Global AI in Fitness and Wellness Market Size is valued at USD 9.8 Billion in 2024 and is predicted to reach USD 46.1 Billion by the year 2034 at a 16.8% CAGR during the forecast period for 2025-2034.
AI is changing the way people think about their health by giving them personalized workout plans, feedback in real time, and more advanced health tracking. Apps and gadgets that are powered by AI, like fitness trackers and smartwatches, look at information like heart rate, activity levels, and sleep habits to help people get more out of their workouts and feel better overall. Virtual personal trainers and workout platforms driven by AI can make training plans just for each person based on their goals, progress, and personal tastes. AI also improves tracking nutrition, dealing with stress, and avoiding injuries. This makes exercise and wellness easier to access, more effective, and more tailored to each user.
Market growth is propelled by number of factors, including technological advancements, increasing demand for personalization, increasing health awareness, advancement in wearable technology, growth of digital wellness platforms, and many others. However, high costs of AI implementation and privacy and security concerns are likely to hinder market growth during the forecast period.
The AI in the fitness and wellness market is segmented into type, application, and end user. As per the type segment, the market is segmented into AI-enabled fitness apps, AI-integrated wearable devices, virtual personnel trainers, and AI-powered smart gym equipment. By application, the market is segmented into personalized fitness recommendations, health monitoring and tracking, virtual coaching and training and smart nutrition and diet planning. Based on end users, the industry is bifurcated into individuals, fitness centres and gyms, healthcare facilities, sports teams and athletes.
The AI-enabled fitness Apps category is expected to hold a major share of the global AI in the fitness and wellness market. Demand for fitness apps that offer individualized training schedules, dietary guidance, and mental wellness support—all of which can be improved by AI—is rising as more and more individuals place a high priority on their health and wellness. Additionally, these apps are now more efficient and user-friendly due to ongoing advancements in AI technology, such as enhanced machine learning algorithms and natural language processing, which have increased adoption and retention rates. Additionally, the COVID-19 epidemic hastened the adoption of digital fitness solutions considerably. Because AI-enabled workout applications are flexible and convenient, many customers are sticking with them even after clubs reopen, which drives revenue growth.
Personalized fitness recommendations are projected to rapid growth in the global AI in the fitness and wellness market. One of the primary sources of revenue is the advancement of complex AI algorithms that can evaluate massive datasets and offer individualized, highly accurate recommendations. To provide individualized regimens, these algorithms take into account several variables, including the user's fitness levels, preferences, historical performance, and health data. Furthermore, customers may conveniently access customized fitness guidance at any time and from any location with the help of AI-powered personalized recommendations. Due to its accessibility, the market has grown, drawing in more people and raising potential sales.
The North American AI in the fitness and wellness market is predicted to register the highest market share in the near future. One of the main factors in the region is the extensive use of wearables like fitness trackers and smartwatches. Strong market presences include Fitbit, Apple, and Garmin, among others, which offer AI-enhanced features that measure health indicators, offer individualized insights and inspire consumers. Furthermore, corporate wellness is becoming more and more important in North America. AI-driven wellness initiatives are becoming popular among businesses as a way to boost productivity, lower medical expenses, and improve employee health. The market is expanding as a result of this tendency. In addition, Europe is likely to grow rapidly in the global AI in the fitness and wellness market due to rapid digital transformation and rising awareness regarding fitness apps.
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Report Attribute |
Specifications |
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Market Size Value In 2024 |
USD 9.8 Billion |
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Revenue Forecast In 2034 |
USD 46.1 Billion |
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Growth Rate CAGR |
CAGR of 16.8% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Mn and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Type, Application, End-User |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
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Competitive Landscape |
Fitbit, Apple Inc., Google LLC, Samsung Electronics Co., Ltd., Garmin Ltd., MyFitnessPal, Nike, Inc., Adidas AG, Under Armour, Inc., Amazon.com, Inc., Microsoft Corporation, IBM Corporation, Xiaomi Corporation, Polar Electro Oy, Wahoo Fitness, Orangetheory Fitness, ClassPass Inc., Tonal Systems, Inc., Virtuagym, Zwift, Inc., Technogym S.p.A., Asana Rebel GmbH, Viome Inc., Mirror (Lululemon Athletica Inc.), Peloton Interactive, Inc. |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI in Fitness and Wellness Market Snapshot
Chapter 4. Global AI in Fitness and Wellness Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Type Estimates & Trend Analysis
5.1. by Type & Market Share, 2024 & 2034
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Type:
5.2.1. AI-Enabled Fitness Apps
5.2.2. AI-Integrated Wearable Devices
5.2.3. Virtual Personal Trainers
5.2.4. AI-Powered Smart Gym Equipment
Chapter 6. Market Segmentation 2: by End User Estimates & Trend Analysis
6.1. by End User & Market Share, 2024 & 2034
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by End User:
6.2.1. Individuals
6.2.2. Fitness Centers and Gyms
6.2.3. Healthcare Facilities
6.2.4. Sports Teams and Athletes
Chapter 7. Market Segmentation 3: by Application Estimates & Trend Analysis
7.1. by Application & Market Share, 2024 & 2034
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Application:
7.2.1. Personalized Fitness Recommendations
7.2.2. Health Monitoring and Tracking
7.2.3. Virtual Coaching and Training
7.2.4. Smart Nutrition and Diet Planning
Chapter 8. AI in Fitness and Wellness Market Segmentation 4: Regional Estimates & Trend Analysis
8.1. North America
8.1.1. North America AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
8.1.2. North America AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by End User, 2021-2034
8.1.3. North America AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
8.1.4. North America AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
8.2. Europe
8.2.1. Europe AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
8.2.2. Europe AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by End User, 2021-2034
8.2.3. Europe AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
8.2.4. Europe AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
8.3. Asia Pacific
8.3.1. Asia Pacific AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
8.3.2. Asia Pacific AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by End User, 2021-2034
8.3.3. Asia-Pacific AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
8.3.4. Asia Pacific AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
8.4. Latin America
8.4.1. Latin America AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
8.4.2. Latin America AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by End User, 2021-2034
8.4.3. Latin America AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
8.4.4. Latin America AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
8.5. Middle East & Africa
8.5.1. Middle East & Africa AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
8.5.2. Middle East & Africa AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by End User, 2021-2034
8.5.3. Middle East & Africa AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
8.5.4. Middle East & Africa AI in Fitness and Wellness Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles
9.2.1. Fitbit
9.2.2. Apple Inc.
9.2.3. Google LLC
9.2.4. Samsung Electronics Co., Ltd.
9.2.5. Garmin Ltd.
9.2.6. MyFitnessPal
9.2.7. Nike, Inc.
9.2.8. Adidas AG
9.2.9. Under Armour, Inc.
9.2.10. Amazon.com, Inc.
9.2.11. Microsoft Corporation
9.2.12. IBM Corporation
9.2.13. Xiaomi Corporation
9.2.14. Polar Electro Oy
9.2.15. Wahoo Fitness
9.2.16. Orangetheory Fitness
9.2.17. ClassPass Inc.
9.2.18. Tonal Systems, Inc.
9.2.19. Virtuagym
9.2.20. Zwift, Inc.
9.2.21. Technogym S.p.A.
9.2.22. Asana Rebel GmbH
9.2.23. Viome Inc.
9.2.24. Mirror (Lululemon Athletica Inc.)
9.2.25. Peloton Interactive, Inc
9.2.26. Other Market Players
AI in Fitness and Wellness Market By Type-
AI in Fitness and Wellness Market By Application-
AI in Fitness and Wellness Market By End User-
AI in Fitness and Wellness Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
