Australia’s Therapeutic Goods Administration (TGA) says it is “stepping up its efforts” to regulate digital scribes, including those using artificial intelligence technology, following calls for greater oversight of the software as it becomes increasingly prevalent in healthcare settings.

AI scribes typically use large language models (LLMs) to quickly transcribe and summarise discussions between patients and healthcare practitioners.

Some systems are also able to suggest potential treatments, write referral letters, make follow-up phone calls, propose billing opportunities, and draft healthcare plans.

Experts have called for advanced AI scribes to be regulated as medical devices by the TGA, given the sensitive data they handle and their ability to make medical recommendations, as Information Age reported in August.

The TGA announced on Friday it was reviewing AI scribes amid concerns some systems were introducing features “such as diagnostic and treatment suggestions”, which may need to be considered medical devices and thereby formally regulated before being sold or advertised.

While most AI scribes do not include such features yet, a TGA review published in July found software which did propose diagnoses or treatment options were “potentially being supplied in breach of the [Therapeutic Goods] Act”.

The TGA had begun responding to complaints and reports of non-compliance, it said, while also addressing “unlawful advertising and supply” of some AI scribes.

“We may take targeted action in response to alleged non-compliance,” the regulator said.

The TGA did not comment on how many complaints or reports of non-compliance it had received.

The regulator said it encouraged consumers to report concerns through its website.

Australian firms welcome regulatory scrutiny

Australian companies such as Heidi Health and Lyrebird Health have seen significant success in the AI scribe industry, amid competition from smaller providers such as i-scribe and mAIscribe — all of which were contacted for comment.

Heidi Health co-founder and CEO Dr Thomas Kelly told Information Age his team “welcome the TGA’s sharpened compliance focus”.

While Kelly said Heidi did not currently have features which would render it a medical device under the TGA definition, he said the firm would engage with the regulator “if we ever introduce features that give Heidi a therapeutic purpose”.

“Proportionate, risk‑based enforcement protects patients and ensures a level playing field for responsible developers,” he said.

_{Australian AI scribe company Heidi Health says its software does not yet meet the definition of a medical device. Image: Heidi Health / YouTube}

Akuru, the health tech company behind i-scribe, said while its product also did not meet the definition of a medical device, it welcomed “the regulator’s latest focus on taking targeted action” against unregulated products which provided diagnostic advice or treatment suggestions.

“We know the scribing market is crowded, and unfortunately, some solutions do cross that line,” Akuru medical director Dr Emily Powell said in a statement.

“… We welcome wider regulatory guidance that empowers clinicians to make informed decisions about secure, compliant, and appropriate software.”

Adoption ‘running ahead of governance’

University of Queensland associate professor of business information systems Dr Saeed Akhlaghpour, who has studied the use of AI scribes in healthcare, described the TGA’s focus on such technology as “a positive move” given their increasing use.

“Bringing AI scribes under safety and medical-device rules gives patients greater peace of mind, reduces legal uncertainty for clinicians, and offers vendors a clearer, more predictable path to compliance,” he said.

“The reality is that adoption is already running ahead of governance — industry surveys suggest nearly half of Australian doctors are already using, or planning to use, AI scribes.

“That scale of uptake makes timely guardrails essential now, not later.”

Regulators in the United States, European Union, and United Kingdom were also “moving to treat scribe tools that go beyond transcription as clinical technologies, not just productivity aids”, Akhlaghpour said.

_{Akuru, the Australian company behind i-scribe, says it welcomes the TGA’s scrutiny of digital scribe software. Image: i-scribe / Supplied}

Expert calls for ongoing reviews

Australian AI governance expert Dr Kobi Leins — who last month told Information Age she was turned away from a medical practice after not consenting to its use of an AI scribe — said ongoing industry-wide expert reviews and training were needed to maintain public confidence.

“Where the data goes and how it is collected and stored is critical, as implications may be profound if shared with insurers, employers, or others — and in the case of genetic and family related health, may have implications for family members not present,” she said.

Ongoing reviews of AI scribes needed to be triggered when systems were “modified, connected, or repurposed”, said Leins, who called for such reviews to analyse “cybersecurity, AI, ethical, legal, vulnerability, medical and other lenses … to capture the wide range of risks and legal compliance required”.

“Included in that review needs to be a plan for ongoing training of the medical profession as to how to use the tools effectively, including seeking consent and always providing the option to opt out,” she said.

