The image is AI-generated
▎Enabling every capillary and every end of the enterprise to achieve digitalization is the core value of All in One.
Is the large model a dimensionality reduction attack on low-code? Initially, some people thought so.
If low-code is simply understood as simplifying software development, the large model is obviously a higher-level intelligence. Interacting with the large model using natural language allows applications to be realized instantly. On one hand, low-code vendors quickly shouted slogans to embrace large models, fearing missing the next industry trend; on the other hand, low-code practitioners wondered whether large models would eliminate the low-code industry.
The ice and fire brought by large models are both present in the low-code industry. However, some vendors have exhibited more calm and rational thinking, with leading low-code vendor Aozhe being one of them. Aozhe’s founder and CEO, Xu Pingjun, believes that “in the face of AI frenzy, we must think calmly and focus more on value.”
As the industry evolved as Xu Pingjun anticipated, changes occurred quickly. Similar to the implementation of large models in other fields, enterprises with higher levels of digitalization find it easier to effectively integrate large models.
So is there a way to combine low-code and large models, allowing enterprises to not worry about missing out on comprehensive digitalization while also not feeling helpless when AI truly enters core business scenarios?
This is the background for Aozhe’s “Business Digital Native 2.0” and the proposed “All in One” concept that effectively merges low-code and no-code.
How should enterprises evaluate AI’s impact on digitalization? How should they implement business-led digital natives? How can low-code and no-code truly integrate? With these questions in mind, Titanium Media had an exclusive conversation with Xu Pingjun.
Titanium Media has summarized some key points from Xu Pingjun’s insights during the interview for your reference:
1. Low-code is gradually becoming the main character in enterprise digital transformation, stepping into the C position. We observe that many emerging economy digital native enterprises use low-code to support their continuous development, and many traditional enterprises achieve comprehensive digital transformation through low-code. Through low-code, they have achieved synchronized support for business and digitalization, realizing business digital natives.
2. The impact of AI on digitalization is dual-sided, with both positive and negative aspects. On one hand, AIGC capabilities have been significantly enhanced, expanding new digital scenarios for many businesses; on the other hand, AI has somewhat slowed the development of enterprise digitalization.
3. In the information age, enterprises that excel in information technology have solid management foundations; in the digital age, enterprises that transform quickly are those with good information technology. Currently, AI is still developing, so in the future, enterprises that effectively utilize AI will likely be those with high levels of digitalization.
4. The current trend in digitalization shows that the dominance of business personnel is becoming increasingly evident. Enterprises need not be limited to a single no-code or low-code platform, but rather a combination of both, simultaneously meeting the needs of business personnel and IT personnel. This reflects the new demand for digitalization, or low-code products, from enterprises.
5. We believe that the most optimized solution for digitalization should effectively integrate low-code and no-code, which is the “All in One” concept we advocate.
6. “Business Digital Native 2.0” means that under the condition where the core business processes of the enterprise have been digitized, it can achieve comprehensive digitalization across all personnel and dimensions. Enabling every capillary and every end of the enterprise to achieve digitalization is the core value of All in One.
7. We hope to see core business perfectly integrated with IT departments and business departments, while non-core business can be led by business departments, achieving self-development and self-evolution, resulting in comprehensive digital transformation.
8. Currently, AI has not yet had a substantial impact on enterprise digitalization, but I firmly believe that AI will be a key force driving digital growth in the future.
The following is the content of the conversation between Titanium Media and Xu Pingjun (edited):
Titanium Media: Can you provide us with a panoramic view of the current state of low-code development?
Xu Pingjun: The past few years can be described as a magnificent and thriving period for the low-code industry. Especially in the three years before AIGC gained popularity, from 2021 to 2023, a large number of vendors entered the market, almost including all software, SaaS, and cloud vendors; the capital market invested fully, and customers began to use it widely. Of course, despite AI attracting some attention in the past two years, customer enthusiasm for exploring and practicing low-code continues to rise, indicating a very vibrant situation.
Additionally, low-code itself has evolved from concept to attempts at peripheral applications, gradually moving to departmental applications and now many core applications of enterprises, making low-code the main character in enterprise digital transformation, stepping into the C position. We observe that many emerging economy digital native enterprises use low-code to support their continuous development, and many traditional enterprises achieve comprehensive digital transformation through low-code. Through low-code, they have achieved synchronized support for business and digitalization, realizing business digital natives.
