In a broad sense it refers to any method and system that allows a computer to pass the Turing test, while the narrow sense refers to let the computer simulate human intelligence through the study of human intelligence generated.
Product manager for AI to do it is through the actual operation of the product: Big Data + + advanced algorithms calculate force to complete.
First, the data phase
Data stage: AI include traditional product manager, product manager.
After several actual product summary, relations with traditional AI product manager, product manager is to include the relationship - that includes traditional AI product manager, product manager.
I thought for a moment, our products always tell the students why the difference with the traditional product manager? AI should be the product manager core competencies should be what? What mode of thinking is the product manager for AI?
Like AI product manager is to understand the content of the traditional product managers, product manager thing itself is relatively more different operating mode of thinking there are differences, so Benpian talk about AI AI era of product manager should be part of any ability to model .
AI product manager and product manager is a traditional inclusion and progressive relationship (AI include traditional product manager, product manager), not side by side comparison.
1. AI core competencies product manager
1.1 AI competency model
AI competency model is the product manager for self-assessment of the key strengths of weaknesses, only know their own inadequacies, to know the place needs to be strengthened.
By a visual check of the AI product manager competency model list, you will find AI product manager competency model is covered by a traditional product manager ability of the model.
Ability of the model:
From the market point of view of traditional product manager, product manager positions have emerged a large number of segments, such as front-end product manager, product manager for the background, data product manager, product manager for payment, ERP product manager, CRM product manager, supply chain, product manager, POP Product Manager and so on, AI is a product manager, product manager of these models and the ability to enhance the performance of these products and experience using AI techniques.
From the traditional to the AI product manager, product manager, in a cross-border capacity, 5 power products, framework knowledge, professional skills, organizational influence and so the level of knowledge needed basis reserves and capacity building, in order to improve communication efficiency and AI expert engineers.
AI technology is in a period of rapid development, the technology itself with each passing day, so the product managers and non-managers should seize this wave of product opportunities. Do come into force, product manager of the circle.
summary:
AI AI technology product manager have to know how, precisely because of AI technology to all product managers the opportunity to re-shuffle, the opportunity to re-zero starting line of the race, the opportunity AI technologies enabling product operation to re-shuffle.
A new opportunity AI technology "hot" to the foundation of all people to do product manager to do the operations manager, product manager for another good AI has made a masterpiece cases require operators AI AI product requires operators to understand AI technology, need to have AI product manager core competency model.
AI is a cross product manager positions, so not only understands technology but also understands the operations that need AI product manager competency model in cross-border capabilities.
1.2 data capabilities
AI and big data merging, has become a reality. AI techniques to obtain breakthrough results of the training algorithm through big data, and to AI technology is characterized by large data applications are everywhere, and gradually infiltrated into all sectors and in all areas.
We are faced with a large data applications as a symbol to AI technology for the characteristics of the new era. AI products combine to provide customers with big data platform solution is to adapt current technology trends and have a good market demand for products.
AI product manager should have six large capacity data products:
1. unified metadata management: Metadata refers to all the data in the context of "all systems, processes and documentation contained in the raw data is knowledge, unified metadata management has become an important part of the big data products for big data quality provide a basis for the maintenance and management of big data more efficiently.
2. Data Management Standards: big data product can be conducted in an orderly, must establish a unified data standard for metadata unified, integrated data integration, data quality improvement and so provide the basis.
3. Large Data Quality Management: Data quality is the basis of data applications, through the management of large data quality, you can get a clean, reliable data. This is an important goal of Big Data products, but also play a necessary precondition for large data value.
4. Master data management: master data across systems and modules, cross-sectoral, cross-regional, there are high quality requirements, time-sensitive requirements, fundamental and sensitive data being repeatedly used the business.
Master data is the nerve center of business information systems, is the basis of business operations and decision analysis, it is considered the gold data. Through the management of master data to ensure its integrity, consistency, accuracy, timeliness, so as to better support cross-sectoral, cross-application requires the application of data fusion.
5. Big Data Integration: Data integration is not just the large data set stored on the physical, but also according to data standards, unified metadata definition, the external data processing into target data services needed to establish between data inherent association.
6. Big Data security and privacy protection: data information into human production and life of convenience, but also brought unprecedented data security and privacy threats, large national security, business, small to personal privacy, all need from different angles to strengthen data security and privacy threats.
AI AI product manager in the data stage of development of products through big data, access to timely, accurate, reliable, high-quality data security desensitization, for large data-depth wide range of applications, enterprise data provide strong product transition of operations the starting point.
1.3 Data ecological closed-loop capability
Break the silos of data, building operational data of the products of the company, nowadays either BAT or other plant are working hard to build a large data products.
Alibaba Group, for example: its large data products nowadays operations, general steps to "establish organizational structure and specifications (the establishment of a cross-sectoral data table team) → carding applications (external data mining needs of the group) → carding business data (external data within an integrated Group) → introduction of big data product platform technology → large data products, "product of the big data become business assets provides the basis for data applications and data operations.
Second, the mountains and the countryside
Down to the Countryside: AI product manager to create new products.
AI product manager in the future through a process of large data products, will reach the mountains and the countryside stage.
Rustication here means: belt AI, traditional go.
It looks plain words well understood, but the logic behind it really simple.
With AI technology to the industry to go, so many customers will naturally understand some particularly effective pain points; then entirely AI way to solve, follow the path "to have pain points do product design". After the hit the customer pain points, bringing the effect is very obvious, fast iterative product, thereby providing better services to ensure that there are orders come in.
The effect of AI + trade scheme is obvious: First, it will bring a significant reduction in labor costs; secondly accuracy will be a big improvement; again there is disruptive change that is to create new products before the traditional method.
Three, AI era
AI era: AI product manager is the general manager / CEO
Traditional product manager era is a reference not only a good product manager can guide the development of products, but also to guide the company's development.
He is also a good performer, project management and team managers have a keen insight, flexibility to walk between the users psychological and product details, grinding out amazing products.
AI era, because their energy attributes AI technology gives the opportunity to re-define the product, thus giving hope to do so once the product manager who co-traditional products circle the opportunity to do the product.
Master the use of AI techniques and efficient cross-border, cross and other characteristics of the product and then re-organized to make the product that is the general manager or CEO, a product manager at AI arrive before becoming a CEO, you need to become an excellent AI product manager.
Prepare members of the CEO's excellent AI Product Manager product is people-centered.
Traditional times Product Manager is a user-centric goal is explicit demand, AI product manager for human-centered goal is not just to meet user demand implicit explicit demand, but also meet people's implicit demand.
AI era of human-centered product lifecycle management product matrix containing the research people, people competing products also include the person's own product manager AI requirements of the times because if you put the previous generation of products on the market to achieve the ultimate, you do not care about the competition opponents did, as long as you own and then beyond the previous generation of products on it.
If you put the previous generation of products on the market to achieve the ultimate, you do not have to care about what competitors do, as long as you own and then beyond the previous generation of products on it.
AI AI technology product manager to understand and operate without AI technology, but also to understand human nature in AI technology.
From the traditional to the AI product manager, product manager, tools and basic theories have in common, but there are a lot of different thinking.