“Ensure independent deep expertise to review, not vendor reviews … and ensure that vendors — like with cybersecurity — have the responsibility to notify of changes to systems to practitioners.”

Healthcare professionals should “regularly assess” digital scribe software before using it, including when software updates may introduce new functionality or change data protection and privacy safeguards, the TGA said in August.

Aside from complying with the TGA’s rules, AI scribes used in healthcare may also need to uphold obligations under laws such as the Privacy Act, Cyber Security Act, and Australian Consumer Law, the regulator added.

Report Overview

The Global AI Search Engine Market size is expected to be worth around USD 73.7 Billion By 2034, from USD 17.3 billion in 2024, growing at a CAGR of 15.6% during the forecast period from 2025 to 2034. In 2024, North America held a dominan market position, capturing more than a 31.9% share, holding USD 5.5 Billion revenue.

The AI search engine market is built around technologies that enable users to find information more intelligently and accurately using machine learning and natural language processing. These solutions not only understand the meaning behind queries but also provide personalized answers that adapt to the user’s context. AI-powered search engines are now core tools for fast, intuitive information access, driving both personal productivity and enterprise workflows.

This market is propelled by the increasing need for personalized and context‑aware search experiences. Improvements in language understanding and generative capabilities enable these systems to interpret complex queries and deliver relevant information with greater precision. In parallel, the explosion of digital content and the demands of decision‑making environments in enterprises and consumers are motivating adoption of AI‑driven search technologies.

Key Insight Summary

• Large Enterprises are the top adopters, holding 64.9% share of the market.
• Natural Language Processing (NLP) is the leading technology segment.
• Cloud deployment dominates with a 65.6% share of total adoption.
• retail & e-commerce emerged as the primary end-use sector, driving demand for AI search engines.

Analysts’ Viewpoint

Investment opportunities abound in enterprise-focused AI search products, cloud-based solutions, industry-specific customizations, and privacy-focused platforms. The sector is attracting funds for agentic AI engines and multi-modal interaction models. Regions like North America and Asia Pacific provide dynamic opportunities due to rapid technology adoption, government-backed innovation, and sizable populations of digital users.

Business benefits realized from AI search adoption include better productivity, increased efficiency in knowledge management, reduced cost in handling vast data, and enhanced customer interactions. Intelligent search engines minimize manual effort, automate document indexing, and allow organizations to respond swiftly to evolving market and customer needs.

The regulatory environment varies regionally but is especially shaped by frameworks such as GDPR and CCPA that govern privacy, user consent, and data protection. Compliance requirements in Europe and North America drive innovation toward secure, transparent, and ethically designed AI search solutions. Privacy-oriented development and algorithmic fairness are increasingly seen as non-negotiable standards, influencing adoption and trust in AI-powered platforms.

Regional Insight

In 2024, North America held a dominant market position, capturing more than 31.9% share and generating USD 5.51 billion revenue in the AI search engine market. The region’s leadership is mainly supported by the rapid digital transformation of enterprises and the strong presence of technology innovators.

Businesses across sectors such as e-commerce, finance, and healthcare are increasingly adopting AI-driven search platforms to deliver faster, more relevant, and personalized results. The high demand for intelligent search solutions that can process natural language queries, analyze unstructured data, and improve decision-making has positioned North America at the forefront of this industry.

The leadership of North America is also reinforced by the widespread integration of advanced AI models, including natural language processing and generative AI, into enterprise applications. Strong investment activity in artificial intelligence, combined with robust cloud infrastructure, has accelerated the deployment of AI-powered search solutions across organizations.

Emerging Trends

Growth Factors

Key Market Segments

By Organization Size

By Technology

• Machine Learning
• Natural Language Processing (NLP)
• Generative AI
• Computer Vision
• Other

By Deployment

By End Use

• BFSI
• Media & Entertainment
• Healthcare
• IT & Telecom
• Retail & E-commerce
• Travel & Hospitality
• Manufacturing
• Education
• Others

Regional Analysis and Coverage

• North America
• Europe
  • Germany
  • France
  • The UK
  • Spain
  • Italy
  • Russia
  • Netherlands
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • South Korea
  • India
  • Australia
  • Singapore
  • Thailand
  • Vietnam
  • Rest of Latin America
• Latin America
  • Brazil
  • Mexico
  • Rest of Latin America
• Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE
  • Rest of MEA

Top Use Cases

Customer Insight

Driver Factor

Personalization Enhances Relevance

The main driver in the AI search engine sector is their ability to personalize results based on individual user data. AI search engines use advanced techniques like natural language processing and machine learning to understand the intent behind each query, surfacing results that match a user’s habits, location, and search history. For instance, a user asking for restaurant options in their city receives listings tailored precisely to their preferences, time of day, and even dietary restrictions.

