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市場調查報告書
商品編碼
1803052
全球人工智慧驅動的慢性疼痛管理市場預測(至 2032 年):按組件、部署類型、分銷管道、應用、最終用戶和地區進行分析AI Chronic Pain Management Market Forecasts to 2032 - Global Analysis By Component (Software, Hardware, and Services), Deployment Mode, Distribution Channel, Application, End User and By Geography |
根據 Stratistics MRC 的數據,全球 AI 慢性疼痛管理市場預計在 2025 年達到 60.7 億美元,到 2032 年將達到 207.8 億美元,預測期內的複合年成長率為 19.2%。
AI慢性疼痛管理是指應用人工智慧技術來評估、監測和治療長期疼痛狀況。它整合了機器學習、預測分析和數位工具,以個人化疼痛管理策略,提高診斷準確性並最佳化治療效果。透過分析患者數據、穿戴式裝置輸入和病歷,AI可以實現早期療育,減少鴉片類藥物依賴,並改善慢性疼痛患者的整體生活品質。
慢性疼痛的流行
全球慢性疼痛的增加推動了對創新疼痛管理解決方案的需求。由於人口老化和生活方式因素,關節炎、纖維肌痛和神經病變疼痛等疾病正變得越來越普遍。傳統的疼痛管理方法往往無法提供長期緩解,這激發了人們對人工智慧方法的興趣。人工智慧技術能夠更精確地分析患者數據並最佳化治療方案。隨著醫療保健系統尋求更有效、更具可擴展性的解決方案,人工智慧正逐漸成為個人化疼痛照護的關鍵推動因素。這種日益成長的需求正在推動醫院、診所和數位健康平台的投資和應用。
來自醫療保健專業人士的抵制
對數據可靠性、臨床檢驗以及缺乏人工監督的擔憂阻礙了人工智慧的推廣應用。醫生可能不願意相信演算法推薦,而更傾向於相信自己的臨床判斷,尤其是在複雜的疼痛病例中。有限的培訓和人工智慧工具的機會進一步加劇了醫學界的阻力。此外,監管的不確定性和倫理方面的考慮也導致人們對採用基於人工智慧的干涉措施猶豫不決。這種阻力減緩了市場滲透,並限制了人工智慧在疼痛治療領域中變革的潛力。
個人化預測護理
預測演算法可以透過預測疼痛發作並建議預防性干預措施來改善患者的治療效果。這些功能支持主動護理模式,減少對被動且通常無效的治療的依賴。與穿戴式裝置和行動應用程式的整合增強了即時監控和回饋迴路。隨著精準醫療的日益普及,人工智慧驅動的疼痛管理與個人化醫療的整體醫療趨勢相契合。這一機遇正吸引新興企業、科技巨頭和差異化醫療服務提供者。
預測不準確和病人受傷的風險
疼痛管理中的人工智慧系統容易受到資料集偏差或不完整導致的誤差的影響。誤診和不恰當的治療建議可能會對患者造成傷害,並削弱人們對該技術的信任。過度依賴缺乏適當臨床監督的演算法可能會加劇風險,尤其是在複雜或非典型病例中。預測模型中的錯誤可能導致治療延誤並使患者病情惡化。監管審查正在加強,以確保人工智慧應用的安全性和課責。這些風險對市場信譽和長期應用構成了重大威脅。
COVID-19的影響
新冠疫情加速了數位醫療工具(包括基於人工智慧的疼痛管理平台)的普及。封鎖措施和麵對面診療服務受限,增加了對遠端監控和虛擬諮詢的需求。人工智慧工具透過實現症狀追蹤和居家治療協調,填補了慢性疼痛護理領域的空白。然而,供應鏈中斷和資本重新配置暫時減緩了新型人工智慧解決方案的開發和部署。這種轉變將繼續支持人工智慧主導的慢性疼痛管理解決方案的成長。
預計軟體領域將成為預測期內最大的領域
由於個人化治療工具、用於疼痛預測的先進機器學習以及雲端遠距遠端醫療解決方案的日益普及,預計軟體領域將在預測期內佔據最大的市場佔有率。值得關注的趨勢包括基於應用程式的疼痛監測、與穿戴式裝置的整合以及基於訂閱的人工智慧平台。近期的進展體現在科技公司與醫療保健提供者之間的合作,旨在建立可互通的系統,以支援與電子健康記錄的一致性、簡化臨床決策流程以及以患者為中心、以結果主導的護理模式。
預計居家醫療領域在預測期內將以最高複合年成長率成長
預計居家醫療領域將在預測期內實現最高成長率,這得益於人們對物聯網設備、穿戴式感測器和基於人工智慧的監控系統等技術支援的遠端個人化護理的興趣日益濃厚。主要趨勢包括虛擬疼痛管理、即時數據驅動的自適應護理以及用於早期症狀檢測的預測工具。近期的創新促使技術提供者和醫療保健機構建立策略合作夥伴關係,提供擴充性的雲端支援平台,以增強患者能力,減少對醫院的依賴,並與不斷發展的報銷和基於價值的護理模式保持一致。
由於慢性疼痛患者數量的增加、數位醫療系統的擴展以及向非鴉片類藥物治療的轉變,預計亞太地區將在預測期內佔據最大的市場佔有率。人工智慧整合行動平台、穿戴式健康追蹤器和雲端基礎的分析等技術正日益普及。主要趨勢包括虛擬疼痛支援、多語言人工智慧工具和遠端醫療整合。近期發展包括區域高科技醫療夥伴關係、政府主導的數位醫療項目,以及對可擴展人工智慧解決方案的投資增加,以滿足多樣化的患者需求。
由於慢性疼痛患者人數眾多、醫療保健體系健全以及數位化治療解決方案的廣泛應用,北美預計將在預測期內呈現最高的複合年成長率。人工智慧診斷工具、穿戴式疼痛監測設備以及與電子健康記錄相連的雲端整合平台等技術是關鍵推動因素。新興趨勢包括個人化疼痛管理演算法、神經調節洞察和虛擬指導。近期的里程碑包括醫院採用人工智慧工具的激增、生技藥品研究資金的增加以及基於遠端醫療的疼痛護理服務的擴展。
