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The Mobile Artificial Intelligence (AI) Market size is projected to increase by USD 39.91 billion, at a CAGR of 26.78% between 2023 and 2028. The surge in smartphone penetration significantly propels market expansion. Advancements in communication technologies and infrastructure, both wired and wireless, are fostering global smartphone adoption. Projections indicate a projected 4 billion smartphone users worldwide by 2025, with smartphone internet users already reaching 62% in 2021, driving mobile data traffic globally. The rising popularity of social networking platforms like Instagram, Facebook Messenger, WhatsApp, and Snapchat catalyzes the integration of human-machine interface (HMI) technologies such as AI, voice recognition, facial recognition, and gesture recognition into smartphones.
Moreover, the burgeoning demand for edge computing in IoT emerges as a pivotal trend shaping market dynamics. Edge computing, characterized by data processing proximity to its source, reduces latency and enhances response time, offering significant advantages in IoT ecosystems. Integration of HMI technologies into IoT devices like cameras, drones, smart speakers, smartphones, and smart televisions drives the deployment of AI chips, enabling power-efficient data processing and machine learning computation in mobile devices. Neural Processing Unit (NPU) technology, as well as advancements in computational photography, further enhance the capabilities of smartphones, providing users with improved imaging and processing performance. Zippia research indicates the growing significance of these technologies in shaping the future of smartphones and mobile devices.
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The mobile AI market is experiencing rapid growth driven by advancements such as 5G connectivity and the integration of vision processing units (VPUs). With the emergence of cloud computing, mobile devices can harness powerful computational capabilities, enabling enhanced technology node insights and leveraging innovations like Intel's 10nm node and FinFET transistors. Leading processors like Apple's A13 Bionic chip are pushing the boundaries of mobile AI performance. Cloud-based solutions ensure reliability and address concerns regarding privacy & security, while also enabling the delivery of personalized services tailored to individual user preferences. This convergence of technologies is reshaping the landscape of mobile AI, driving innovation and efficiency in various sectors.
The market share growth by the software segment will be significant during the forecast period. One of the most important market segments in the mobile artificial intelligence (AI) market is the software segment. The software segment can be broken down into different components, each of which plays a critical role in improving the performance and intelligence of your mobile device. One of the most important components is natural language processing (NLP) software, which allows mobile AI to learn and understand human speech.
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The software was the largest and was valued at USD 3.47 billion in 2018. Machine learning algorithms are another important software element that forms the backbone of mobile-AI apps. Machine learning algorithms help devices learn from user behaviour, adjust to user preferences, and provide personalized experiences. From predictive text input to image recognition to recommendation systems, ML improves mobile devices' overall intelligence and performance. Additionally, computer vision software enables mobile-AI to process and act on visual data. This element is essential for augmented reality (AR) and facial recognition applications, improving user experience and security on mobile devices. These factors under the software segment will drive the growth of the global market during the forecast period.
This smartphones segment is expected to grow during the forecast period at a moderate rate, owing to the saturation in the global market. The mobile artificial intelligence market is witnessing a decline in the unit shipments of smartphones due to the lack of innovation. The integration of new advanced technologies requires AI-chips that can process data faster. Most of the smartphones available in the market have these technologies, but these applications are not efficiently supported by the processors integrated into these devices. Therefore, smartphone users are finding AI-technologies a value addition to their devices. Therefore, smartphone OEMs are investing heavily in the development of AI-chips that offer the potential to integrate and deploy advanced technologies in smartphones. Therefore, these factors under the smartphone segment will drive the growth of the global market during the forecast period.
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North America is estimated to contribute 37% to the growth of the global market during the forecast period. Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. One of the reasons for mobile artificial intelligence market growth in this region is the rapid implementation of advanced technologies. In addition, the availability of a strong wired and wireless communication infrastructure, high Internet penetration, and a well-developed ecosystem of IoT devices are leading to the development of AI for IoT devices. US-based major smartphone original equipment manufacturers (OEMs) such as Apple and Google are heavily investing in Research and Development (R&D) to develop innovative products. This region also benefits from significant venture capital financing, further driving technology development and the utilization of real-world data, creating a virtuous circle that fuels market expansion. Additionally, the proliferation of drones generates vast amounts of drone-generated data, contributing to advancements in the global mobile artificial intelligence (AI) market.