(Editor’s note: “Business Digital Native” was first proposed by Xu Pingjun in 2020, pointing out that the essence of low-code is to greatly shorten the distance between business and digitalization. Its core lies in the seamless integration of business modeling and development processes, enabling close collaboration between business backbones and developers, effectively reducing communication costs and errors. This model allows enterprises to develop and iterate their management systems more quickly and efficiently, ultimately achieving deep integration of business and digitalization with zero distance.)
Titanium Media: From your perspective, what changes and impacts has AI technology brought to enterprises in the fields of digitalization and low-code?
Xu Pingjun: Regarding this issue, my view may seem somewhat radical; the impact of AI on digitalization is dual-sided, with both positive and negative aspects.
On one hand, AIGC capabilities have been significantly enhanced, expanding new digital scenarios for many businesses, such as the widespread application of intelligent verification and intelligent analysis, which indeed reflects positive value, and the value continues to develop and deepen. However, the current application of AI is still limited to specific scenarios and ranges, similar to the capabilities of the previous generation of AI technologies like OCR and facial recognition. In the short term, it will become a specialized plugin to solve specific problems and be integrated into digital systems. In terms of overall enterprise digital transformation, it has not yet brought substantial breakthroughs or changes.
On the other hand, AI has somewhat slowed the development of enterprise digitalization. Due to the infinite possibilities exhibited by AGI, expectations for AI’s future are extremely high, which in turn leads to reduced attention and investment in technologies and products that are currently more helpful in enhancing digital capabilities.
The same applies to the low-code field; we are also using AI to assist in improving efficiency and lowering the usage threshold, achieving significant breakthroughs. However, this is just the beginning. The current changes to the core, form, and value output of low-code products are still not significant, and continuous exploration is needed.
In the information age, enterprises that excel in information technology are those with solid management foundations; in the digital age, enterprises that transform quickly are those with good information technology. Currently, AI is still on its way, so in the future, enterprises that effectively utilize AI will likely be those with high levels of digitalization. Therefore, I suggest that while exploring AI, everyone should fully leverage the excellent technologies accumulated over the past few years, not just low-code, but also RPA, BI, and others.
Titanium Media: You mentioned that many customers are currently in a wait-and-see stage. What key areas do you think enterprises should focus on in their digitalization efforts? Could you provide some suggestions?
Xu Pingjun: Over the past few years, low-code has become a core method for countless SMEs and large enterprises in their digital transformation.
For some enterprises with weak digital foundations, digital transformation must follow a priority order rather than being achieved overnight. I recommend focusing first on realizing core and important business processes. For example, the LTC process that enterprises often focus on, from how a Lead turns into Cash. If this process achieves comprehensive digitalization, with precise insights into data at every stage, it undoubtedly represents a successful digital transformation, which is precisely what low-code platforms can achieve in the business digital native phase.
Additionally, I see a major trend: full personnel digitalization. In our practices with clients, especially for medium to large enterprises with high digital maturity, digital awareness has deeply rooted in every department and even individual. Each department and individual desires to enhance their capabilities through digital means. Currently, digital transformation has entered a deep water zone. The competition among enterprises has shifted from a singular focus on data, technology, or talent to a competition of overall capabilities. Therefore, the development of enterprise digitalization requires the synergy of data, technology, and talent, which will become the key to achieving high growth for enterprises.
Titanium Media: From your observations, what new trends or developments should we pay attention to in the low-code field?
Xu Pingjun: The full personnel digitalization I just mentioned currently has only one solution, which is low-code + no-code. Using low-code to achieve business digital natives, and then using no-code to achieve comprehensive digitalization. Although currently, very few enterprises are using both low-code and no-code simultaneously, there are indeed some enterprises beginning to try; however, we see that the results are not very ideal.
On one hand, there are often gaps or overlaps in capabilities between no-code and low-code platforms, making some applications difficult to implement or complicating platform selection. On the other hand, applications developed by different products cannot achieve smooth transitions. Many of our enterprise’s businesses develop gradually, from simple to complex, from peripheral to core, and the inability to smoothly upgrade is a significant support issue at critical stages of business development.
