The global(RPA) market has grown by leaps and bounds in recent years. In China, the market is still nascent but has drawn a lot of attention since 2019, as existing and new vendors have started offering more AI capabilities. Big technology vendors, as well as startups, are increasing their R&D investments, as well as the capability of their sales and delivery teams.
We spoke to key vendors and their clients in the market and here are some key observations of the RPA market in China:
- Customers experiment their way to RPA success. Clients are experimenting with RPA tools, new features provided by vendors, and the best ways to cooperate with service providers and service teams from software vendors. The wide range of vendors gives clients more options. Some are cooperating with more than two vendors, accelerating their pilot stages.
- RPA success requires a robust operating model. In China, most clients quickly started their RPA programs in silos, each business unit running different pilots and proofs of concept. Each team established basic operating models during the actual implementations, resulting in many automation islands across the firm. To effectively manage RPA programs, enterprises need to take a step back and create enterprise-wide governance structures.
- AI is driving RPA to intelligent automation. Interestingly, RPA emerged in China after the AI craze driven by digital giants and other highly visible startups. Many clients can leverage AI capabilities from day one. RPA and practical AI components create the intelligent automation that has been adopted by over half of surveyed clients.
In spite of the many challenges, Forrester expects that Chinese organizations will increasingly consider RPA to support a rising number of automation initiatives. However, adopting new technology is always challenging and CIOs in China need to understand the current RPA trends in China, adoption drivers and common challenges, and AI’s potential role in their automation efforts in order to formulate a strategy to get them started.
This post was written by Analyst Guannan Lu, and it originally appeared here.
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