According to Stratistics MRC, the Global AI Chronic Pain Management Market is accounted for $6.07 billion in 2025 and is expected to reach $20.78 billion by 2032 growing at a CAGR of 19.2% during the forecast period. AI Chronic Pain Management refers to the application of artificial intelligence technologies to assess, monitor, and treat long-term pain conditions. It integrates machine learning, predictive analytics, and digital tools to personalize pain management strategies, improve diagnosis accuracy, and optimize treatment outcomes. By analyzing patient data, wearable device inputs, and medical histories, AI enables early intervention, reduces dependency on opioids, and enhances overall quality of life for individuals suffering from chronic pain.
Growing prevalence of chronic pain
The increasing global burden of chronic pain is driving demand for innovative management solutions. Conditions such as arthritis, fibromyalgia, and neuropathic pain are becoming more prevalent due to aging populations and lifestyle factors. Traditional pain management methods often fall short in providing long-term relief, prompting interest in AI-driven approaches. AI technologies offer the potential to analyse patient data and optimize treatment plans with greater precision. As healthcare systems seek more effective and scalable solutions, AI is emerging as a key enabler of personalized pain care. This growing need is catalysing investments and adoption across hospitals, clinics, and digital health platforms.
Resistance from healthcare professionals
Concerns around data reliability, clinical validation, and loss of human oversight hinder adoption. Physicians may be reluctant to trust algorithmic recommendations over their clinical judgment, especially in complex pain cases. Limited training and exposure to AI tools further exacerbate resistance within the medical community. Additionally, regulatory ambiguity and ethical considerations contribute to hesitation in deploying AI-based interventions. This resistance slows market penetration and limits the full potential of AI in transforming pain care.
Personalized and predictive treatment
Predictive algorithms can forecast pain flare-ups and recommend pre-emptive interventions, improving patient outcomes. These capabilities support proactive care models, reducing reliance on reactive and often ineffective treatments. Integration with wearable devices and mobile apps enhances real-time monitoring and feedback loops. As precision medicine gains traction, AI-driven pain management aligns with broader healthcare trends toward individualized care. This opportunity is attracting start-ups, tech giants, and healthcare providers seeking to differentiate their offerings.