In addition, the implementation of AI chips by Apple in its flagship smartphones is expected to accelerate the adoption of AI-chips in other IoT devices. Apple integrated A13 Bionic AI chips in its latest iPhones, including iPhone 11 and iPhone 11 Pro. The growing demand for smart home speakers such as Google Assistant and Amazon Alexa is also expected to attract investments in AI-chips. The abovementioned factors will drive the growth of the market in this region during the forecast period.
The surge in smartphone adoption significantly fuels market expansion, propelled by advancements in both wired and wireless communication technologies globally. Projections indicate a staggering 4 billion smartphone users worldwide by 2025, with smartphone internet users reaching 62% in 2021, driving mobile data traffic on a global scale. The escalating popularity of social networking platforms like Instagram, Facebook Messenger, WhatsApp, and Snapchat drives the integration of human-machine interface (HMI) technologies such as AI, voice recognition, facial recognition, and gesture recognition into smartphones.
Furthermore, the rising demand for edge computing in IoT emerges as a pivotal trend shaping market dynamics, offering advantages such as reduced latency and improved response time. Integration of HMI technologies into IoT devices like cameras, drones, smart speakers, smartphones, and smart TVs drives the deployment of AI chips, enabling power-efficient data processing and machine learning computation. However, a significant challenge hindering market growth is the inadequate availability of AI-experts, hampering the implementation of AI within business operations and impeding market growth analysis due to a shortage of experts with requisite knowledge of AI-technology.
Increasing smartphone penetration is notably driving market growth. Developments in wired and wireless communication technologies and communication network infrastructure are driving smartphone penetration globally. It is expected that the number of smartphone users across the world will reach 4 billion by 2025. The rising smartphone penetration increased the number of smartphone Internet users to 62% in 2021. This is driving mobile data traffic globally. The growing popularity and the increasing use of social networking platforms, such as Instagram, Facebook Messenger, WhatsApp, and Snapchat, are leading to the integration of human-machine interface (HMI) technologies such as AI, voice recognition, facial recognition, and gesture recognition into smartphones.
However, Qualcomm Technologies, Inc., Samsung Electronics Co. Ltd., Intel Corporation, IBM Corporation, Ericsson, and Sense Time. are among the vendors that are integrating these technologies into their product offerings. Thus, the rising penetration of smartphones and the increased use of AI in smartphones are expected to drive the growth of the global market during the forecast period.
Increasing demand for edge computing in IoT is an emerging trend shaping the market growth. Edge computing is a network architecture wherein the data is stored and processed near its origin. The advantage of edge computing is that the stored content is close to the client machine. This helps reduce latency and improve response time. IoT is an ecosystem of interrelated computing devices, objects, and machines that perform tasks without the need for human intervention. IoT device manufacturers are integrating HMI technologies in devices such as cameras, drones, smart speakers, smartphones, and smart Televisions (TVs). This is leading to the deployment of AI-chips in mobile that enable power-efficient data processing and machine learning (ML) computation in these devices.
Moreover, the AI chips integrated into these devices enable them to make real-time decisions. This market trends and analysis is expected to increase the use of AI in IoT devices including mobile. Hence, vendors are introducing new AI-chips, Crypto chips and platforms at the edge for IoT devices. Thus, the increasing use of edge in IoT will drive the adoption of AI-chips in IoT devices and will expand the growth of the market during the forecast period.
Inadequate availability of AI experts is a significant challenge hindering market growth. The demand for AI chips is growing owing to their potential benefits. However, the lack of workers with technical expertise in AI is hampering the growth of the mobile artificial intelligence (AI) systems market. Companies need to analyze all aspects before integrating AI because of its high R&D costs. Enterprises usually seek information from highly experienced AI professionals. Several new firms with low budgets have stated that a lack of talent is the greatest barrier to the implementation of AI within their business operations. The market growth analysis of an enterprise is hampered by a shortage of experts with the requisite knowledge of AI technology.
