Radar · Industry landscape · the United States
Conversational AI and Chatbots Landscape of the United States 1,548 Conversational AI and Chatbots companies in the United States, in one picture: who is hiring, who is raising money, who founded them, where they are based, what the news is about, which skills employers want and where the research is going. Updated August 2026.
1,548 companies tracked
$13.7B disclosed funding
106 hiring right now
647 events · 24 months
2,218,811 news articles · 12 months
Who leads Conversational AI and Chatbots in the United States Shows 1,548 U.S. Conversational AI firms, highlighting which are hiring, best funded, and most covered; 106 are hiring now and 413 have disclosed a funding round.
Radar
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Filter by funding, headcount, hiring and location, and export the list.
How the Conversational AI and Chatbots ecosystem in the United States grew, 2016–2025 Shows the number of firms founded each year, with a peak of 242 new companies in 2023 and 126 in 2025.
Companies founded / year
new Conversational AI and Chatbots companies in the United States
2016: 96 2017: 89 2018: 93 2019: 94 2020: 110 2021: 79 2022: 102 2023: 242 2024: 199 2025: 126 2016 2025
peak 242 in 2023
Companies raising / year
with a disclosed round that year
2016 2025
peak 91 in 2025
Disclosed funding / year
sum of disclosed rounds (USD)
2016: 277,590,264 2017: 271,600,422 2018: 513,841,656 2019: 690,132,174 2020: 1,149,388,898 2021: 2,459,313,338 2022: 1,828,727,164 2023: 2,015,952,561 2024: 883,696,464 2025: 2,146,943,164 2016 2025
peak $2.5B in 2021
Where Conversational AI and Chatbots companies in the United States are based Lists the cities with the most companies, led by San Francisco (278) and New York City (142).
→ Hub 01
San Francisco
278 Conversational AI and Chatbots companies
45% of the Conversational AI and Chatbots companies across these hubs
278 companies
$2.5B disclosed funding
26 hiring now
Hub 02
New York City
142 Conversational AI and Chatbots companies
23% of the Conversational AI and Chatbots companies across these hubs
142 companies
$2.3B disclosed funding
10 hiring now
Hub 03
Palo Alto
47 Conversational AI and Chatbots companies
8% of the Conversational AI and Chatbots companies across these hubs
47 companies
$2.7B disclosed funding
5 hiring now
Hub 04
Los Angeles
40 Conversational AI and Chatbots companies
6% of the Conversational AI and Chatbots companies across these hubs
40 companies
$77.3M disclosed funding
2 hiring now
Hub 05
Austin
29 Conversational AI and Chatbots companies
5% of the Conversational AI and Chatbots companies across these hubs
29 companies
$149.2M disclosed funding
3 hiring now
Hub 06
Wilmington
28 Conversational AI and Chatbots companies
5% of the Conversational AI and Chatbots companies across these hubs
28 companies
$213.7M disclosed funding
Hub 07
Boston
28 Conversational AI and Chatbots companies
5% of the Conversational AI and Chatbots companies across these hubs
28 companies
$322.3M disclosed funding
2 hiring now
Hub 08
Dover
26 Conversational AI and Chatbots companies
4% of the Conversational AI and Chatbots companies across these hubs
26 companies
$19.6M disclosed funding
5 hiring now
The Conversational AI and Chatbots market map of the United States: what these companies actually do Breaks down product sub‑categories and revenue models, noting that enterprise tech (1,360 firms) and subscription models (1,445 firms) dominate.
Enterprise Tech 1,360 companies · $12.6B raised · 97 hiring Enterprise Software 1,164 companies · $10.4B raised · 86 hiring SaaS 914 companies · $8.8B raised · 56 hiring Artificial Intelligence 386 companies · $9.1B raised · 49 hiring Consumer Digital 287 companies · $2.9B raised · 13 hiring Lead Management 260 companies · $1.3B raised · 10 hiring Live Chat Software 252 companies · $1.1B raised · 20 hiring AI as a Service 242 companies · $6.2B raised · 32 hiring Loneliness Economy 209 companies · $2.5B raised · 6 hiring Lead Generation 185 companies · $388.5M raised · 7 hiring Fintech 148 companies · $1.3B raised · 14 hiring Native AI in Customer Support 143 companies · $5.4B raised · 24 hiring Monetization
How Conversational AI and Chatbots companies make money How many companies earn revenue each way. Plenty use more than one model, so the counts add up to more than the sector.
