AI discovery in 2025 is increasingly complex, shaped by a variety of large language models (LLMs) that cater to distinct industries and user intents. Understanding which platform dominates specific verticals and how users interact with them is critical for brands seeking visibility and influence in this evolving search ecosystem.
Overview of Leading LLM Growth in 2025
Throughout 2025, leading LLM platforms exhibited markedly different growth rates, signaling distinctive roles and user preferences:
ChatGPT experienced steady 3x growth, maintaining dominance as a broad discovery tool. Meanwhile, Microsoft’s Copilot surged dramatically with 25x growth, demonstrating widespread adoption within enterprise workflows. Anthropic’s Claude grew 13x, carving a niche in deep analytic and strategic tasks. Conversely, Perplexity and Gemini showed minimal growth, reflecting more specialized use cases or attribution challenges.
“The diversity in LLM growth patterns reflects varying professional demands — from operational efficiency to rigorous analysis,” noted digital AI strategist Dr. Helen Montague.
Copilot’s Ascendancy Inside Enterprise Workflows
Copilot’s rapid expansion is most pronounced in business-to-business (B2B) sectors where Microsoft tools are ubiquitous. Key industries include SaaS, education, and finance, where users prefer seamless, embedded AI assistance over switching platforms.
In SaaS, Copilot grew 21x compared to ChatGPT’s 2x. Its integration in Microsoft Excel, Word, and Teams allows professionals to interpret and synthesize data in place, enhancing productivity without workflow disruption.
Educational institutions also favor Copilot, with 27x growth thanks to the platform’s alignment with research synthesis and knowledge sharing practices. Finance professionals rely heavily on Copilot’s ability to reconcile reports, financial filings, and datasets directly within trusted environments—a fact underscored by 23x growth.
“Copilot’s embedded approach means professionals don’t just discover information; they execute decisions instantly within familiar tools,” commented finance technology analyst Marcus Liu.
Perplexity’s Unique Position in Finance
Perplexity’s overall growth remains flat, but it retains a significant 24% market share in finance. This sector uniquely prioritizes verifiability and source transparency due to the high stakes of financial decision-making.
By partnering with Benzinga, FactSet, Morningstar, and others, Perplexity offers direct access to authoritative datasets, such as earnings transcripts and SEC filings. Features like Enterprise Finance enable scheduled updates and live data visualizations, reinforcing trust for institutional users.
This contrasts with broader markets where convenience typically trumps citation. In finance, the ability to trace answers back to verified sources is non-negotiable.
“Trustworthiness and auditability are the foundation of financial AI discovery,” stated fintech expert Laura Simmons.
Claude’s Stronghold in Deep Analysis and Strategic Research
Though Claude constitutes only 0.6% of AI discovery traffic, it commands significant influence in specialized professional sectors including publishing, education, finance, and SaaS, with growth rates from 10x to 49x.
What differentiates Claude is its capacity for standalone, deep reasoning. Users upload extensive manuscripts or datasets—such as legacy code or multi-year earnings transcripts—and seek coherent, strategic insights over simple fact-finding.
Claude’s extensive 200,000-token context window supports advanced synthesis and critique unavailable in more workflow-bound models. This positions Claude as a reasoning partner for high-level content evaluation and decision-making.
“For strategic professionals, Claude is invaluable for complex analysis beyond surface-level querying,” remarked AI content analyst Priya Patel.
Gemini’s Attribution Challenges and Invisible AI Discovery
Gemini’s reported traffic shows inconsistent patterns—marked declines in tracked visits in education but growth in e-commerce and SaaS. This paradox likely results from attribution collapse rather than an actual drop in usage.
As Gemini retains users within Google’s ecosystem, AI-assisted search interactions often lack identifiable source clicks. Users may receive comprehensive answers and later perform branded searches, obscuring AI’s role in discovery.
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