Artificial Intelligence (AI) in Healthcare - Thematic Intelligence
Summary
Triple-digit growth in AI is expected by 2030Artificial intelligence (AI) is a fast-growing industry. GlobalData expects every segment of the AI market to grow over the next decade. According to GlobalData forecasts, the AI market was worth $81.3 billion in 2022. By 2030, it will have grown at a compound annual growth rate (CAGR) of 35.2% to $908.7 billion. AI consulting and support services and AI conversational platforms will drive market growth, bolstered by the adoption and increased interest in generative AI.
Scope
- This report is a thematic brief, which identifies those companies most likely to succeed in a world filled with disruptive threats. Inside, we predict how each theme will evolve and identify the leading and disrupting companies.
- The report covers the artificial intelligence theme.
- GlobalData’s thematic research ecosystem is a single, integrated global research platform that provides an easy-to-use framework for tracking all themes across all companies in all sectors. It has a proven track record of identifying the important themes early, enabling companies to make the right investments ahead of the competition, and secure that all-important competitive advantage.
- Develop and design your corporate strategies through an in-house expert analysis of artificial intelligence by understanding the primary ways in which this theme is impacting the healthcare industry.
- Stay up to date on the industry’s major players and where they sit in the value chain.
- Identify emerging industry trends to gain a competitive advantage.
- Executive Summary
- Players
- Healthcare Challenges
- The Impact of AI on Healthcare’s Challenges
- How AI helps resolve the challenge of drug discovery and development
- How AI helps resolve the challenge of low success rates of clinical trials
- How AI helps resolve the challenge of staff and skills shortages
- How AI helps resolve the challenge of supply chain disruption
- How AI helps resolve the challenge of medical imaging and diagnosis
- The AI Impact Assessment
- Healthcare providers, payors, service providers, and suppliers
- Pharma
- Medical devices
- Barriers to the uptake of generative AI
- Case Studies
- Alto Neuroscience uses AI to develop brain biomarkers
- Nabla uses GPT-3 to power its healthcare assistant platform, Copilot
- Harvard Medical School researchers use AI to turn low-field strength MRI scans into high-resolution brain images
- BenchSci uses AI to map diseases for preclinical drug discovery
- King’s College London researchers create AI-model to predict cancer spread
- AI Timeline
- Market Size and Growth Forecasts
- Signals
- Mergers and acquisitions (M&A)
- Partnerships
- Company filings trends
- Hiring trends
- Social media trends
- AI Value Chain
- Hardware
- Semiconductors
- Cameras
- Sensors and lasers
- Servers
- Storage devices
- Networking equipment
- Edge equipment
- Data management
- Data governance and security
- Data storage
- Data processing
- Data aggregation
- Data integration
- Foundational AI
- Data science
- Machine learning
- 3D modeling
- Knowledge representation and reasoning
- Visualization engines
- Advanced AI capabilities
- Human-AI interaction
- Decision-making
- Motion
- Creation (also known as generative AI)
- Sentience
- Delivery
- Hardware appliance
- Licensed software
- Artificial intelligence as a service
- Companies
- Leading AI adopters in healthcare
- Leading AI vendors
- Specialist AI vendors in healthcare
- Sector Scorecards
- Drug development sector scorecard
- Who’s who
- Thematic screen
- Valuation screen
- Risk screen
- Medical devices sector scorecard
- Who’s who
- Thematic screen
- Valuation screen
- Risk screen
- Glossary
- Further Reading
- GlobalData reports
- Bibliography
- Our Thematic Research Methodology
- About GlobalData
- Contact Us
- List of Tables
- Table 1: Key challenges facing the healthcare sector
- Table 2: Key M&A transactions associated with the AI theme since January 2022
- Table 3: Key M&A transactions associated with the AI theme in healthcare since January 2022
- Table 4: Partnerships
- Table 5: Leading AI adopters in healthcare
- Table 6: Leading AI vendors
- Table 7: Specialist AI vendors in healthcare
- Table 8: Glossary
- Table 9: GlobalData reports
- List of Figures
- Figure 1: Key players in AI in healthcare
- Figure 2: AI will be the most disruptive technology in the next two years in the healthcare sector
- Figure 3: Thematic impact assessment for healthcare providers, payors, service providers, and suppliers
- Figure 4: Thematic impact assessment for pharma
- Figure 5: Generative AI is transforming drug development and discovery
- Figure 6: Thematic impact assessment for medical devices
- Figure 7: Poll respondents can see the potential of generative AI in the medical devices industry
- Figure 8: Barriers to the integration of generative AI in the pharma, medical devices, and healthcare sectors
- Figure 9: Input scan vs. SynthSR high-resolution T1 scans
- Figure 10: The AI story
- Figure 11: The AI market will be worth $908.7 billion by 2030
- Figure 12: Mentions of AI by healthcare companies increased from 2016, peaking in 2021 at 1,737
- Figure 13: AI-related hiring activity across healthcare has increased since the start of the COVID-19 pandemic
- Figure 14: Pharma and medical device companies are active hirers in AI
- Figure 15: AI-related social media activity in healthcare increased since 2020
- Figure 16: The AI value chain - An overview
- Figure 17: The AI value chain - Hardware - semiconductors
- Figure 18: The AI value chain - Hardware - cameras
- Figure 19: The AI value chain - Hardware – sensors and lasers
- Figure 20: The AI value chain - Hardware – servers
- Figure 21: The AI value chain - Hardware – storage devices
- Figure 22: The AI value chain - Hardware – networking equipment
- Figure 23: The AI value chain - Hardware – edge equipment
- Figure 24: The AI value chain - Data management
- Figure 25: The AI value chain - Foundational AI – data science
- Figure 26: The AI value chain - Foundational AI – machine learning
- Figure 27: The AI value chain - Foundational AI – 3D modeling
- Figure 28: The AI value chain - Foundational AI – knowledge representation and reasoning
- Figure 29: The AI value chain - Foundational AI – visualization engines
- Figure 30: The AI value chain - Advanced AI capabilities– human-AI interaction
- Figure 31: The AI value chain - Advanced AI capabilities– decision-making
- Figure 32: The AI value chain - Advanced AI capabilities– motion
- Figure 33: The AI value chain - Advanced AI capabilities– creation
- Figure 34: The AI value chain - Advanced AI capabilities– sentience
- Figure 35: The AI value chain - Delivery
- Figure 36: Who does what in the drug development space?
- Figure 37: Thematic screen - Drug development sector scorecard
- Figure 38: Valuation screen - Drug development sector scorecard
- Figure 39: Risk screen - Drug development sector scorecard
- Figure 40: Who does what in the medical devices space?
- Figure 41: Thematic screen - Medical devices sector scorecard
- Figure 42: Valuation screen - Medical devices sector scorecard
- Figure 43: Risk screen - Medical devices sector scorecard
- Figure 44: Our five-step approach for generating a sector scorecard
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