Other issues also have a significant impact, such as the lack of data connectivity between no-code and low-code. We find that business personnel often need to re-model and re-enter data that already exists in other enterprise systems when building departmental systems, leading to a significant workload and increased difficulty in promotion.
Today’s digitalization trend shows that the dominance of business personnel is becoming increasingly evident. Enterprises need not be limited to a single no-code or low-code platform, but rather a combination of both, simultaneously meeting the needs of business personnel and IT personnel. This also reflects the new demand for digitalization, or low-code products, from enterprises.
Titanium Media: In response to current market demands and technological trends, what specific actions and strategies has Aozhe taken?
Xu Pingjun: In simple terms, we are launching integrated low-code and no-code products. Low-code helps enterprises build flexible and scalable application systems to meet various business needs. No-code further lowers the technical threshold, allowing more business personnel to participate in application development, achieving deep integration of business and IT. At the same time, after introducing AI technology, the system becomes more intelligent, helping staff make wiser decisions through data analysis, prediction, and optimization.
We believe that the most optimized solution for digitalization should effectively integrate low-code and no-code, which is the “All in One” concept we advocate. Based on this concept, we officially launched a new generation of low-code products at the end of March.
Titanium Media: What aspects does the “All in One” concept primarily reflect?
Xu Pingjun: It mainly reflects four “All in One” features:
The first is All in One for different groups.
This is not limited to the core development team, but refers to everyone. Whether you are a professional developer, ITBP, or a business person, you can participate in the digitalization process. Participants can implement your management ideas and business concepts through a unified platform, achieving collaboration among all.
The second is All in One for different applications.
Whether it is simple personal needs or complex needs at the departmental or company level, it can be realized on a unified platform. The demand for digital application development in enterprises often presents a layered progressive pattern. From L1 to L4, there are four layers of demand, categorized by complexity. Relatively simple L1-L2 level needs can be configured using no-code platforms, while more complex L3-L4 level needs typically require low-code for expansion.
The third is All in One for data.
The low-code platform will act as the hub of the enterprise’s “data open ecosystem,” linking new and old systems, on-premise and cloud data, third-party platform plugins, etc., to meet the diversified needs of enterprises in data management and integration.
Finally, there is All in One for new technologies that we have been discussing.
We have been talking about new technologies, including AI technology. In many new scenarios, it is necessary to combine with AI to achieve AI-native applications.
I believe that with these four All in One features, this product can help enterprises take a significant step forward in digitalization. We refer to this form of enterprise digitalization as “Business Digital Native 2.0,” which means that under the condition where the core business processes of the enterprise have been digitized, it can achieve comprehensive digitalization across all personnel and dimensions. Enabling every capillary and every end of the enterprise to achieve digitalization is the core value of All in One.
Titanium Media: You previously mentioned that AI has not had a substantial impact on current enterprise digitalization. Does this mean you hold a pessimistic view of AI’s future?
Xu Pingjun: Not at all. What I mentioned earlier is that AI has not yet had a substantial impact on enterprise digitalization, but I firmly believe that AI will be a key force driving digital growth in the future.
Last year, we also published many views on AI’s future, including several stages of the integration of low-code and AI, which will gradually evolve from Copilot to Pilot to Agent, representing a more automated development model. This judgment has not changed, as today’s AI ultimately integrates into digitalization in three forms:
First, it becomes a specific scenario plugin integrated into digital systems.
Second, it becomes an important module of enterprise systems, occupying about 30% of enterprise digitalization with AI-native application scenarios generated by neural networks, such as IM tools, iPaaS integration, and BI analysis.
Third, applications primarily based on Agent interaction models will occupy 70% of application entrances, undertaking major interactions and application generation intelligence.
We have conducted research on these three stages, and the first two stages have already been implemented in products. In the future, reaching the third form, with low-code integrated with AI, all applications will be generated in real-time according to scenarios, with all application needs generated instantly based on neural networks, completing data model construction, rules, chart analysis, knowledge invocation, etc., on demand. This form can be understood as business digital native 3.0, which we envision and research.
Titanium Media: What strategies has Aozhe already adopted in the field of AI?
Xu Pingjun: For us, the core is still two things.
First, continuous upgrading and improvement of products and technology. Especially in integrating AI products, we mainly address the following needs:
First, at the product level, we adopt design-based configuration Copilot to improve efficiency throughout the application development lifecycle, benefiting both business personnel and professional developers. At the same time, we have integrated AI-assisted development capabilities into the integrated development environment (IDE).
