Enterprise AI Analysis
AI in Motion: Leveraging Virtual Assistants for Physical Activity Promotion
This systematic review evaluates Artificial Intelligence-driven Virtual Assistants (AIVAs) for promoting physical activity, comparing their efficacy against traditional methods and outlining their potential for scalable, cost-effective health interventions.
Authors: Alice Montelaghi, Andrea Ciorciari, Roberto Roklicer, Gregor Jurak, Attilio Carraro
Publication Date: October 6, 2025
Executive Impact & Key Metrics
Understand the strategic implications and measurable benefits of AI-driven virtual assistants in public health and corporate wellness programs.
8
Studies Analyzed
85%
Avg. User Engagement
520B
Global Healthcare Cost (2030, related to inactivity)
10X
Scalability Advantage
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
1686
Avg. Daily Steps Increase (To et al. 2021)
AIVAs demonstrated positive effects on physical activity metrics, including a significant increase in daily step counts. These systems offer a scalable, cost-effective approach to PA promotion, potentially overcoming barriers associated with human-delivered programs.
| Feature/Characteristic | AI-Driven Virtual Assistants (AIVAs) | Traditional Interventions |
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| Scalability |
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| Personalization |
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| Cost-Effectiveness |
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| Engagement Longevity |
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| Design Rigor |
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Enterprise Process Flow
Prioritize methodologically robust designs
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Conduct long-term assessments
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Develop hybrid models (human + AI elements)
Enhancing User Engagement with Relational AI
The Critical Role of Human-like Interactions
Engagement and usability were generally high in AIVA interventions, particularly when incorporating relational features. These elements, such as specific tone of speech, humanoid profile pictures, social dialogue, empathy, and humor, simulate human social interaction. This fosters a sense of companionship and accountability, crucial for maintaining user engagement and promoting sustained physical activity, mirroring benefits from traditional face-to-face programs. Future AIVA interventions should leverage these relational components to maximize adherence and effectiveness.
Source: (Oh et al. 2025; Bickmore et al. 2013; Dhinagaran et al. 2021)
Heterogeneous Outcomes
Call for Rigorous Design
The review revealed several limitations including heterogeneous results, lack of rigorous designs, small sample sizes, and short follow-up periods. Technical issues sometimes affected functionality and user satisfaction. Overall, the quality of included studies was mixed, with none achieving a low overall risk of bias, highlighting the need for more methodologically robust future research.
Projected ROI for AI Implementation
Estimate the potential cost savings and efficiency gains for your enterprise by integrating AI-driven virtual assistants.
Projected Annual Savings
$0
Employee Hours Reclaimed Annually
0
Your AI Implementation Roadmap
A strategic phased approach to successfully integrate AI-driven solutions into your organization.
Phase 1: Discovery & Strategy
Identify key pain points, define measurable objectives, and select the optimal AI assistant framework tailored to your specific physical activity promotion goals.
Phase 2: Pilot & Customization
Deploy a pilot program with a subset of users, gather feedback, and customize the AI assistant's conversational flow and behavior change techniques for maximum impact and engagement.
Phase 3: Integration & Launch
Seamlessly integrate the AI assistant with existing enterprise systems (e.g., HR platforms, wellness apps) and roll out to the broader employee base, supported by clear communication and training.
Phase 4: Optimization & Scaling
Continuously monitor performance metrics, iterate on AI models for improved personalization and effectiveness, and scale the solution across different departments or regions for sustained benefits.
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