"Super artificial intelligence will arrive within 'a few thousand days.'"

Recently, Sam Altman, CEO of OpenAI, rarely published a long article on social media, predicting this. Previously, many experts predicted that super artificial intelligence would arrive within five years, and Altman's expectation may make this number more optimistic.

Super artificial intelligence, namely Artificial Super Intelligence (ASI), refers to artificial intelligence with a level of wisdom far beyond that of humans. Altman believes that "it can truly learn the distribution patterns of any data" and "generate the underlying rules of any data distribution."

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"Data" has become the key word for ASI, this human vision, and on the road to ASI, more and more tools or applications highly related to data are developing rapidly. Among them is business intelligence (BI), which deeply mines the value of data and supports data analysis within enterprises. Its progress resonates with the evolution of AI's ability to deal with data.

In China, according to data from the Prospective Industry Research Institute, it is expected that by 2029, the scale of China's business intelligence software market will exceed 3 billion US dollars, and the market's compound annual growth rate (CAGR) in the next five years will reach about 20%.

However, while the value of BI is widely recognized, the long-standing "product power" problem that BI has faced cannot be ignored. For example, high professionalism leads to insufficient coverage of people within enterprises (only specific groups have the ability to use it), and the output ability of BI is limited, including single report forms and insufficient depth of data analysis.

At this time, AI, which is on the way to ASI and in rapid development, has found a place to use.

From ANI (narrow artificial intelligence, including various assistants) to AGI (general artificial intelligence, current exploration) and finally to ASI, AI's understanding and value mining of data is an increasingly in-depth process. It gradually realizes scenario-driven value in all industries and ultimately moves towards Altman's prophecy. Intelligent BI, represented by large models, combined with BI, has become a typical representative and annotation of this.

With chat-based BI (ChatBI) as the main external manifestation, intelligent BI is becoming a direction pursued by many manufacturers. For example, Microsoft has upgraded and implanted the Copilot capability in its flagship BI product PowerBI (commonly referred to as PB in the industry), and Smartbi AIChat Bai Ze, a new generation of intelligent BI based on AI Agent, released by Smart in early August, are all convenient and efficient tools that can achieve data analysis through chat-style interaction like ChatGPT.

With the support of large models, the "product power" of BI is about to achieve new breakthroughs.01 Intelligent BI, Enhancing BI's "Product Power"

From a product perspective, the "upgrade" value brought about by the combination of large models and BI is reflected in several aspects.

1. Continuously Lowering Usage Barriers

Intelligent BI, with its conversational BI approach aimed at business personnel, means that business needs no longer require "translation" by data analysts or even IT engineers, but can be directly met and realized. In actual product experience, simple commands can obtain the desired bar charts:

Without dragging components, creating dashboards, and reports, it is more intuitive, flexible, and efficient.

2. Continuously Enriching Presentation Formats

Intelligent BI can automatically generate more types of charts and reports, thereby helping users better understand data.

For example, directly invoking preset graphic components in a specific library with natural language, such as bar charts and pie charts, and adjusting titles, legends, etc.

Under intelligent BI, users can explore and develop more presentation formats, making business support and data mining more effective.

3. Continuously Strengthening the Customer Value of Data Analysis

Intelligent BI can automatically generate more types of charts and reports, thereby helping users better understand data. For example, directly invoking preset graphic components in a specific library with natural language, such as bar charts and pie charts, and adjusting titles, legends, etc. Under intelligent BI, users can explore and develop more presentation formats, making business support and data mining more effective. With intelligent BI, the customer value of data analysis is continuously strengthened. It can automatically generate more types of charts and reports, helping users better understand data. For instance, it can directly invoke preset graphic components in a specific library with natural language, such as bar charts and pie charts, and adjust titles, legends, etc. Under intelligent BI, users can explore and develop more presentation formats, enhancing the effectiveness of business support and data mining.If simplicity in interaction and a rich variety of output formats are merely the "external" aspects of data analysis products, then data accuracy is the core value that the product can bring to customers.

Currently, the intelligent Business Intelligence (BI) developed by manufacturers such as Microsoft and Smartbi has almost universally added one or more data analysis capabilities on top of the dashboards and reports of traditional BI, such as time calculations, attribution analysis, data forecasting, and data interpretation.