Subscription 1,445
Advertising 64
Commission on Transaction 55
Fee-For-Service 43
E-Commerce - Service 40
E-Commerce - Product 9
Physical Commerce 7
Licensing 5
Funding, M&A and the deals moving Conversational AI and Chatbots in the United States Counts 647 corporate events over the past two years, including 153 funding rounds, 115 key‑person announcements, and 110 earnings releases.
Funding 153 Leadership 115 Earnings 110 Product 76 M&A 76 Announcement 48 Capital 30 Contracts 15 Layoffs 7 Regulatory 7
Funding Netomi has now raised a total of $217M in total equity funding and is backed by Accenture Ventures, Adobe Ventures, Demis Hassabis, Fin Capital, Gokul Rajaram, Greg Brockman, Henry Kravis, Justin Wexler, Metis Strategy, Mustafa Suleyman, Naver Ventures, Nikesh Arora, Silver Lake Waterman, SLW, and WndrCo. 2026-05-04 M&A SoundHound AI, Inc. (Nasdaq: SOUN) announced on April 21, 2026, a definitive agreement to acquire LivePerson, Inc. (Nasdaq: LPSN). 2026-04-22 Funding Phonely has now raised a total of $16.5M in total equity funding and is backed by Base10 Partners, EngageCX, Etech Global Services, TSA Group, and Y Combinator. 2026-04-18 Funding Gasgoo Munich- Gasgoo has learned that TARS has officially closed a $455 million (roughly 3.1 billion yuan) Pre-A funding round. 2026-04-16 Funding Power management company Claros recently raised $30m in a seed round to fund the development of an integrated voltage regulator – a type of electronic device placed beneath or on a chip to maintain a stable voltage that is meant to reduce power losses – and a direct current power distribution platform. 2026-04-14 Funding Uniphore leads with nearly $985 million in total funding and a $2.5 billion valuation. 2026-04-10 M&A Rezolve announced on April 8 that it would take its offer directly to Commerce.com shareholders. 2026-04-09 Funding Voice AI startup Gnani.ai has raised $10 million in a funding round led by impact investor Aavishkaar Capital, as the company looks to expand its business internationally and improve its R&D capabilities. 2026-03-31 M&A Banzai International, Inc. has reached terms to acquire assets of ConnectAndSell, Inc., a move the company said would add about $15 million in annual revenue and more than double its top line if completed. 2026-03-23 Funding The fresh capital will be used to fund Resemble AI’s expansion into Saudi Arabia and the wider Middle East, enabling the firm to provide infrastructure that can help organisations analyse data locally. 2026-03-18 Mergers and acquisitions Deals from the last 24 months where a Conversational AI and Chatbots company in the United States was the buyer or the one bought, newest first. “Undisclosed” means the price was never published — not that the deal was worth nothing.
Acquirer Target Deal value Status Date SoundHound AI LivePerson $43M Announced 2026-04-27 Rezolve AI Commerce.com undisclosed Announced 2026-04-08 Dblp Sea CowRezolve AI undisclosed Announced 2026-04-02 zendeskForethought AI undisclosed Announced 2026-03-31 banzai internationalConnectAndSell undisclosed Completed 2026-03-27 css corpDirectly undisclosed Announced 2026-03-18
Who is listing, hiring leaders, launching and winning work Provides details on leadership moves, product launches, and customer contract wins within the sector.
Contract wins
17 customer wins · last 24 months
Workforce actions
3 companies cutting roles · last 24 months
Gupshup ~300 roles reported · acquisitions, profitability focus Mar 2026 Artisan ~46 roles reported · cost reduction Mar 2026 Character.ai ~120 roles reported · refocus Aug 2024 Earnings pulse
companies reporting results · last 24 months
7 companies reporting108 company-quarters trackedbeat 23 miss 2 in line 0
Half of these companies grew revenue faster than +0.7% , half slower.
Who is building Conversational AI and Chatbots in the United States Profiles 1,217 founders and CEOs across 763 firms, with Stanford (45 alumni) and Google (35 former employees) most common.
