AI: An engine for growth

Growth opportunities are hard to come by without significant investment, but artificial intelligence (AI) is a self-running engine for growth in healthcare. According to Accenture analysis, when combined, key clinical health AI applications can potentially create $150 billion in annual savings for the US healthcare economy by 2026.

AI in health represents a collection of multiple technologies enabling machines to sense, comprehend, act and learn1 so they can perform administrative and clinical healthcare functions. Unlike legacy technologies that are only algorithms/ tools that complement a human, health AI today can truly augment human activity.

With immense power to unleash improvements in cost, quality and access, AI is exploding in popularity. Growth in the AI health market is expected to reach $6.6 billion by 2021—that’s a compound annual growth rate of 40 percent. In just the next five years, the health AI market will grow more than 10x2.

The AI health market is seeing explosive growth

1Accenture; “AI is the Future of Growth”

2Frost & Sullivan

Acquisitions of AI startups are rapidly increasing while the health AI market is set to register an explosive CAGR of 40% through 2021.


2014 Health AI Market Size


2021 Health AI Market Size

AI thinks and pays for itself

AI represents a significant opportunity for industry players to manage their bottom line in a new payment landscape, while capitalizing on new growth potential. To better understand the savings potential of AI, Accenture analyzed a comprehensive taxonomy of 10 AI applications with the greatest near-term impact in healthcare.

The assessment defined the impact of each application, likelihood of adoption and value* to the health economy. The top three applications that represent the greatest near-term value are robot-assisted surgery ($40 billion), virtual nursing assistants ($20 billion) and administrative workflow assistance ($18 billion). As these and other AI applications gain more experience in the field, their ability to learn and act will continually lead to improvements in precision, efficiency and outcomes.

Top 10 AI Applications
  • Robot-Assisted Surgery** $40B
  • Virtual Nursing Assistants $20B
  • Administrative Workflow Assistance $18B
  • Fraud Detection $17B
  • Dosage Error Reduction $16B
  • Connected Machines $14B
  • Clinical Trial Participant Identifier $13B
  • Preliminary Diagnosis $5B
  • Automated Image Diagnosis $3B
  • Cybersecurity $2B

TOTAL = ~$150B

Source: Accenture analysis

* ”Value” is the estimated potential annual benefits for each application by 2026.

** Orthopedic surgery specific

AI is becoming the new OS

To be positioned to take full advantage of new AI capabilities, Accenture suggests focusing on:

WORKFORCE. The nature of work and employment is rapidly changing1 and will continue to evolve to make the best use of both humans and AI talent. For example, AI offers a way to fill in gaps amid the rising labor shortage in healthcare. AI has the power to alleviate burden on clinicians and give workers tools to do their jobs better.

INSTITUTIONAL READINESS. To realize greater value from AI, healthcare players can incorporate AI expertise in their organization’s structure and governance. They also should build an AI-smart workforce and culture that will use AI to enhance efficiency, quality and outcomes.

CARE REACH. AI can magnify care reach by integrating health data across platforms. However, as new technology is introduced, various data sources must be connected to enable a seamless experience for patients.

SECURITY. Parties in the ecosystem will need to work together in an ethical way, and be secure in how they manage critical information on patients.

1Accenture; “Digital Health Tech Vision 2016: Liquid Workforce”

AI can Address Unmet Clinical Demand - 20% Estimated unmet demand addressable via AI

Source: Accenture analysis. Graph is not to scale and is illustrative

Matthew Collier

Sr. Managing Director – Accenture Strategy, Health

Richard Fu

Senior Manager – Strategy, Health


Accenture 2019 Digital Health Consumer Survey
Person-centered segmentation

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