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Artificial Intelligence in Healthcare Market to Reach USD

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Artificial Intelligence in Healthcare Market

Mordor Intelligence has published a new report on the Artificial Intelligence in Healthcare Market offering a comprehensive analysis of trends, growth drivers, and future projections.
Introduction

According to a 2025 report on AI in healthcare market by Mordor Intelligence, the market is estimated at USD 39.92 billion in 2025 and is projected to reach USD 196.91 billion by 2030, growing at a CAGR of 37.60 percent during the forecast period.

The artificial intelligence in the healthcare market [https://www.mordorintelligence.com/industry-reports/artificial-intelligence-in-healthcare-market?utm_source=abnewswire] is witnessing rapid growth as hospitals, pharmaceutical companies, and healthcare providers increasingly adopt AI tools to improve patient care and operational efficiency. AI is used for a range of applications including diagnostics, imaging analysis, drug discovery, virtual assistants, and patient management.

Key Market Trends

AI in Diagnostics and Imaging

AI tools are widely used to analyze medical images such as X-rays, MRIs, and CT scans. Hospitals and diagnostic centers are adopting AI-powered imaging solutions to detect diseases like cancer, neurological conditions, and cardiovascular diseases with higher accuracy and speed. This reduces diagnostic errors and supports clinicians in providing timely treatment.

Use of AI in Drug Discovery and Development

Pharmaceutical companies are leveraging AI platforms to identify new drug candidates, analyze molecular structures, and predict drug responses. AI is helping reduce the time and cost involved in drug development by accelerating research, screening compounds efficiently, and supporting clinical trial processes.

Growth of Virtual Health Assistants and Chatbots

AI-based virtual assistants are being used in hospitals and clinics for appointment scheduling, medication reminders, answering patient queries, and post-discharge follow-ups. This trend is helping healthcare providers reduce administrative workloads and improve patient engagement and satisfaction.

Application of AI in Personalized Medicine

AI enables analysis of patient-specific data including genetic information, medical history, and lifestyle factors to recommend tailored treatment plans. This is supporting the growth of personalized medicine, especially in oncology, where targeted therapies are crucial for effective treatment outcomes.

Adoption of AI for Administrative Workflow Automation

Hospitals and healthcare providers are using AI to automate administrative tasks such as billing, claim processing, and patient data management. This trend is helping reduce operational costs, minimize errors in records, and improve workflow efficiency across departments.

Market Segmentation

By Technology

Machine Learning, Deep Learning, NLP, Computer Vision, Generative AI/Foundation Models, Reinforcement Learning, Others

These technologies form the backbone of AI healthcare tools. Machine learning and deep learning power predictive analytics and image interpretation, while NLP supports automated documentation and clinical decision support. Emerging technologies like generative AI and foundation models which are expanding at roughly 48% CAGR represent the fastest-growing tech area.

By Application

Robotassisted Surgery, Virtual Assistants, Precision & Personalized Medicine, Remote patient Monitoring, Fraud Detection, Others

AI is applied across care delivery and support systems. It’s used in robotic surgery, intelligent scheduling assistants, and automated billing workflows. Diagnostic imaging remains a dominant use case, with AI helping analyze scans and track disease progression. AI also supports clinical trials with data management, and aids in fraud detection and cybersecurity in patient records

By Offering

Hardware, Software, Services

Offerings in AI healthcare span physical devices, digital tools, and consultancy/support services. Software, which includes AI platforms and specialized applications, holds a significant market share given hospitals’ reliance on digital diagnostics, workflow optimization, and predictive analytics.

By End User

Hospitals & Healthcare Providers, Patients, Pharmaceutical & Biotechnology Companies, Healthcare Payers, Others

This segmentation captures the diverse customer base for AI solutions. Hospitals and providers make up the bulk of users for diagnostic or workflow tools. Patients benefit indirectly via virtual health apps or monitoring. Pharma and biotech firms use AI for drug discovery and trial enhancement. Payers leverage AI in claims processing, fraud detection, and cost management.