Founders and chief executives 12 of 1,217, from the best-funded companies on this page
→ repeat founder Board Member - Entreprenuer First · Greylock, Inflection AI, ex-PayPal, Fujitsu Software Corporation, Apple Computer \ Stanford University BS 1990…
Co-Founder & COO
Ravi Saraogi
Ex-TeNet · Jaypee University of Information Technology BE 2007
Co-Founder & CEO
Craig Walker
repeat founder Ex-Google Ventures, Co-Founder GrandCentral Communications, Sterling Payot Capital. University of California, Berkeley 1988…
Co-Founder & CTO
Ashwin Sreenivas
Ex-Co-Founder Helia, Palantir Technologies. Stanford University BS 2017, MS 2019
Co-Founder & CEO
Minna Song
Co-Founder Influencers Required. MIT
Ex-Microsoft, NurtureNext, IBM · PSG College of Technology BE 1997
Founder and CEO
David Karandish
Capacity, ex-Varsity Tutors A Nerdy, ex-Forbes Technology Council, Washington University in St. Louis, 2005
Co-Founder & CTO
Vaibhav Nivargi
Ex-Founder ClearStory Data, Aster Data, CalSoft · Pune Institute of Computer Technology BE 2003, Stanford University MS 2007
Ex-CEO CommTech, ADC. Stevens Institute of Technology BE 1984 & MS 1987
Ex-Co-Founder iTouchPoint, Kony, Seranova, Intelligroup.
Co-Founder & Chief Product Officer
Nate Mitchell
Sesame · Ex-Mountaintop Studios, Facebook, Oculus · Dickinson College BS
Co-Founder & CTO
Jithendra Vepa
Ex-Samsung Research & Development India, Philips Research. Andhra University BE 1996, IISc MSc 1999, University of Edinburgh PhD 2004
Where the founders studied
alma mater on record for 317 of 1,217 founders
Stanford University 45
University of California (Berkeley) 29
Harvard University 25
Massachusetts Institute of Technology 23
Harvard Business School 15
Carnegie Mellon University 15
BITS Pilani 15
Columbia University 14
Where they worked before
a previous employer on record for 105 of 1,217 founders
Google 35
Microsoft 17
Amazon 11
Facebook 7
Apple 7
Intel 6
Cisco 4
Boston Consulting Group 4
Founders flagged as repeat founders
of 1,103 founders with a profile on this page
13
carry a repeat-founder flag
flagged as repeat founders 13 no repeat-founder flag 1,090 Women and men among the founders
first names matched for 1,068 of 1,217 founders
10%
of matched founders are women
Inferred from first names, using 119 million people who state their own gender: a first name counts only where at least 20 of them share it and at least 90% of those share the same gender. The other 149 founders go in neither column.
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Who funds Conversational AI and Chatbots in the United States Records 818 funding rounds since 2016 from 1,282 investors, with a typical round size of $3.7 million.
Stage mix · rounds since 2016
Seed & Angel 441
Series A–B 242
Series C+ / PE 72
Grants, debt & other 63
The typical round is $3.7M — half were bigger, half smaller.
The biggest Conversational AI and Chatbots funding rounds in the United States Highlights the largest disclosed round—Inflection’s $1.3 billion Series E—and lists ten other large recent rounds.
Company Round Size When Backers Inflection Series Emega-round $1.3B Jun 2023 Nvidia , Microsoft , CoreWeave +3 more Uniphore Series Emega-round $400M Jan 2022 New Enterprise Associates , March Capital , GoldenArc Capital +4 more Uniphore Series Fmega-round $260M Oct 2025 Nvidia , Snowflake , Databricks +6 more Sesame Series Bmega-round $250M Oct 2025 Sequoia Capital , Spark Capital EliseAI Series Emega-round $250M Aug 2025 Andreessen Horowitz , Bessemer Venture Partners , Sapphire Ventures +1 more Decagon Series Dmega-round $250M Jan 2026 Coatue , Index Ventures , Chemistry VC +11 more Inflection Series D $225M Apr 2022 Greylock Partners , Microsoft , Reid Hoffman +7 more Moveworks Series C $200M Jun 2021 Tiger Global Management , Alkeon Capital Management , Kleiner Perkins +4 more ASAPP Series B $185M May 2020 JC2 Ventures , John Doerr , John Chambers +8 more Capacity Series D $182.4M Sep 2023 Toloka , TVC Capital
Venture round sizes · 2023–2025
<$1M 86
$1–10M 114
$10–50M 45
$50–250M 16
>$250M 4
265 venture rounds with a disclosed amount in the window.
