At present, China's capital market has shown an extremely active environment despite the weak performance of overseas markets and global financing challenges. As of the end of 2016, there were 244 listed companies in the A-share securities sector, along with over 200 firms operating on the New Third Board. This positive market trend has attracted a large number of investors. In the first quarter of 2017, more than 10% of companies in the security sector achieved a net profit growth rate exceeding 70%, showcasing the industry’s strong momentum.
The year 2017 marked a significant milestone for artificial intelligence (AI), which became one of the most talked-about technologies that year. In China, AI applications have primarily focused on computer vision, speech recognition, and natural language processing. Thanks to the extensive video surveillance infrastructure built through the "Safe City" initiative over the past decade, computer vision has found clear and fast deployment opportunities. As a result, the security industry is expected to be the fastest in terms of AI industrialization, commercialization, and competition.
This paper aims to analyze the evolving trends of the third decade of the security industry in the AI era, drawing from the ten-year cycle patterns observed in the past. It also explores how AI is reshaping the competitive landscape of the security sector, providing insights for industry peers.
First, the ten-year cycle law reemerges, signaling a major transformation in the security industry during the AI era.
Looking back at the development of the domestic security monitoring industry over the past 20 years, it becomes evident that the industry has followed a similar pattern to broader social and economic cycles—approximately a decade per cycle. In the mid-1990s, the domestic security market began its journey, with the first cycle peaking around 2006. During this period, analog technology dominated, with products such as black-and-white/color cameras, VCRs, multi-screen splitters, video matrices, and monitors being the mainstay. Brands like MinTong, Panasonic, Sony, Samsung, AnXun, PELCO, and AD led the market, mostly from Taiwan and overseas.
From 2006 onward, the industry entered the digital era, driven by hard disk recorders, IP cameras, HD cameras, and network video storage. Domestic brands such as Hikvision, Dahua, and Yushu emerged as market leaders, capitalizing on the digital revolution and the "Safe City" construction wave. This rapid growth led to the rise of several large-listed companies, some of which have become global security giants. During this phase, the influence of foreign brands declined significantly, with many even disappearing from the Chinese market.
By 2016, the traditional "Safe City" projects were nearing completion, leading to severe product homogenization and price wars among major players. This signaled the end of the second decade-long cycle.
With the advent of deep learning and AI, the third decade of the security industry has begun, and 2017 naturally marks the start of this new cycle. The first decade was the analog era, the second the digital and high-definition era, and the third unquestionably the AI era.
Second, analyzing the changing trends in the third decade.
From the transformations of the first two decades, we can see that technological and product changes drive shifts in market demand and competition. The shift from analog to digital technology not only created massive demand for "Safe City" projects but also reshaped the competitive landscape. Many once-dominant foreign brands lost their positions due to non-subversive technological upgrades, allowing local players to take over. Similarly, the AI-driven technological change will bring even more disruptive changes to market demands and competition dynamics.
1. Market demand will be redefined.
In the previous decade, the security market mainly focused on "clear, well-received, and transmitted" requirements, emphasizing information acquisition, transmission, and storage. With AI, the focus is shifting to "query, analyze, and predict," emphasizing data collection, analysis, and risk prediction. Security monitoring is moving from the information and digital era into the data age, paving the way for the big data era in security.
Public security big data platforms, influenced by internet companies, have been developed to aggregate and analyze data such as personal identity, hotel registration, and vehicle data. However, issues like data source uncertainty and lack of real-time processing have limited their effectiveness. AI technologies like face recognition and video structuring are addressing these gaps, making big data applications more practical and efficient.
2. Market size will expand significantly.
In the last decade, the growth rate of the security market slowed down, with growth falling below 20% by 2016. The arrival of AI is expected to unlock new market demands and create more application scenarios, leading to substantial market expansion. It is estimated that by 2022, the AI security market will grow at a compound annual rate of 40%-50%.
Additionally, AI will redefine the use of surveillance images, installation locations, and device metrics, requiring system upgrades. New areas like community entrances, banks, and parking lots will become key points for data collection, creating numerous market opportunities.
3. The market competition pattern faces reshuffling.
AI introduces a different technological approach compared to traditional security, with high barriers to entry. This allows new AI startups to enter the market with fresh perspectives, challenging established players. The growing market potential will attract non-traditional competitors, such as tech giants and AI-focused startups, leading to a reshaped competitive landscape.
4. A healthier security ecosystem will emerge.
Over the past decade, the security industry has seen consolidation, with a few giants dominating the market. This has hindered innovation and sustainable development. AI brings the opportunity to rebuild a more balanced and innovative ecosystem, with a longer supply chain involving algorithms, hardware, and applications.
Third, analyzing the competitive landscape in the AI era.
As mentioned, the AI era presents new opportunities for market reshuffling. Traditional security companies, internet firms like Baidu and Huawei, and AI startups like Yitu and Shangtang are all entering the field. Each has unique strengths and challenges.
The technical competition in AI hinges on three factors: algorithms, computing power, and data resources. While algorithmic expertise is crucial, traditional security companies hold advantages in brand recognition, sales channels, and on-site support. They also possess strong hardware capabilities, especially in front-end devices like cameras.
Although AI algorithms are advancing rapidly, they still require continuous iteration and optimization. Edge computing and cloud computing are becoming essential, and many AI teams are developing front-end solutions and AI-specific chips to gain a competitive edge.
In the future, traditional security companies will leverage their market presence to lead early adoption, educating the market and laying the foundation for AI integration. Meanwhile, AI algorithm teams will benefit from collaborations and strategic investments to overcome industry limitations.
Internet companies, with their big data and cloud service capabilities, are well-positioned to offer comprehensive solutions for high-end users. Network communication equipment firms can also provide advanced security solutions, securing their place in the evolving market.
The future of the security industry lies in the convergence of AI and security. With continued innovation and collaboration, China's security industry is poised to lead globally, benefiting society as a whole.
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