By Geography

North America, Europe, AsiaPacific, Middle East & Africa, South America

Geographic segmentation highlights regional differences: North America leads due to its healthcare infrastructure and investment capacity, while AsiaPacific is identified as the fastest-growing due to rising digital adoption and government-backed health tech initiatives

Key Players

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IBM Corporation A leading AI healthcare provider, IBM offers robust diagnostic and analytics solutions such as the Watson Health platform that assist hospitals and clinics in decision support, oncology, and imaging workflows.

*
Google LLC (Alphabet) Through its Google Health and DeepMind divisions, Google is developing AI-enabled medical imaging tools and predictive health models. Its efforts include diabetic retinopathy detection and cardiology risk prediction, leveraging advanced AI algorithms.

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NVIDIA Corporation NVIDIA delivers critical AI infrastructure including GPUs and deeplearning frameworks that support healthcare AI applications in diagnostics and image processing. Healthcare institutions rely on hardware acceleration for largescale AI deployment.

*
Microsoft Corporation Microsoft provides AI services integrated into Azure and its healthcare cloud, supporting predictive insights, imaging analysis, and seamless EHR integration for clinician support

Conclusion

The AI in the healthcare market is experiencing strong growth, supported by the increasing demand for diagnostic accuracy, efficient hospital workflows, and personalized care solutions. The use of AI in diagnostics, imaging, drug discovery, and patient management is expected to rise further as hospitals and pharmaceutical companies seek cost-effective, data-driven decision-making tools.

North America will continue to lead in terms of market share, while Asia-Pacific will emerge as a key growth region due to its expanding healthcare infrastructure and government initiatives in digital health. Key players are focusing on enhancing their AI capabilities through continuous investment in research, partnerships with healthcare providers, and expanding AI applications in various medical fields.

Get more insights: https://www.mordorintelligence.com/industry-reports/artificial-intelligence-in-healthcare-market?utm_source=abnewswire

Industry Related Reports

Artificial Intelligence in Medicine Market: [https://www.mordorintelligence.com/industry-reports/artificial-intelligence-in-medicine-market?utm_source=abnewswire] The Artificial Intelligence (AI) in Healthcare Market report is segmented by Application Type (Medical Administration and Support, Patient Management, Research and Development, Other Applications), by Type (Hardware, Software, Services), and by Geography (North America, Europe, Asia-Pacific, Latin America, Middle East and Africa). The report offers market forecasts and size in value (USD) for all the above segments.

North America Artificial Intelligence in Healthcare Market: The Artificial Intelligence in Healthcare Market North America report segments the industry into by Technology (Natural Language Processing (NLP), and more), by Application (Robot-assisted Surgery, and more), by Offering (Hardware, Software, Services), by End User (Healthcare Payers, and more), and by Geography (United States, and more).

For More information: https://www.mordorintelligence.com/industry-reports/north-america-artificial-intelligence-in-healthcare-market?utm_source=abnewswire

AI In Medical Billing Market: [https://www.mordorintelligence.com/industry-reports/ai-in-medical-billing-market?utm_source=abnewswire] The AI in Medical Billing Market report segments the industry into by Deployment (Cloud, On-Premises), by Applications (Automated Billing and Documentation, Claims Processing, Fraud Detection, Other Applications), by End Users (Hospitals and Clinics, Healthcare Payers, Ambulatory Surgical Centers, Other End Users), and by Geography (North America, Europe, Asia, Australia and New Zealand, Latin America, Middle East and Africa).

About Mordor Intelligence: Mordor Intelligence is a trusted partner for businesses seeking comprehensive and actionable market intelligence. Our global reach, expert team, and tailored solutions empower organizations and individuals to make informed decisions, navigate complex markets, and achieve their strategic goals. With a team of over 550 domain experts and on-ground specialists spanning 150+ countries, Mordor Intelligence possesses a unique understanding of the global business landscape. This expertise translates into comprehensive syndicated and custom research reports covering a wide spectrum of industries, including aerospace & defense, agriculture, animal nutrition and wellness, automation, automotive, chemicals & materials, consumer goods & services, electronics, energy & power, financial services, food & beverages, healthcare, hospitality & tourism, information & communications technology, investment opportunities, and logistics.