Fresh cheques · last 6 months
What the news says about Conversational AI and Chatbots in the United States Counts 2,218,811 news articles in the last year, most often covering administrative, geopolitical, and international political topics.
News volume
Conversational AI and Chatbots coverage across United States · articles per quarter
2021Q2: 468,156 2021Q3: 489,724 2021Q4: 467,150 2022Q1: 507,766 2022Q2: 499,960 2022Q3: 514,141 2022Q4: 575,398 2023Q1: 605,693 2023Q2: 606,730 2023Q3: 547,042 2023Q4: 511,612 2024Q1: 533,655 2024Q2: 518,142 2024Q3: 503,917 2024Q4: 532,652 2025Q1: 803,710 2025Q2: 552,356 2025Q3: 1,301,382 2025Q4: 289,823 2026Q1: 408,807 2026Q2: 218,799 2021Q2 2026Q2
peak 1,301,382 in 2025Q3 · 2,218,811 articles in the last 12 tracked months
Tone of coverage
share of articles by dominant sentiment (positive / neutral / negative )
2021 2023 2025
Positive-tone share moved 19% → 23%, negative 19% → 28% across 2021–2025.
What the coverage is about The subjects that dominate Conversational AI and Chatbots news in United States. The arrow shows whether each one is being written about more or less than a year ago.
Administrative and political subdivisions 4,331,266 ▲+17% Geopolitical disputes and contested areas 320,234 ▲+30% International and transnational geographic entities 320,066 ▲+30% International political relations 209,169 →+3% Security and defense policies 145,922 ▲+19% International relations and diplomacy 96,251 →-8% Geographic naming conventions and etymology 81,669 ▲+383% Trade policies and agreements 75,484 ▼-26% Human rights advocacy reports 72,271 ▼-26% Political asylum and refugee policies 58,307 ▼-30% Most-covered companies · last 12 months
67 Conversational AI and Chatbots companies here were named in the news over this period.
Prism
Watch Conversational AI and Chatbots coverage in United States as it happens
Prism follows these subjects story by story — which companies are named, what is said about them and how the tone moves.
Momentum
The words getting louder — and quieter Which terms are showing up in more stories than a year ago, and which are fading. The percentage is the change in how many articles mention them.
countries+100% etf trading+142% oil price volatility+125% etfs+145% sector etfs+144% etf products+158% etf structures+151% stablecoin fx impact+45% cannabis policy reform discussions+44% export sanctions+178%
tariff negotiations-39% free trade deals-37% stock price-39% economic slowdown-42% trade enforcement-38%
Conversational AI and Chatbots jobs in the United States: who is hiring and what they ask for Shows 3,846 job postings from 205 employers in 12 months, with median pay $108 k and top skills including Python and AWS.
3,846 postings · last 12 months
5,567 postings tracked overall
205 employers advertising
$108k median advertised salary/yr (n=545)
Demand
The Skills Employers Ask For What Conversational AI and Chatbots employers in the United States put in their job ads. The bar is how many postings ask for it; the arrow shows whether demand grew or shrank against the year before.
python 202 ▲ aws 137 ▲ sql 121 ▲ typescript 104 ▲ kubernetes 95 ▲ react 91 ▲ gcp 86 ▲ excel 83 ▲ salesforce 79 ▲ ai 69 ▲ What level are these roles?
Entry 40
Intern 41
Senior 500
Lead 185
Manager 1,021
What they pay, by level
Manager $128k/yr (n=95) Senior $157k/yr (n=44) Most advertised titles
Virtual Assistant (Work From Home) 77 Customer Service Representative (Work From Home) 41 Ft Customer Support Representative - Work From Home 38 Customer Success Manager 33 Account Executive 32 Senior Lead Compensation Analyst 30 What Conversational AI and Chatbots research in the United States is working on Lists 5,087 U.S. academic papers, of which 3,254 identify opportunities, 454 note common problems, and 275 issue cautions.