Taking attribution analysis as an example, in Smartbi's White Elephant product, if one needs to find the reason for an abnormal contract amount in a certain month, simply inquiring about it will provide possible reasons:

In a specific application, a securities company discovered an abnormal indicator on the dashboard during a business analysis meeting. By directly asking Smartbi's White Elephant, they were able to conduct further analysis and exploration of the abnormal indicator.

From this, it can be seen that intelligent BI is moving BI from simple descriptive and a small amount of diagnostic capabilities towards in-depth diagnostic capabilities combined with internal and external knowledge-based guidance, and even directly prescribing "remedies" for business and management personnel.

02 Behind the "product power" is the multiple thresholds of AI+BI

Strengthening product power, large models are bringing a new growth curve to the BI industry and are becoming the main driving force for future markets. However, AI+BI is not something that "everyone can follow the trend" and there are objective thresholds.

In summary, this has led to a result: the competition in the BI industry, which was already very fierce, will become even more intense, making it difficult to maintain a stable pattern. Some manufacturers are using the opportunity of AI+BI to overtake others, which not only provides domestic manufacturers with an opportunity to counterattack international veteran manufacturers but also allows some manufacturers to occupy a more favorable position in the industry with the unique advantages of intelligent BI.

The former, BI manufacturers that have been developed abroad for many years are gradually being surpassed by domestic manufacturers. In the "China Business Intelligence and Analytical Software Market Tracking Report, 2023H2", the current top 10 BI market are FanRuan, Microsoft, Baidu, SAP, Smartbi, Yonghong, Inspur, Salesforce, IBM, and Yixun Huachen, indicating that the market has shifted from being dominated by a single foreign manufacturer to a situation where domestic and foreign manufacturers compete together. It is particularly worth mentioning that among the top 10 manufacturers, only Microsoft and Smartbi have launched direct intelligent BI products. Under the backdrop of the information technology innovation industry, the advantages of domestic manufacturers are more prominent. The combination of various factors has become an important reason for shaking up the industry's pattern.

The latter, also in this IDC report, the growth rates and rankings of various manufacturers do not match, and the market is far from the Matthew effect. For example, the fastest-growing manufacturer is Smartbi, which ranks fifth overall and second among Chinese BI manufacturers. It ranks first in the industry with a growth rate of 45.7%, far exceeding other peers and more than 12 times the market average. This strong performance is closely related to the development of intelligent BI.Analyzing the trends in the evolution of this industry landscape, several thresholds for achieving intelligent BI become apparent one by one—since it's AI+BI, "AI," "BI," and "+" are all indispensable.

1. "AI"—Large models are just an advancement of AI's application in BI

Intelligent BI must first be built on a long-term integration of "intelligence."

Microsoft's植入PB's Copilot will automatically adjust the data dashboard based on user needs and ultimately generate the desired data model, allowing users to become experts in data modeling directly through Copilot, thus promoting the digital transformation and construction of digital systems within enterprises.

In this context, Copilot has always been Microsoft's ace capability in the field of AI large models, and the "co-pilot" concept proposed by Microsoft based on this has become an important backdrop for the emergence of assistant-like large models.

Now, with Copilot embedded in PB to create an intelligent BI with natural language interaction, it is clear that this is not a one-time effort but comes from Microsoft's long-term cultivation of AI capabilities and integration with its various products.

Similarly, the rapidly growing Smart has started a forward-looking layout of AI very early on. In 2019, it was the first in the industry to achieve the integration of AI and data analysis, and based on its independently developed Natural Language Analysis (NLA), it realized the conversational analysis function. Subsequently, it was the first in the industry to release the ABI platform that integrates AI into data analysis, and then in 2023, it combined large model technology with BI products to launch the conversational analysis large model version, ultimately leading to the emergence of Bai Ze.

This indicates that the utilization of large models by intelligent BI should only be an "opportunity" for AI+BI, and those who directly want to follow the trend to "add" large models in BI products may find it difficult to work due to a lack of foundation. This is not a trend, it can only be a battle that is well-prepared.

This is particularly evident in Smart's more prominent technical advantages in conversational analysis compared to the industry. For example, Bai Ze is very similar to the Advanced Data Analysis capabilities provided by ChatGPT-o4—users specify CSV or Excel files, ChatGPT understands the question, generates Python code to solve the user's problem (figure: Advanced Data Analysis example, check weather data, analyze data, and make charts).

