{"id":20339,"date":"2025-05-16T14:11:54","date_gmt":"2025-05-16T18:11:54","guid":{"rendered":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/?p=20339"},"modified":"2025-05-20T08:22:51","modified_gmt":"2025-05-20T12:22:51","slug":"20339","status":"publish","type":"post","link":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/ai\/20339.html","title":{"rendered":"Healthcare and Finance Lead AI Adoption in 2025, While Construction Lags Behind"},"content":{"rendered":"\n

A new industry analysis reveals a striking divide in how artificial intelligence is being adopted across sectors in 2025, with healthcare and finance racing ahead while construction, insurance, and real estate struggle to keep pace. The findings come from a comprehensive study by Yijin Hardware<\/a>, which evaluated global industries using a composite \u201cAI engagement score\u201d based on total startup investments, startup count, public interest via Google search data, and the most common applications of AI within each field.<\/p>\n\n\n\n

According to the report, healthcare leads all sectors<\/strong> with an AI engagement score of 100, the highest in the ranking. The sector has seen a staggering $4.2 billion in global AI startup investments<\/strong> and is home to 11,228 active AI startups<\/strong>, the largest number in any single industry. Applications of AI in healthcare are wide-ranging, from image analysis of X-rays and MRIs to clinical trial optimization, administrative workflow automation, and AI-driven drug discovery. The rapid expansion of AI in healthcare reflects both the complexity of medical systems and the potential for transformative efficiencies through automation.<\/p>\n\n\n\n

Trailing just behind is the finance industry<\/strong>, which scored 72.4<\/strong> despite having nearly the same number of startups (11,057) as healthcare. The lower score reflects a more modest investment total of $2.1 billion<\/strong>. AI\u2019s key uses in finance include fraud detection, algorithmic trading, credit risk modeling, and process automation in customer onboarding and compliance. While the finance sector was an early adopter of machine learning and predictive analytics, the disparity in funding compared to healthcare highlights the premium being placed on AI\u2019s role in solving systemic challenges within global health systems.<\/p>\n\n\n\n

Marketing and advertising<\/strong> rounds out the top three, with $1.1 billion in startup funding<\/strong> and a notable 241,000 monthly Google searches related to AI<\/strong> in the field. With an engagement score of 60.9<\/strong>, this industry stands out for its public curiosity and the breadth of startups deploying AI for ad targeting, content generation, campaign performance analysis, and customer segmentation. The explosion of generative AI tools in particular has made marketing one of the fastest-moving industries in terms of AI experimentation and deployment.<\/p>\n\n\n\n

In fourth place is legal services<\/strong>, which earned an AI engagement score of 58.1<\/strong>, with 9,250 AI startups<\/strong> but only $400 million in funding<\/strong>. AI is increasingly used in legal research, contract analysis, and e-discovery, helping law firms and corporate legal departments reduce labor costs and improve accuracy. While investment levels are lower compared to other top-five sectors, the industry\u2019s appetite for automation tools is growing fast.<\/p>\n\n\n\n

The education and e-learning<\/strong> sector ranked fifth with a score of 41.8<\/strong>, buoyed by strong public interest \u2013 nearly 400,000 monthly searches<\/strong> \u2013 and $1.2 billion in startup funding<\/strong> across 4,340 companies<\/strong>. Popular AI use cases include automated grading, intelligent tutoring systems, plagiarism detection, and adaptive learning platforms that personalize content for students. This sector illustrates how AI is penetrating even traditionally slow-to-adapt industries as tools become more accessible and effective.<\/p>\n\n\n\n

On the other end of the spectrum, the construction industry ranked last<\/strong>, with an AI engagement score of 1<\/strong> \u2013 the lowest possible. The sector has just 696 startups<\/strong> globally and has received only $200 million in funding<\/strong>. Despite construction\u2019s vast economic footprint and complex logistics, the sector remains heavily manual, with limited digitization. Some efforts have begun in areas like project scheduling optimization and on-site safety monitoring using AI, but progress remains slow.<\/p>\n\n\n\n

Insurance<\/strong> placed second-to-last, with a score of 5.2<\/strong>. Although the industry logs over 60,000 monthly searches<\/strong> for AI applications, funding levels remain stagnant at $600 million<\/strong>, and there are fewer than 700 AI startups<\/strong> in the space. This highlights a paradox: while insurance is rich in data and theoretically ripe for automation, legacy systems and regulatory complexity have stifled rapid innovation.<\/p>\n\n\n\n