How this field talks about itself
United States-affiliated Conversational AI and Chatbots papers (gold) against all published research (grey)
Breakthrough 44.3% · 26.0% 1.7×
Promising 19.7% · 37.1% 0.5×
Descriptive 17.6% · 17.8% ≈ par
Problem-identifying 5.6% · 9.7% 0.6×
Cautionary 5.4% · 4.4% 1.2×
Comparative 4.1% · 3.9% ≈ par
United States-affiliated Conversational AI and Chatbots literature runs 1.7× more “breakthrough” than science at large (44.3% vs 26.0% baseline).
How the work is done
Methods-led 54.5%
Empirical 30.7%
Reviews 8.2%
Theoretical 4.2%
Position pieces 2.4%
How the research reads
90% positive · 7% neutral · 3% negative , across 5,087 papers.
The institutions doing the work · United States
Google 194k Stanford University 162k Carnegie Mellon University 82k Microsoft 59k University of Washington 47k Georgia Institute of Technology 44k ranked by how often their work is cited
Leading researchers · United States-affiliated work
Christopher D. Manning · Tomáš Mikolov · Richard Socher · Greg S. Corrado · Kai Chen · Quoc V. Le · Ilya Sutskever · Jeffrey Pennington
The most-cited breakthroughs
Glove: Global Vectors for Word Representation · 33k cites Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization · 20k cites Efficient Estimation of Word Representations in Vector Space · 18k cites Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics · 14k cites Sequence to Sequence Learning with Neural Networks · 13k cites Common problems researchers identify 405 papers · 7 recurring themes
→ Problems · theme 01
Fundamental NLP Model Issues
80 papers · 19.8% of this block
2022: 980 of every 10,000 papers on this subject 2023: 1,030 of every 10,000 papers on this subject 2024: 833 of every 10,000 papers on this subject 2025: 418 of every 10,000 papers on this subject 2022: 980 of every 10,000 papers on this subject 2023: 1,030 of every 10,000 papers on this subject 2024: 833 of every 10,000 papers on this subject 2025: 418 of every 10,000 papers on this subject ▼ -57% share 2022→2025 share of research on this subject Researchers highlight core challenges in language modeling, explainability, and societal impact of NLP systems.
Natural language processing · Natural language · Natural · Language model
“Explainability for Large Language Models: A Survey”
Problems · theme 02
Representation and Comprehension Gaps
76 papers · 18.8% of this block
2022: 90 of every 10,000 papers on this subject 2023: 102 of every 10,000 papers on this subject 2024: 88 of every 10,000 papers on this subject 2025: 96 of every 10,000 papers on this subject 2022: 90 of every 10,000 papers on this subject 2023: 102 of every 10,000 papers on this subject 2024: 88 of every 10,000 papers on this subject 2025: 96 of every 10,000 papers on this subject ▲ +6% share 2022→2025 share of research on this subject Papers point to difficulties in knowledge representation, metaphor understanding, and consistent interpretation of text.
Representation · Comprehension · Interpretation · Consistency
“Using Texts in Science Education: Cognitive Processes and Knowledge Representation”
Problems · theme 03
Lexical and Negation Limitations
62 papers · 15.3% of this block
2022: 1,436 of every 10,000 papers on this subject 2023: 1,409 of every 10,000 papers on this subject 2024: 1,083 of every 10,000 papers on this subject 2025: 424 of every 10,000 papers on this subject 2022: 1,436 of every 10,000 papers on this subject 2023: 1,409 of every 10,000 papers on this subject 2024: 1,083 of every 10,000 papers on this subject 2025: 424 of every 10,000 papers on this subject ▼ -70% share 2022→2025 share of research on this subject Studies expose weaknesses in handling negation, verb semantics, and lexical diversity across languages.
Negation · Linguistics · Verb · Vocabulary
“Register as a predictor of linguistic variation”
Problems · theme 04
Architectural and Cognitive Shortcomings
53 papers · 13.1% of this block
2022: 450 of every 10,000 papers on this subject 2023: 421 of every 10,000 papers on this subject 2024: 367 of every 10,000 papers on this subject 2025: 455 of every 10,000 papers on this subject 2022: 450 of every 10,000 papers on this subject 2023: 421 of every 10,000 papers on this subject 2024: 367 of every 10,000 papers on this subject 2025: 455 of every 10,000 papers on this subject → +1% share 2022→2025 share of research on this subject Works critique current AI architectures and their inability to mimic human cognition in sentence processing.