For any inquiries or to access the full report, please contact:media@mordorintelligence.com https://www.mordorintelligence.com/

Media Contact
Company Name: Mordor Intelligence Private Limited
Contact Person: Jignesh Thakkar
Email:Send Email [https://www.abnewswire.com/email_contact_us.php?pr=artificial-intelligence-in-healthcare-market-to-reach-usd-19691-billion-by-2030-driven-by-diagnostics-and-imaging-applications]
Phone: +1 617-765-2493
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City: Hyderabad
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Country: India
Website: https://www.mordorintelligence.com/

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5 Ways CFOs Can Upskill Their Staff in AI to Stay Competitive

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12 minutes ago

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July 7, 2025

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Chief financial officers are recognizing the need to upskill their workforce to ensure their teams can effectively harness artificial intelligence (AI).

According to a June 2025 PYMNTS Intelligence report, “The Agentic Trust Gap: Enterprise CFOs Push Pause on Agentic AI,” all the CFOs surveyed said generative AI has increased the need for more analytically skilled workers. That’s up from 60% in March 2024.

“The shift in the past year reflects growing hands-on use and a rising urgency to close capability gaps,” according to the report.

The CFOs also said the overall mix of skills required across the business has changed. They need people who have AI-ready skills: “CFOs increasingly need talent that can evaluate, interpret and act on machine-generated output,” the report said.

The CFO role itself is changing. According to The CFO, 27% of job listings for chief financial officers now call for AI expertise.

Notably, the upskill challenge is not limited to IT. The need for upskilling in AI affects all departments, including finance, operations and compliance. By taking a proactive approach to skill development, CFOs can position their teams to work alongside AI rather than compete with it.

The goal is to cultivate professionals who can critically assess AI output, manage risks, and use the tools to generate business value.

Among CEOs, the impact is just as pronounced. According to a Cisco study, 74% fear that gaps in knowledge will hinder decisions in the boardroom and 58% fear it will stifle growth.

Moreover, 73% of CEOs fear losing ground to rivals because of IT knowledge or infrastructure gaps. One of the barriers holding back CEOs are skills shortages.

Their game plan: investing in knowledge and skills, upgrading infrastructure and enhancing security.

Here are some ways companies can upskill their workforce for AI:

Ensure Buy-in by the C-Suite

  • With leadership from the top, AI learning initiatives will be prioritized instead of falling by the wayside.
  • Allay any employee concerns about artificial intelligence replacing them so they will embrace the use and management of AI.

Build AI Literacy Across the Company

  • Invest in AI training programs: Offer structured training tailored to finance to help staff understand both the capabilities and limitations of AI models, according to CFO.university.
  • Promote AI fluency: Focus on both technical skills, such as how to use AI tools, and conceptual fluency of AI, such as understanding where AI can add value and its ethical implications, according to the CFO’s AI Survival Guide.
  • Create AI champions: Identify and develop ‘AI champions’ within the team who can bridge the gap between finance and technology, driving adoption and supporting peers, according to Upflow.

Integrate AI Into Everyday Workflows

  • Start with small, focused projects such as expense management to demonstrate value and build confidence.
  • Foster a culture where staff can explore AI tools, automate repetitive tasks, and share learnings openly.

Encourage Continuous Learning

Make learning about AI a continuous process, not a one-time event. Encourage staff to stay updated on AI trends and tools relevant to finance.

  • Promote collaboration between finance, IT, and other departments to maximize AI’s impact and share best practices.

Tap External Resources

  • Partner with universities and providers: Tap into external courses, certifications, and workshops to supplement internal training.
  • Consider tapping free or low-cost resources, such as online courses and AI literacy programs offered by tech companies (such as Grow with Google). These tools can provide foundational understanding and help employees build confidence in using AI responsibly.

Read more:

CFOs Move AI From Science Experiment to Strategic Line Item

3 Ways AI Shifts Accounts Receivable From Lagging to Leading Indicator

From Nice-to-Have to Nonnegotiable: How AI Is Redefining the Office of the CFO



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Real or AI: Band confirms use of artificial intelligence for its music on Spotify

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1 hour ago

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July 7, 2025

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The Velvet Sundown, a four-person band, or so it seems, has garnered a lot of attention on Spotify. It started posting music on the platform in early June and has since released two full albums with a few more singles and another album coming soon. Naturally, listeners started to accuse the band of being an AI-generated project, which as it now turns out, is true.