Real estate<\/strong> came in third-lowest, with an AI engagement score of 5.4<\/strong>. The sector, like insurance, has generated $600 million in funding<\/strong> for AI startups and is home to 799 companies<\/strong>. AI uses in this space typically revolve around predictive property valuations, market trend analysis, and smart tenant screening. While public interest is moderate, industry-wide adoption remains limited due to fragmented ownership and conservative operating models.<\/p>\n\n\n\n

Manufacturing<\/strong>, a sector once hailed as the heart of industrial AI, ranks surprisingly low with a score of 9.5<\/strong>. While there\u2019s $900 million in funding<\/strong> and a long history of automation, the limited number of 1,080 AI-specific startups<\/strong> suggests that innovation is concentrated in certain niches like quality control, predictive maintenance, and robotic vision. Analysts note that while manufacturing has embraced robotics, broader AI transformation is slower than expected.<\/p>\n\n\n\n

Finally, agriculture<\/strong> rounds out the bottom five, despite being home to 1,736 AI-focused startups<\/strong> and generating $500 million in funding<\/strong>. With an engagement score of 11.4<\/strong>, the sector shows promise with use cases like pest detection, irrigation optimization, and satellite-driven crop monitoring. However, long deployment cycles and inconsistent data infrastructure remain barriers to mass adoption.<\/p>\n\n\n\n

A spokesperson for Yijin Hardware commented that the study highlights a \u201cgrowing innovation inequality\u201d across sectors, where AI haves and have-nots are diverging rapidly. \u201cThis widening gap isn’t just about efficiency gains \u2013 it represents a fundamental reimagining of how entire sectors function, with early AI adopters positioned to completely redefine market rules while technological laggards face increasingly difficult catch-up challenges.\u201d<\/p>\n\n\n\n

As AI systems become more capable, real-time, and integrated, these early adopters could enjoy lasting structural advantages. Meanwhile, industries failing to invest risk falling further behind\u2014not just in productivity, but in talent acquisition, data readiness, and long-term competitiveness.<\/p>\n\n\n\n

For business leaders, the findings are a call to action. AI transformation is no longer a speculative trend\u2014it is reshaping the industrial landscape. The message is clear: adopt early, or risk irrelevance.<\/p>\n\n\n\n

Learn how AI Agents can supercharge your company’s profits and productivity at TMC’s <\/a>AI Agent Event <\/a>in Sept 29-30, 2025 in DC.<\/em><\/mark><\/strong><\/p>\n\n\n\n

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If you liked this post, you\u2019ll love one of the the leading global business communications and technology events since 1999, the ITEXPO #TECHSUPERSHOW<\/a>, Feb 10-12, 2026 Fort Lauderdale, Florida.<\/p>\n\n\n\n

Don’t forget the collocated MSP Expo<\/a> – just for managed service providers!<\/p>\n\n\n\n

\"\"<\/a><\/figure>\n\n\n\n

Aside from his role as CEO of <\/em>TMC<\/em><\/a> and chairman of <\/em>ITEXPO<\/em><\/a> #TECHSUPERSHOW Feb 10-12, 2026, Rich Tehrani is CEO of RT Advisors<\/a> and a Registered Representative (investment banker) with and offering securities through Four Points Capital Partners LLC <\/a>(Four Points) (Member FINRA\/SIPC). He handles capital\/debt raises as well as M&A. RT Advisors is not owned by Four Points.<\/em><\/p>\n\n\n\n

The above is not an endorsement or recommendation to buy\/sell any security or sector mentioned. No companies mentioned above are current or past clients of RT Advisors.<\/p>\n\n\n\n

The views and opinions expressed above are those of the participants. While believed to be reliable, the information has not been independently verified for accuracy. Any broad, general statements made herein are provided for context only and should not be construed as exhaustive or universally applicable.<\/p>\n","protected":false},"excerpt":{"rendered":"

A new industry analysis reveals a striking divide in how artificial intelligence is being adopted across sectors in 2025, with healthcare and finance racing ahead while construction, insurance, and real estate struggle to keep pace. The findings come from a comprehensive study by Yijin Hardware, which evaluated global industries using a composite \u201cAI engagement score\u201d<\/p>\n","protected":false},"author":44,"featured_media":20340,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[194],"tags":[],"post_mailing_queue_ids":[],"_links":{"self":[{"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/posts\/20339"}],"collection":[{"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/users\/44"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/comments?post=20339"}],"version-history":[{"count":2,"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/posts\/20339\/revisions"}],"predecessor-version":[{"id":20490,"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/posts\/20339\/revisions\/20490"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/media\/20340"}],"wp:attachment":[{"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/media?parent=20339"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/categories?post=20339"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.tmcnet.com\/blog\/rich-tehrani\/wp-json\/wp\/v2\/tags?post=20339"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}