Architecture · Applications of artificial intelligence · Cognition · Sentence
“Toward Teleodynamic Architectures in Artificial Intelligence”
Problems · theme 05
Language Acquisition and Semantics
52 papers · 12.8% of this block
2022: 624 of every 10,000 papers on this subject 2023: 647 of every 10,000 papers on this subject 2024: 630 of every 10,000 papers on this subject 2025: 653 of every 10,000 papers on this subject 2022: 624 of every 10,000 papers on this subject 2023: 647 of every 10,000 papers on this subject 2024: 630 of every 10,000 papers on this subject 2025: 653 of every 10,000 papers on this subject ▲ +4% share 2022→2025 share of research on this subject Research flags obstacles in grammar learning, semantic mapping, and cross‑lingual textual similarity.
Language acquisition · Grammar · Vocabulary · Semantics
“SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation”
Problems · theme 06
Generative Model Evaluation Gaps
48 papers · 11.9% of this block
2022: 169 of every 10,000 papers on this subject 2023: 214 of every 10,000 papers on this subject 2024: 131 of every 10,000 papers on this subject 2025: 267 of every 10,000 papers on this subject 2022: 169 of every 10,000 papers on this subject 2023: 214 of every 10,000 papers on this subject 2024: 131 of every 10,000 papers on this subject 2025: 267 of every 10,000 papers on this subject ▲ +58% share 2022→2025 share of research on this subject Authors note insufficient testing frameworks for generative models, especially in specialized domains like health records.
Generative grammar · Language model · Generative model · Data modeling
“Testing and evaluation of generative large language models in electronic health record applications: a systematic review”
Problems · theme 07
Sentiment and Public Opinion Challenges
34 papers · 8.4% of this block
2022: 2,505 of every 10,000 papers on this subject 2023: 2,559 of every 10,000 papers on this subject 2024: 3,074 of every 10,000 papers on this subject 2025: 2,697 of every 10,000 papers on this subject 2022: 2,505 of every 10,000 papers on this subject 2023: 2,559 of every 10,000 papers on this subject 2024: 3,074 of every 10,000 papers on this subject 2025: 2,697 of every 10,000 papers on this subject ▲ +8% share 2022→2025 share of research on this subject Analyses reveal persistent issues in accurately extracting sentiment and opinion from social media content.
Sentiment analysis · Social media · Public opinion · Product
“Sentiment Analysis and Subjectivity”
Cautions 257 papers · 5 recurring themes
→ Cautions · theme 01
Caution on Language Learning Applications
67 papers · 26.1% of this block
2022: 298 of every 10,000 papers on this subject 2023: 314 of every 10,000 papers on this subject 2024: 298 of every 10,000 papers on this subject 2025: 325 of every 10,000 papers on this subject 2022: 298 of every 10,000 papers on this subject 2023: 314 of every 10,000 papers on this subject 2024: 298 of every 10,000 papers on this subject 2025: 325 of every 10,000 papers on this subject ▲ +9% share 2022→2025 share of research on this subject Researchers urge careful deployment of AI in language teaching and translation due to reliability concerns.
Machine translation · Language acquisition · Grammar · Reading
“Recognizing Contextual Polarity: An Exploration of Features for Phrase-Level Sentiment Analysis”
Cautions · theme 02
Benchmark Reliability Concerns
66 papers · 25.7% of this block
2022: 166 of every 10,000 papers on this subject 2023: 194 of every 10,000 papers on this subject 2024: 106 of every 10,000 papers on this subject 2025: 179 of every 10,000 papers on this subject 2022: 166 of every 10,000 papers on this subject 2023: 194 of every 10,000 papers on this subject 2024: 106 of every 10,000 papers on this subject 2025: 179 of every 10,000 papers on this subject ▲ +7% share 2022→2025 share of research on this subject Papers caution that current recall and precision metrics may misrepresent model performance in critical tasks.
Language model · Recall · Benchmark · Precision and recall
“Using Large Language Models to Analyze Symptom Discussions and Recommendations in Clinical Encounters.”
Cautions · theme 03
Documentation and Training Data Risks
55 papers · 21.4% of this block
2022: 139 of every 10,000 papers on this subject 2023: 136 of every 10,000 papers on this subject 2024: 87 of every 10,000 papers on this subject 2025: 132 of every 10,000 papers on this subject 2022: 139 of every 10,000 papers on this subject 2023: 136 of every 10,000 papers on this subject 2024: 87 of every 10,000 papers on this subject 2025: 132 of every 10,000 papers on this subject ▼ -5% share 2022→2025 share of research on this subject Studies highlight the dangers of poor documentation, biased coding practices, and noisy social‑media training sets.