However, organizations need to prioritize talent acquisition and cultivation activities by recruiting people with strong technical backgrounds. Furthermore, they need to invest in skill and training programs to help retain AI practitioners. However, the lack of a skilled workforce, AI engineers, and technicians limit the deployment of AI in enterprises, which, in turn, may hamper the growth of the market during the forecast period.
Market forecasts include the adoption lifecycle of the market research and growth, covering from the innovator’s stage to the laggard’s stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the market report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their market growth and trends strategies.
Global Market Customer Landscape
Companies are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.
Alphabet Inc. - The company offers mobile-AI solutions such as Google Cloud-AI, and Google Assistant.
Apple Inc. - The company offers mobile-AI solution such as AI-virtual assistant Siri.
Baidu Inc. - The company offers mobile-AI solutions such as DuerOS, a voice assistant platform integrated into various smart devices and smartphones.
The market growth and forecasting report also includes detailed analyses of the competitive landscape of the market and information about 20 market companies, including:
Market analysis and report of qualitative and quantitative analysis of companies has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key market players. Data is qualitatively analyzed to categorize companies as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize companies as dominant, leading, strong, tentative, and weak.
The market is witnessing exponential growth fueled by advancements in tiny circuits and AI chipsets, particularly in the 10 nm node/10 nm segment segment and 7 nm technology node. These innovations enable hyper scaling of on-device AI capabilities, empowering smartphone AI processors with neural processing units (NPUs) and vision processing unit (VPU)/VPU processor.Key players like Snapdragon are introducing cutting-edge platforms such as the Snapdragon 7+ Gen 2 Mobile Platform, integrating AI-specific chipsets for enhanced performance in various applications, from smartphone photography to speech and voice recognition. The convergence of AI with virtual reality (VR) and AR/VR technology experiences further drives demand, especially in the mobile gaming industry and automotive sector.
To address cyber threats and ensure data security, regulatory bodies and industry groups collaborate to establish standardized frameworks and protocols, tackling interoperability issues and safeguarding against unauthorized access. Additionally, R&D investments and cloud-based processing are bolstering healthcare data security, particularly in health and fitness applications and wearables equipped with voice-activated AI assistants.As the market continues to evolve, partnerships and mergers and acquisitions play a crucial role in driving innovation, exemplified by companies like Facebook AI Research (FAIR) lab and Epic, enhancing object recognition and image enhancement capabilities in mobile AI technologies.
The market research report forecasts market growth by revenue at global, regional & country levels and provides an analysis of the latest trends and growth opportunities from 2018 to 2028
Market Scope |
|
Report Coverage |
Details |
Page number |
169 |
Base year |
2023 |
Historic period |
2018-2022 |
Market forecasting period |
2024-2028 |
Growth momentum & CAGR |
Accelerate at a CAGR of 26.78% |
Market Growth 2024-2028 |
USD 39.91 billion |
Market structure |
Fragmented |
YoY growth 2023-2024(%) |
26.33 |
Regional analysis |
North America, Europe, APAC, South America, and Middle East and Africa |
Performing market contribution |
North America at 37% |
Key countries |
US, China, Germany, UK, and France |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
Key companies profiled |
Alphabet Inc., Apple Inc., Baidu Inc., Beijing Kuangshi Technology Co. Ltd., C3.ai. Inc., Huawei Technologies Co. Ltd., Imagination Technologies Ltd., Intel Corp., International Business Machines Corp., MediaTek Inc., Microsoft Corp., NVIDIA Corp., OpenAI-L.L.C., Passio Inc., Qualcomm Inc., Samsung Electronics Co. Ltd., SenseTime Group Inc., Tencent Holdings Ltd., ThinkForce, and Dribbble Holdings Ltd. |
Market dynamics |
Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and recovery analysis and future consumer dynamics, Market condition analysis for the forecast period. |
Customization purview |
If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized. |
We can help! Our analysts can customize this market research report to meet your requirements.
1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation by Component
7 Market Segmentation by Application
8 Customer Landscape
9 Geographic Landscape
10 Drivers, Challenges, and Trends
11 Vendor Landscape
12 Vendor Analysis
13 Appendix
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