AI big model, is killing to B software?

Original Source: Technical Leadership

Image source: Generated by Unbounded AI‌

Recently, the "Hundred Models War" is in full swing, and major technology companies have launched their own general models and industry models that combine industry characteristics. The prosperity of the technology industry even made people temporarily forget the ferocity of the wave of layoffs in major factories.

The industry model has received unprecedented attention, which means that the application of artificial intelligence in the To B industry will be further deepened.

By using large industry models, enterprises can more conveniently build exclusive models that meet their own business needs, improve work efficiency and quality, and further reduce costs. At the same time, the use of large industry models can also help companies better realize digital transformation and improve their competitiveness and market position.

As soon as the news came out, these toB software manufacturers could not sit still, and had to question their souls, where are the barriers to B-end software?

**AI big model strikes, which toB software ushers in life and death? **

1. Data Analysis

BI (Business Intelligence) and other data analysis software play an important role in the management and decision-making of enterprises. This type of software can process, analyze and visualize massive amounts of internal and external data to help companies make more informed decisions. However, with the continuous development of large model technology, some AI platforms can start to provide more intelligent data analysis and prediction services, which can better meet the needs of enterprises. There is no doubt that this type of data analysis software will face being risk of substitution.

2. Standard process class

The powerful data processing and learning capabilities of the large model can automatically process some highly repetitive tasks with clear rules through the learning and analysis of a large amount of office data, so as to avoid simple repetitive but time-consuming and labor-intensive manual processing. Therefore, like all highly standardized occupations, standard process software such as OA (office automation), business approval flow, and marketing automation are also facing the threat of being replaced.

For example, in the OA system, AI can automate some daily office processes, such as mail classification, file filing, etc. In the business approval process, AI can speed up the approval process and improve process efficiency through automatic review and classification of application content. In marketing automation, AI large models can realize automated marketing and accurate recommendations through automatic analysis and prediction of user behavior, and improve conversion rates.

Third, Execution Automation

RPA (Robotic Process Automation) is a business process automation technology based on software robots and artificial intelligence (AI). Replace human labor in high-level, well-defined tasks. For example, in the financial field, RPA can automatically perform tasks such as accounting processing, data entry, and invoice verification; in the field of customer service, RPA can automatically reply to customer emails and handle complaints through natural language processing technology.

However, the shortcomings of RPA are also obvious. For example, it cannot handle complex and highly variable processes, and tasks that require human decision-making and judgment are not suitable for RPA. In addition, RPA requires configuration and programming, so it may require a high technical threshold and cost.

Based on natural language processing and machine learning technology, AutoGPT can perfectly avoid these problems, automatically understand, learn and imitate human work, so it can replace the functions of some RPA products.

Therefore, in the future, RPA needs to constantly combine the capabilities of AI to iterate products, otherwise such less intelligent automatic execution robots will easily "fall out of favor".

4. Light Consulting Service Software

This type of software can help companies understand industry dynamics, market trends and competition conditions, and provide decision support. However, with the development of AI technology, it is actually better and more convenient for Big Model to provide intelligent industry analysis and consulting services.

Therefore, in the future, not only software, but the entire light consulting industry will be the hardest hit area that will be affected by the AI model.

5. Traditional educational software

Compared with traditional online education software, such as English training, programming education, etc., AI has more obvious advantages, such as:

1. Automated teaching: AI large models can automatically generate teaching plans to provide more personalized and accurate teaching content, thereby reducing the dependence on manual teaching.

2. Intelligent feedback: AI large model can monitor students' learning status and progress in real time, and give timely feedback and suggestions to help students better master knowledge and skills.

3. Customized learning path: The AI large model can customize the learning path according to the individual needs and learning progress of students, providing more flexible and diverse learning methods.

4. Intelligent evaluation: AI large model can automatically evaluate students' learning outcomes and provide more objective and accurate evaluation results, so as to help students better understand their own learning progress and level.