Documentation · Coding · Training set · Social media
“Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions”
Cautions · theme 04
Robustness to Contextual Distractions
39 papers · 15.2% of this block
2022: 125 of every 10,000 papers on this subject 2023: 151 of every 10,000 papers on this subject 2024: 77 of every 10,000 papers on this subject 2025: 147 of every 10,000 papers on this subject 2022: 125 of every 10,000 papers on this subject 2023: 151 of every 10,000 papers on this subject 2024: 77 of every 10,000 papers on this subject 2025: 147 of every 10,000 papers on this subject ▲ +18% share 2022→2025 share of research on this subject Works emphasize vulnerability of language models to negation, variable categories, and adversarial context shifts.
Robustness · Language model · Negation · Categorical variable
“Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context”
Cautions · theme 05
Baseline and Deployment Pitfalls
30 papers · 11.7% of this block
2022: 980 of every 10,000 papers on this subject 2023: 1,029 of every 10,000 papers on this subject 2024: 833 of every 10,000 papers on this subject 2025: 418 of every 10,000 papers on this subject 2022: 980 of every 10,000 papers on this subject 2023: 1,029 of every 10,000 papers on this subject 2024: 833 of every 10,000 papers on this subject 2025: 418 of every 10,000 papers on this subject ▼ -57% share 2022→2025 share of research on this subject Researchers point out overreliance on baseline NLP tools and challenges in stable software deployment.
Natural language processing · Natural language · Baseline · Software deployment
“Dissecting Contextual Word Embeddings: Architecture and Representation”
Opportunities 2,938 papers · 7 recurring themes
→ Opportunities · theme 01
Knowledge Graph and Domain Integration
558 papers · 19.0% of this block
2022: 116 of every 10,000 papers on this subject 2023: 112 of every 10,000 papers on this subject 2024: 69 of every 10,000 papers on this subject 2025: 99 of every 10,000 papers on this subject 2022: 116 of every 10,000 papers on this subject 2023: 112 of every 10,000 papers on this subject 2024: 69 of every 10,000 papers on this subject 2025: 99 of every 10,000 papers on this subject ▼ -15% share 2022→2025 share of research on this subject Opportunities focus on linking graphs, code, and domain knowledge to enhance reasoning and decision making.
Graph · Knowledge graph · Code · Domain
“SkillGen: Learning Domain Skills for In-Context Sequential Decision Making”
Opportunities · theme 02
Language Acquisition and Meaning Modeling
508 papers · 17.3% of this block
2022: 624 of every 10,000 papers on this subject 2023: 647 of every 10,000 papers on this subject 2024: 630 of every 10,000 papers on this subject 2025: 653 of every 10,000 papers on this subject 2022: 624 of every 10,000 papers on this subject 2023: 647 of every 10,000 papers on this subject 2024: 630 of every 10,000 papers on this subject 2025: 653 of every 10,000 papers on this subject ▲ +4% share 2022→2025 share of research on this subject Papers explore how models can learn grammar, vocabulary, and abstract meaning akin to human learners.
Vocabulary · Grammar · Language acquisition · Meaning
“Humans and transformer LMs: Abstraction drives language learning”
Opportunities · theme 03
Vision‑Language Representation Advances
478 papers · 16.3% of this block
2022: 29 of every 10,000 papers on this subject 2023: 32 of every 10,000 papers on this subject 2024: 17 of every 10,000 papers on this subject 2025: 24 of every 10,000 papers on this subject 2022: 29 of every 10,000 papers on this subject 2023: 32 of every 10,000 papers on this subject 2024: 17 of every 10,000 papers on this subject 2025: 24 of every 10,000 papers on this subject ▼ -19% share 2022→2025 share of research on this subject Research showcases progress in aligning images with text for captioning and discriminative visual models.
