A comprehensive study conducted by Deloitte during the summer of 2024 reveals that Artificial Intelligence (AI) and Generative AI (GenAI) are fundamentally transforming the medical technology sector, offering significant value across various business functions[1].
Current Impact and Value Realization
The research, which surveyed 85 medtech leaders, demonstrates that AI implementation is already showing concrete results. Notably, 42% of executives reported benefits in product development, while 35% saw improvements in IT and cybersecurity functions[1]. The adoption rate is remarkable, with 57% of surveyed organizations either implementing or scaling GenAI use cases across different departments[1].
Financial Implications
The financial impact of AI implementation is particularly striking. Medtech companies could achieve cost efficiencies ranging from 6% to 12% of their total revenue within the next two to three years[1]. For large medtech companies with revenues between $20 billion and $26 billion, this translates to potential savings of $1.2 billion to $3.2 billion[1].
Functional Benefits Across Departments
In product development, AI is being utilized for concept design and prototyping, while GenAI assists in summarizing scientific literature and drafting trial documents. IT departments are leveraging GenAI for code generation and data management processes, including meta labeling and data anonymization[1].
Commercial operations are seeing improvements through AI-driven sales analysis and customer data interpretation, leading to better engagement recommendations and improved conversion rates. The supply chain benefits from automated supplier checks and optimized inventory management, while financial departments gain from enhanced decision-making capabilities through AI-powered scenario analysis[1].
Cost Efficiency Breakdown
The study provides detailed insights into potential cost savings across different areas:
– Selling, General, and Administrative (SG&A) costs could see reductions of 7% to 19%
– Cost of Goods Sold (COGS) might decrease by 5% to 12%
– R&D costs could be reduced by up to 20%[1]
Implementation Strategy
Success in AI implementation requires a comprehensive approach. Deloitte recommends six key building blocks for maximizing AI value:
1. Strategic Blueprint Development: Companies need to align AI investments with business goals and identify high-value opportunity areas
2. Operating Structure Creation: Establishing AI Centers of Excellence to manage investments and capabilities
3. Value Realization Focus: Implementing systems to track and communicate AI-driven benefits
4. Technology and Scaling Capabilities: Building robust enterprise architecture for AI deployment
5. New Working Methods: Fostering AI adoption through training and demonstrating value
6. Responsible AI Use: Establishing ethical guidelines and governance frameworks[1]
Future Outlook
The medical technology industry stands at a crucial turning point. The integration of AI and GenAI is no longer optional but essential for maintaining competitiveness. Companies must adopt a „string-of-pearls“ approach, integrating multiple AI workflows with existing systems to transform entire processes[1].
Industry Examples
Real-world applications are already showing impressive results. Siemens Healthineers developed an AI-powered digital asset management system that saved approximately €3.5 million in digital asset procurement. Companies like Meticuly are using AI with 3D printing to create custom medical implants in just 2-7 days, while Johnson and Johnson has transformed its HR operations using AI-driven models for employee retention and development[1].
The transformation of the medtech industry through AI and GenAI represents a fundamental shift in how medical technology companies operate, innovate, and deliver value. As these technologies continue to evolve, their impact is expected to grow, making early adoption and strategic implementation crucial for future success.
Source:
[1] us-lshc-ai-readiness-assessment-in-medtech-1.pdf https://ppl-ai-file-upload.s3.amazonaws.com/web/direct-files/21436693/580c7792-b2fb-4853-82de-92cc82539e26/us-lshc-ai-readiness-assessment-in-medtech-1.pdf
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