From this point of view, several links of education have been covered clearly and clearly. What future does online education have?

**Which toB software are not easily replaced by AI? **

1. Complex business management software

Complex business management software such as ERP (Enterprise Resource Planning), WMS (Warehouse Management System) and TMS (Transportation Management System) play an important role in businesses. This type of software can help enterprises realize the optimal allocation of resources, the management of purchase, sales and inventory, and the monitoring of the transportation process. However, complex business management software often needs to deal with a large amount of data and complex processes, and needs to be customized based on the actual situation of the enterprise. AI technology can provide auxiliary functions to a certain extent, but it is difficult to completely replace such software.

2. Software with scarce data

Some industry software, such as precision manufacturing, discrete manufacturing and other industrial software, as well as new drug research and development management software, equipment production management software and other industry management software, usually need to process a large amount of data and complex algorithms. The data and algorithms in these software are often scarce resources that only a few companies can have. In addition, human expertise and experience still play an important role in processing highly specialized data and knowledge, so it is difficult to be completely replaced by AI large models.

3. Industry management software

Industry management software such as new drug research and development management software and equipment production management software play an important role in certain specific industries. This type of software can help enterprises realize the standardization, flow and standardization of R&D, production, quality, and material management. Because the business and management models of different industries are very different, and these software usually need to deal with complex industry rules and knowledge. Therefore, it is difficult for AI technology to develop general industry management software for each industry.

Based on the above, it is not difficult to find that whether it is human positions or software, all those that are not easy to be replaced by AI are actually those that are highly professional, complex, technical and interactive. But in the future, if these softwares want to survive and develop better, they must cooperate and integrate with AI large models to jointly provide more efficient and accurate services.

**In the era of AI, how does toB software deal with challenges? **

1. Combining AI large model to reshape the product

Since the end of last year, large language models represented by ChatGPT and Wenxin Yiyan have led a new round of revolution in the global information technology field. The new wave is surging, AI is reconstructing the future, and thousands of industries will usher in new opportunities.

Under this new opportunity, Baidu has issued a statement more than once, and will use AI large models to reconstruct all products.

Product remodeling is to combine with AI large model, and through the assistance of artificial intelligence technology, improve the intelligence and personalization of products, and even reconstruct their own products.

For example, the toB software industry can consider using technologies such as natural language processing and machine learning to realize functions such as intelligent customer service and intelligent recommendation, thereby enhancing user experience and product value.

Second, take advantage of the window period, reposition and switch tracks

Taking advantage of the window period, reposition your products and services, and switch to a more promising track. In this ever-changing era, no product or even an industry can become an evergreen tree. If you stand still, you will only accelerate its decline. Therefore, at the right time, switch your thinking strategy and step into a new track. Breathe new life into it. For example, the toB software industry can also consider entering emerging fields such as cloud computing, big data, and artificial intelligence based on its own needs and development strategies to obtain more development opportunities.

3. Provide services for the AI model, sell water and shovels

It is an undeniable fact that AI large models are gradually eating up the market share of to B software. However, that doesn't mean the software is helpless and just sits and dies. In fact, these software still have advantages in many aspects, such as mature technology, stable performance, rich functions and so on.

Of course, if your product has indeed been besieged by AI and has been put to the ground, and there is no exit for transformation in a short period of time, then perhaps you should stop as soon as possible and turn your business around in other directions.

For example, consider providing data labeling, training, optimization and other services for AI large models, as well as related hardware devices and software tools.

Really, there's no shame in that.

The work of selling water, pots, and shovels may not seem that high-end, but it is indeed a strong demand. As long as you can survive through these, you will be able to make money just around the corner.

After having money, slowly consider the transformation and upgrading of the business model, so as to occupy a place in the development of AI technology.

In essence, a large model is a tool just like any platform or software. All enterprises should pay close attention to the development of AI large models, actively explore its application fields, and seek ways to cooperate with AI large models. As long as you can make good use of it, you will not be destroyed or harmed by it, but will benefit instead.