Image · Representation · Closed captioning · Discriminative model
“Deep visual-semantic alignments for generating image descriptions”
Opportunities · theme 04
Unified NLP Parsing Frameworks
466 papers · 15.9% of this block
2022: 990 of every 10,000 papers on this subject 2023: 1,037 of every 10,000 papers on this subject 2024: 840 of every 10,000 papers on this subject 2025: 432 of every 10,000 papers on this subject 2022: 990 of every 10,000 papers on this subject 2023: 1,037 of every 10,000 papers on this subject 2024: 840 of every 10,000 papers on this subject 2025: 432 of every 10,000 papers on this subject ▼ -56% share 2022→2025 share of research on this subject Works propose comprehensive architectures that streamline parsing and conversational modeling across tasks.
Natural language processing · Natural language · Parsing · Sentence
“A unified architecture for natural language processing”
Opportunities · theme 05
Scalable Generative Language Systems
409 papers · 13.9% of this block
2022: 247 of every 10,000 papers on this subject 2023: 299 of every 10,000 papers on this subject 2024: 195 of every 10,000 papers on this subject 2025: 371 of every 10,000 papers on this subject 2022: 247 of every 10,000 papers on this subject 2023: 299 of every 10,000 papers on this subject 2024: 195 of every 10,000 papers on this subject 2025: 371 of every 10,000 papers on this subject ▲ +50% share 2022→2025 share of research on this subject Studies highlight large‑scale models that efficiently generate natural language and encode specialized knowledge.
Language model · Generative grammar · Natural language · Scalability
“Large language models encode clinical knowledge”
Opportunities · theme 06
Healthcare Knowledge Extraction
280 papers · 9.5% of this block
2022: 98 of every 10,000 papers on this subject 2023: 70 of every 10,000 papers on this subject 2024: 51 of every 10,000 papers on this subject 2025: 33 of every 10,000 papers on this subject 2022: 98 of every 10,000 papers on this subject 2023: 70 of every 10,000 papers on this subject 2024: 51 of every 10,000 papers on this subject 2025: 33 of every 10,000 papers on this subject ▼ -66% share 2022→2025 share of research on this subject Papers demonstrate using language models and graphs to derive medical concepts and support clinical analytics.
Health records · Electronic health record · Disease · Medical diagnosis
“Learning Low-Dimensional Representations of Medical Concepts.”
Opportunities · theme 07
Multilingual Sentiment Mining
239 papers · 8.1% of this block
2022: 2,502 of every 10,000 papers on this subject 2023: 2,556 of every 10,000 papers on this subject 2024: 3,072 of every 10,000 papers on this subject 2025: 2,694 of every 10,000 papers on this subject 2022: 2,502 of every 10,000 papers on this subject 2023: 2,556 of every 10,000 papers on this subject 2024: 3,072 of every 10,000 papers on this subject 2025: 2,694 of every 10,000 papers on this subject ▲ +8% share 2022→2025 share of research on this subject Research advances sentiment analysis techniques for diverse social‑media streams and multiple languages.
Sentiment analysis · Social media · Microblogging · Support vector machine
“Opinion Mining and Sentiment Analysis”
Which of these themes are growing fastest Tracks how the share of research themes has shifted globally from 2022 to 2025.
Problems
how much more (or less) of the world’s research on this subject each theme took up, 2022→2025
gaining share losing share
Generative Model Evaluation Gaps ▲+58%
Sentiment and Public Opinion Challenges ▲+8%
Representation and Comprehension Gaps ▲+6%
Language Acquisition and Semantics ▲+4%
Architectural and Cognitive Shortcomings ▲+1%
Fundamental NLP Model Issues ▼-57%
Lexical and Negation Limitations ▼-70%
Cautions
how much more (or less) of the world’s research on this subject each theme took up, 2022→2025
gaining share losing share
Robustness to Contextual Distractions ▲+18%
Caution on Language Learning Applications ▲+9%
Benchmark Reliability Concerns ▲+7%
Documentation and Training Data Risks ▼-5%
Baseline and Deployment Pitfalls ▼-57%
Opportunities
how much more (or less) of the world’s research on this subject each theme took up, 2022→2025
gaining share losing share
Scalable Generative Language Systems ▲+50%
Multilingual Sentiment Mining ▲+8%
Language Acquisition and Meaning Modeling ▲+4%
Knowledge Graph and Domain Integration ▼-15%
Vision‑Language Representation Advances ▼-19%
Unified NLP Parsing Frameworks ▼-56%
Healthcare Knowledge Extraction ▼-66%
Prism
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