Risk of inaccurate predictions and patient harm
AI systems in pain management are vulnerable to inaccuracies stemming from biased or incomplete datasets. Misdiagnosis or inappropriate treatment recommendations can lead to patient harm, undermining trust in the technology. Overreliance on algorithms without adequate clinical oversight may exacerbate risks, especially in complex or atypical cases. Errors in prediction models can result in delayed care, worsening patient conditions. Regulatory scrutiny is intensifying to ensure safety and accountability in AI applications. These risks pose a significant threat to market credibility and long-term adoption.
Covid-19 Impact
The COVID-19 pandemic accelerated the adoption of digital health tools, including AI-based pain management platforms. Lockdowns and limited access to in-person care drove demand for remote monitoring and virtual consultations. AI tools helped bridge gaps in chronic pain care by enabling symptom tracking and treatment adjustments from home. However, supply chain disruptions and funding reallocations temporarily slowed development and deployment of new AI solutions. This shift continues to support growth in AI-driven chronic pain management solutions.
The softwaresegment is expected to be the largest during the forecast period
The softwaresegment is expected to account for the largest market share during the forecast period, fuelled by increasing adoption of personalized treatment tools, advanced machine learning for pain prediction, and cloud-enabled remote care solutions. Notable trends include app-based pain monitoring, integration with wearable devices, and subscription-based AI platforms. Recent advancements feature collaborations between tech companies and healthcare providers to create interoperable systems that align with electronic health records, streamline clinical decision-making, and support patient-centric, outcome-driven care models.
The homecaresegment is expected to have the highest CAGR during the forecast period
Over the forecast period, the homecaresegment is predicted to witness the highest growth rate, driven by growing interest in remote, individualized care supported by technologies like IoT-enabled devices, wearable sensors, and AI-based monitoring systems. Key trends include virtual pain management, real-time data-driven adaptive care, and predictive tools for early symptom detection. Recent innovations involve strategic alliances between technology providers and healthcare organizations to deliver scalable, cloud-supported platforms that empower patients, lower hospital dependency, and align with evolving reimbursement and value-based care models.
During the forecast period, the Asia Pacific region is expected to hold the largest market sharedue to increasing cases of chronic pain, expanding digital healthcare systems, and a shift toward non-opioid treatment options. Technologies such as AI-integrated mobile platforms, wearable health trackers, and cloud-based analytics are gaining traction. Key trends include virtual pain support, multilingual AI tools, and telemedicine integration. Recent progress includes regional tech-healthcare partnerships, government-led digital health programs, and rising investments in scalable AI solutions tailored to diverse patient needs.
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to widespread chronic pain cases, robust healthcare systems, and strong uptake of digital treatment solutions. Technologies such as AI-driven diagnostic tools, wearable pain monitoring devices, and cloud-integrated platforms linked to electronic health records are key enablers. Emerging trends include personalized pain management algorithms, neuromodulation insights, and virtual coaching. Recent milestones include a surge in hospital adoption of AI tools, increased funding for biologics research, and expanded telehealth-based pain care services.
Key players in the market
Some of the key players profiled in the AI Chronic Pain Management Market includeJohnson & Johnson, Horizon Therapeutics, Pfizer, Amgen, Medtronic, Mallinckrodt, Teva Pharmaceuticals, AstraZeneca, AbbVie, Bristol-Myers Squibb, Eli Lilly, Regeneron Pharmaceuticals, BoehringerIngelheim, Novartis, and GlaxoSmithKline (GSK).
In July2025, Johnson & Johnson announced the launch of the VIRTUGUIDE(TM) System. This AI-powered, patient-matched solution is designed to support Lapidus procedures2, a type of bunion surgery that helps realign the foot by joining two bones near the arch (the first metatarsal bone and the medial cuneiform).3 The system uses pre-operative planning software, developed in collaboration with PeekMed(R), to assess each patient's bunion and make personalized recommendations for the intended correction.
In October2023,Amgen announced that it has completed its acquisition of Horizon Therapeutics plc for $116.50 per share in cash, representing a transaction equity value of approximately $27.8 billion.