The computational capability stratification and other capabilities required behind this make Smart's unique AI technical advantage in doing intelligent BI, ultimately being able to execute complex data analysis logic, not just simple number checking. Obviously, this can only come from long-term AI layout.2. "BI"—The essence of AI+BI is AI for BI, with BI capability accumulation being the core.

It is evident from the natural language interaction with text boxes that the enhancement of product power by AI+BI is essentially addressing the "last mile" issue of BI. To some extent, AI+BI is AI for BI, hence the accumulation of BI capabilities remains central and crucial.

Breaking it down, the accumulation of BI essentially revolves around data models and metric models, which are precisely the areas where Microsoft and Smartbi have been accumulating advantages over the years. For instance, in terms of data models, both parties have established objectively benchmarked constellation patterns, multiple fact tables, OLAP analysis capabilities, etc. (such as DAX in Power BI), and Smartbi has also attempted to provide a stronger encapsulation capability for data models in metric models, offering multi-business perspective management capabilities that better integrate with scenarios.

In fact, this also illustrates that in the combination of AI+BI, BI is at the bottom, solving the connection with big data platforms, data lakes, and data middleware at the underlying data architecture level, which is an extension of the basic data architecture. AI, on the other hand, is at the top, addressing intelligent analysis applications and business execution issues, thus forming a complete system.

Metaphorically speaking, it is much like e-commerce plus express delivery; our users simply place an order and wait for the delivery, but behind the scenes, there must be a very complex e-commerce operation system plus a national or even global logistics system, which is invisible but core content.

3. "+"—Scenario practice is the "Wall of Lamentations" for latecomers.

The BI vendor with a leading growth rate is Smartbi, which ranks second in the domestic market. In the BI market, another interesting thing is that the "2023 China Banking Industry IT Solution Market Share Analysis Report" released by CCID Consulting, a subsidiary of the Ministry of Industry and Information Technology's CCID Research Institute, shows that Smartbi is also the market leader in the banking industry's business intelligence software product market in 2023.

Industry Know-how is the key issue of how AI+BI can "add up." Only with in-depth practice in industries and scenarios can intelligent BI be well executed.

In specific industries, without the accumulation of practice, it is difficult for latecomers to gain a competitive advantage, which includes both new BI players and mature BI vendors in the market when facing certain industries lacking practical understanding— the market share ranking of BI in the financial industry is precisely a product of this phenomenon, as the market ultimately only believes in and is willing to choose BI vendors who "know the industry."

Looking back, if industry knowledge is the energy reserve, then the AI large model becomes the fuse for value detonation. It is not difficult to see from the Smartbi case that the ability to achieve a significant increase that shakes the market structure is directly related to its 13 years of accumulation in BI data analysis and the accumulation of more than 5,000 customer experiences. Its performance in the financial industry directly illustrates the immense value of industry Know-how for BI vendors. Industry news indicates that with intelligent BI, Smartbi has successfully signed contracts with a top securities customer and a large integrator, and is also continuously following up with more than 100 large customers— the current commercialization and landing of intelligent BI are surprising, but do not forget that this is inseparable from industry understanding.It is evident that to excel in intelligent BI, "AI," "BI," and "+" are all indispensable. They are the inherent "barriers" that intelligent BI has brought with it since its inception. Vendors with comprehensive capabilities are leveraging these to seize new market opportunities.

03 Conclusion

Starting from 2023, AI and large models have been transforming the landscape of various industries. Features such as question-and-answer queries and intelligent assistants (like Copilot) have greatly improved product usability and significantly reduced the difficulty of performing professional business analysis.

Intelligent BI is right in the midst of this wave. It not only helps users extract value from data and achieve digital operations for businesses but also assists business personnel in optimizing processes and providing better service experiences for customers. Intelligent BI directly enhances the competitiveness and efficiency of enterprises from various dimensions, making its impact and value on businesses more profound.

"AI," "BI," and "+" are advancing comprehensively. BI is continuously integrating with large models, and the treasure trove of data is being further unearthed by intelligent BI. Business decision-making is moving towards higher levels of intelligence and automation. At the same time, intelligent BI is becoming a winning tool for some BI companies to comprehensively enhance their competitiveness and a weapon for individual businesses and even the entire industry to achieve a second growth curve.