Personalized search means users get information that is truly relevant, not just a list of generic results. This shift toward individualized search experiences leads users to rely on AI engines for more complex and ambiguous questions, making these tools an essential part of modern information-seeking behavior.

Restraint Factor

Growing Privacy Concerns

One of the clearest limiting factors for AI search engines comes from mounting privacy concerns. AI-powered systems often require extensive access to user data so they can tailor those responses and improve results. However, handling large sets of personal information raises worries about how data is collected, stored, and used.

Public awareness and new regulations, such as GDPR and CCPA, have created hurdles for providers of AI search engines. These rules mandate strict data security protocols and greater transparency about data use. As a result, some innovations in personalization are held back, and users may hesitate to trust or adopt these new search technologies when privacy feels compromised.

Opportunity Analysis

Expanding into Voice and Visual Search

A standout opportunity in the AI search engine space is expansion into voice and visual search. As technology evolves, users increasingly expect to find information without typing, using voice assistants or taking a quick picture. Incorporating natural language and image recognition allows AI search platforms to understand queries in a more human way, whether spoken or visual.

This new direction offers a richer, more accessible experience for users, making it easier to search and get contextual results in daily life. Companies that invest in multi-modal search – where spoken words, images, or even video can guide search – are positioned to shape the future of user interaction and engagement.

Challenge Analysis

Competing with Established Search Leaders

One of the major challenges for new AI search engines is breaking the dominance of established traditional engines, especially when users are deeply accustomed to platforms like Google. Building brand recognition and user trust takes time, especially when established competitors offer proven reliability and vast resources.

Additionally, creating technically robust systems able to interpret ambiguous or complex queries requires continuous innovation. Gaining a foothold means not only outperforming competitors on accuracy and relevance but also convincing people to try unfamiliar tools. This is compounded by the need for substantial investment in infrastructure and expertise, which further raises the barrier for newcomers.

Competitive Analysis

In the AI search engine market, leading enterprise technology providers such as SAP SE, Amazon Web Services, Salesforce, and Google LLC play a central role. Their focus lies in integrating AI-driven search functions into enterprise systems and cloud platforms. These companies leverage their vast customer base and advanced cloud ecosystems to deliver scalable search solutions.

Another group of influential players includes IBM Corporation, Zeta Global Corp., and Adobe, who emphasize personalization and data-driven decision-making in search technologies. IBM brings expertise in natural language processing and enterprise AI, while Adobe integrates AI search into content management systems. Zeta Global enhances customer engagement by using AI-powered insights.

Additionally, Microsoft, NVIDIA Corporation, and Oracle contribute significantly to market innovation. Microsoft strengthens the market with AI-powered tools within its productivity ecosystem, while NVIDIA accelerates AI search capabilities with its high-performance GPUs. Oracle integrates AI into its database and enterprise applications to support more intelligent information retrieval.

Top Key Players in the Market

• SAP SE
• Amazon Web Services, Inc.
• Salesforce, Inc.
• Google LLC
• IBM Corporation
• Zeta Global Corp.
• Adobe
• Microsoft
• NVIDIA Corporation
• Oracle

Recent Developments

• In July 2025, Google LLC launched AI Mode in the UK, powered by Gemini 2.5. It delivers conversational answers instead of long lists of links, supports complex queries, and keeps context for follow-up questions, making search more natural and precise.
• In March 2025, One 97 Communications Limited partnered with Perplexity AI, Inc. to bring AI-driven search to the Paytm app. The integration improves accessibility in local languages and provides real-time insights, helping users make informed financial decisions and boosting digital inclusion.
• In October 2024, Meta Platforms Inc. started building its own AI-based search engine with a dedicated web crawler. Linked with Meta AI across its platforms, it provides real-time conversational answers and reduces reliance on external search providers, strengthening its independence in the search ecosystem.

Report Scope