empathetic Social Chatbot

Microsoft researchers present the development of Microsoft XiaoIce, the most popular social chatbot in the world. Dives into the design of the entire chatbot system, some evaluation metrics, as well as ethical concerns. Really worth a read — if someone wants to do a more bite-sized summary of the paper, would be happy to feature it in a ChinAI issue.

Should-read: Translation of Qianzhan Chanye Report on China’s AI Industry

In a November issue of ChinAI, I highlighted a cool overview-style 50-page slide deck on China’s AI industry by Qianzhan and covered a few translated slides. The translation team at CSET has translated the full thing (link goes to CSET’s translation page where you can download the translated PPT).

Should-read: Douyin’s 2019 user trends report translated

Katherine Wu has translated Bytedance’s 2019 data report on user behaviors and trends on Douyin (Chinese counterpart to TikTok). Her analysis highlights some of the unique subcultures on the app. H/t to my fellow Iowan Joseph Nelson for sharing this with me - his Des-Moines based company (Roboflow) is doing some cool work on computer vision apps.

Thank you for reading and engaging.

These are Jeff Ding's (sometimes) weekly translations of Chinese-language musings on AI and related topics. Jeff is a PhD candidate in International Relations at the University of Oxford, Researcher at GovAI/Future of Humanity Institute, and non-resident Research Fellow at the Center for Security and Emerging Technology.

Check out the archive of all past issues here & please subscribe here to support ChinAI under a Guardian/Wikipedia-style tipping model (everyone gets the same content but those who can pay for a subscription will support access for all).

Any suggestions or feedback? Let me know at or on Twitter at @jjding99