The band or music project called The Velvet Sundown has over a million monthly listeners on Spotify. That’s an impressive debut considering their first album called “Floating on Echoes” hit the music streaming platform on June 4. Then, on June 19, their second album called “Dust and Silence” was added to the library. Next week, July 14, will mark the release of the third album called “Paper Sun Rebellion.” Since their debut, listeners have accused the band of being an AI-generated project and now, the owners of the project have updated the Spotify bio and called it a “synthetic music project guided by human creative direction, and composed, voiced, and visualized with the support of artificial intelligence.”

It goes on to state that this project challenges the boundaries of “authorship, identity, and the future of music itself in the age of AI.” The owners claim that the characters, stories, music, voices, and lyrics are “original creations generated with the assistance of artificial intelligence tools,” but it is unclear to what extent AI was involved in the development process.

The band art shows four individuals suggesting they are owners of the project, but the images are likely AI-generated as well. Interestingly, Andrew Frelon (pseudonym) claimed to be the owner of the AI band initially, but then confirmed that was untrue and that he pretended to run their Twitter because he wanted to insert an “extra layer of weird into this story,” of this AI band.

As it stands now, The Velvet Sundown’s music is available on Spotify with the new album releasing next week. Now, whether this unveiling causes a spike or a decline in monthly listeners, remains to be seen. 



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How to Choose Between Deploying an AI Chatbot or Agent

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2 hours ago

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July 7, 2025

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In artificial intelligence, the trend du jour is AI agents, or algorithmic bots that can autonomously retrieve data and act on it.

But how are AI agents different from AI chatbots, and why should businesses care?

Understanding how they differ can help businesses choose the right solution for the right job and avoid underusing or overcomplicating their AI investments.

An AI chatbot or assistant is a program that uses natural language processing to interact with users in a conversational way. Think of ChatGPT. It can answer questions, guide users and simulate dialogue.

Chatbots only react to prompts. They don’t act on their own or carry out multistep goals. They are helpful and conversational but ultimately limited to what they’re asked.

An AI agent goes a step further. Like a chatbot, it can understand natural language and interact conversationally. But it also has autonomy and can complete tasks. It is proactive.

Instead of just replying, an AI agent can make decisions, take actions across systems, plan and carry out multistep processes, and learn from past interactions or external data.

For example, imagine a travel platform. An AI chatbot might help a user plan their travel itinerary. An AI agent, on the other hand, could do more, such as:

  • Understand the request, such as booking a flight to Los Angeles.
  • Search multiple airline sites.
  • Compare flight options based on user preferences.
  • Book the flight.
  • Send a confirmation email.

All of this could happen without the user needing to click through a series of links or speak to a human agent. AI agents can be embedded in customer service, HR systems, sales platforms and the like.

Read also: Understanding the Difference Between AI Training and Inference

Why Businesses Should Care

Knowing the difference can help a business plan more strategically. AI chatbots use less inference than AI agents and therefore are more cost-effective. Moreover, businesses can use AI chatbots and AI agents for very different outcomes.

AI chatbot use cases include the following:

  • Customer service
  • Data retrieval
  • Planning and analysis
  • Basic IT support
  • Conversation
  • Writing documents
  • Code generation

AI agent use cases include the following:

  • Automated checkout
  • Automated content curation
  • Travel and reservation execution tasks
  • Shopping and payment processing

AI chatbots and AI agents both use natural language and large language models, but their functions are different. Chatbots are answer machines while agents are action bots.

For businesses looking to improve how they serve customers, streamline operations or support employees, AI agents offer a new level of power and flexibility. Knowing when and how to use each tool can help companies make smarter AI investments.

To choose between deploying an AI chatbot or AI agent, consider the following:

  • Budgets: AI chatbots are cheaper to run since they use less inference.
  • Complexity of use case: For straightforward tasks, use a chatbot. For tasks that need multistep coordination, use an AI agent.
  • Skilled talent: Assess the IT team’s ability to handle chatbots versus agents. Chatbots are easier to deploy and update. AI agents require more advanced machine learning, natural language processing and other skills.

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