Second, we provide AI-native application development capabilities for edge fragmented scenarios. Clients can configure simple AI assistants to handle various scenario needs, such as contract review, text summarization, work order analysis, customer service knowledge, etc., continuously enhancing the convenience and efficiency of business processing.
Finally, we are advancing the integration of AI capabilities in low-code applications. By integrating AIGC plugins into existing business processes, applications can seamlessly acquire AI invocation capabilities and collaborate with AI-native applications.
Second, embracing AI across the organization and culture.
Within our company, there is not only an expert team on AI, but the entire team utilizes AI. From product design to development, service, and even management and marketing, we actively leverage AI technology. Every product manager is required to master product design concepts empowered by AI; every programmer is encouraged to utilize AI technology to assist programming when feasible; our delivery team analyzes customer industries and assists in drafting business blueprints using AI. By deeply understanding and applying AI across the board, we can better integrate our products and services with AI technology.
Through these two strategies, I believe Aozhe can achieve stable and effective development in the future.
Titanium Media: In the latest IDC “2023 Half-Year Tracking Report on the Low-Code and No-Code Software Market in China,” Aozhe has maintained its position as the leading independent low-code vendor, achieving outstanding results against the trend. What is the secret behind this? What specific key measures or strategies are in place?
Xu Pingjun: Last year, our development was indeed impressive, which can be attributed to two core factors.
First, adhering to the essence of low-code products. The core value of low-code is to lower thresholds and enhance efficiency, and the improvement of efficiency refers not only to pure development efficiency; it also involves the entire process from business conception to system implementation, spanning the entire application lifecycle, which is the essence of low-code.
Over the past two years, at the product development level, we have continuously optimized and improved product efficiency based on actual customer feedback through regular surveys and data analysis, thus avoiding the pitfall of closed-door development.
Likewise, as enterprises have gradually embraced low-code over the past few years, we have gained and accumulated a large number of clients. The concepts we previously proposed have been put into practice and successfully verified over time. We have refined practical applications that have proven effective to better align with the essence of the product, which is the first step we got right.
Second, Aozhe’s low-code implementation methodology. Even if we are selling a set of low-code products, we must ensure that customers are aware of the free online training materials we provide.
Why do we do this? We recognize that customers have vastly different understandings of low-code; some mistakenly believe that low-code is equivalent to no-code, while others think low-code is merely a development tool, with usage varying widely.
But how can we truly showcase the value of low-code? We need a clear methodology as guidance. Therefore, over the past two years, we have deeply researched a series of methodologies, exploring what products can be effectively utilized by enterprises to maximize their value.
We believe that the construction of low-code methodologies must center around the essence of business digital natives, focusing on business-driven digitalization, while promoting collaboration between business and IT on the same platform to achieve rapid implementation. To this end, we have developed a systematic strategy that includes delivery concepts and guidelines to help enterprises build a platform, a system, and a team. Currently, this methodology has received positive responses and high recognition from clients.
In addition, our products have reached a high level of maturity and have been widely recognized by clients. In the past, selling low-code meant selling a project. However, since last year, we have observed that many clients prefer to purchase a combination of products and services rather than a single service project.
Previously, each project might require three to five personnel for delivery; now, we prefer to provide clients with a comprehensive training solution to meet their full personnel digitalization needs.
Titanium Media: What new measures and developments can we expect from Aozhe in the near future?
Xu Pingjun: As I mentioned earlier, Aozhe will focus on helping more enterprises achieve process digitalization and business digitalization through low-code. This is our current primary focus—enabling more enterprises to realize business digital natives.
At the same time, we actively promote the “All in One” strategy, aiming to help more enterprises leap into the digital native 2.0 stage. We hope to see core business perfectly integrated with IT and business departments, while non-core business can be led by business departments, achieving self-development and self-evolution for comprehensive digital transformation.
Moreover, Aozhe will continue to delve into AI technology, hoping to leverage AI to help enterprises embrace the arrival of the business digital native 3.0 era.
In summary, future measures and developments will revolve around helping enterprises achieve digital transformation, and we will continue to explore and innovate to achieve this goal.
Source: Titanium Media
Editor: WeChat Editorial Department of Foshan Information Association
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