AI Startups: Statistics (Market Size, Facts and Growth)

Traditional startups focus on building new products or services from the ground up, whereas AI startups leverage artificial intelligence technology to provide innovative solutions.

AI Startups are the hot thing in the market right now, and all the VCs are looking to cash in big time. But nothing is to swear by, with 90% of AI startups failing within a year.

The massive increase in AI startups makes us wonder how fast technology advances. In this article, we share exciting yet serious data that gives insight into the risky world of AI startups.

Overview of AI Startup Statistics

MetricStatistic
Global VC Funding for AI Startups (2023 estimate)$120-140 billion
US AI Startup Funding (2023 estimate)$44 billion
China AI Startup Funding (2023 estimate)$43.4 billion
Number of AI Unicorns (as of 2023)143
AI Market Size (2028 estimate)$1.07 trillion
Median Seed Funding for AI Startups$2.5 million
Median Series A Funding for AI Startups$15 million
Median Number of Employees at AI Startups62
Most In-Demand AI RolesMachine Learning Engineers, Data Scientists, AI Researchers
Leading Countries for AI StartupsUS, China, UK, India, Israel

Key AI Startup Funding Statistics

Global

CategoryFunding EstimateNotes
Global Total$120-140 billion [1]VC funding for AI Startups
United States$44 billion [2]Leads in AI startup funding
China$43.4 billion [3]Second highest after the US
UK, India, Israel, Canada$1-2 billion eachKey countries to watch [4]
Autonomous Driving$5-7 billion [5]As commercial services expand
Healthcare AI$4-6 billion [6]Growth in precision medicine
Enterprise AI$7-10 billion [6]Major opportunity
VC Firms Investing1,800+ [8][7]Sequoia, Accel, Tiger Global lead
Median Seed Funding$2.5 million [8]
Median Series A$15 million [8]For AI startups
AI Startup IPOs4-5 projected [10]Could raise $25-40 billion

Median

Metric2023 ProjectionNotes
Median VC deal size$8.4MDown from $10M in 2022
Median AI startup funding$14MAccording to Crunchbase
Generative AI market size$42.6BAccording to Pitchbook
Total AI market size$1.07 trillion by 2028Per Grand View Research
Generative AI startups in India60+Across industry verticals
AI annual growth rate40.2%2021 to 2028
  • As of 2023, there are 143 Artificial Intelligence Unicorn startups, according to data provided by CBInsights.
  • As of April 2023, approximately half of the unicorns worldwide were headquartered in North America. The regions that hosted the fewest unicorns were Oceania and Africa, with 8 and 4 unicorns based in each area.
  • In AI, these startups create innovative solutions and technologies that shape the future.

Most Well-Funded AI Startups

CompanyValuationFunds RaisedYear FoundedFocus Area
OpenAI$29 billion$11.3 billion2015Researching and developing ML solutions
Anthropic$4.1 billion [12]$1.5 billion2021AI safety and research
Inflection AI$4 billion$1.5 billion2022Human-computer interaction
Tempus$8.1 million [12]$1.3 billion2015Medicine solutions

Demographics of AI Startups

In 2023, the United States continues to lead in the total number of newly funded AI companies, with 1.9 times more than the European Union and the United Kingdom combined and 3.4 times more than China. However, China led the world in the number of generative AI startups receiving funding in the first half of 2023.

Number of AI startups by region

RegionNumber of Startups
North America7,522
Europe3,569
Asia2,686
South America1,027
Africa393


Number of AI startups by country

CountryNumber of Startups
United States5,749
China1,152
United Kingdom1,024
India767
Israel533

AI Market Size and Growth

TopicYearValue ($ Billion)Description
AI Market Revenue202286.9The estimated revenue of the AI market in the year 2022
Projected

AI Market Size

2028997The expected size of the AI market in the future
Technologies Fueling GrowthMachine learning, natural language processing, computer vision
  • AI is not just about robots and self-driving cars anymore. It’s permeating every industry, from healthcare to finance to entertainment. The AI market is no less than a futuristic playground, with a market size projected to reach $1.85 trillion by 2030.[9]
  • Businesses worldwide recognize and invest heavily in AI’s potential. Global spending on AI systems is expected to reach $97 billion by 2023. [13]
  • Investors are pouring money into AI startups like never before. In 2023 alone, AI startups raised over $40 billion in funding

Generative AI Startups: Pioneers of Ingenuity

  • Generative AI startups lead AI innovation, creating models that generate new content like music, art, or novels.
  • These startups address significant AI challenges such as efficiency, accuracy, and fairness.
  • The generative AI market size stands at $13.71 billion in 2023.
  • The AI startup scene is vibrant, with new startups emerging regularly, each with a unique approach to using AI.
  • The ecosystem supporting these startups includes investors providing funding, accelerators offering mentorship and resources, and communities providing support and inspiration.
  • The global generative AI market is projected to reach $1.85 trillion by 2030, growing at a CAGR of 37.3% from 2023 to 2030. [9]

Key Application Sectors for AI Startups

Top SectorsExamples
HealthcarePrecision medicine, medical imaging
FinanceFraud detection, risk modeling
RetailRecommendation systems, inventory management
Autonomous VehiclesComputer vision, predictive modeling
  • AI is transforming various sectors, including media and entertainment, where it’s used for tasks like visual dubbing.
  • AI is being used for textile recycling in the fashion and retail industry.
  • Many AI startups are focused on developing solutions that can be applied across various industries, such as AI assistants, human-machine interfaces (HMIs), digital twins, climate tech, and smell tech.
  • Around one-third of the most promising AI companies in 2023 are focused on specific industries.
  • Healthcare, finance, retail, and autonomous vehicles are hot sectors for promising new AI startups.
  • A significant number of AI startups are also working on cross-industry solutions.
Category% of StartupsDetails
Industry-Specific33%Healthcare, finance, retail, autonomous vehicles
Cross-Industry40%AI assistants, HMIs, digital twins, climate tech, smell tech
AI Development Tools27%Vector databases, synthetic datasets
  • Around one-third of the top AI companies in 2023 focus on specific industries.
  • About 40% are working on cross-industry solutions, including AI assistants and human-machine interfaces (HMIs), digital twins, climate tech, and smell tech.
  • Approximately 27% of the companies are developing tools to support AI development, such as vector database tech and synthetic datasets.

AI Startup Growth: A Data-Driven Perspective

TrendKey StatisticSourceYear
Market GrowthAI market to reach $407B

Up from $86.9B revenue

ResearchAndMarkets

 

Statista

2027

 

2022

Corporate Demand64% believe AI will increase productivityMIT Sloan Management Review2021
Cloud ServicesThe global cloud AI market size is valued at $44.97Grand View Research [11]2022
  • The AI market is projected to reach $407 billion by 2027, up from an estimated $86.9 billion in revenue in 2022. 
  • Corporations increasingly seek AI solutions. A significant 64% of businesses believe that artificial intelligence will help increase their productivity. 
  • This growing confidence in AI’s potential has led to an increase in acquisitions of AI startups.
  • Cloud services like Microsoft Azure, Google Cloud, and Amazon Web Services are making powerful AI tools more accessible to companies of all sizes.
CategoryDetails
DataExpansion of datasets for model training
AlgorithmsDevelopment of sophisticated algorithms
Compute PowerImprovement in computing power
Corporate DemandIncreased acquisitions of AI startups
Cloud ServicesMicrosoft Azure, Google Cloud, AWS

Talent and Computing Needs

MetricStatistic
Employees at prominent startup (OpenAI)500
Most in-demand rolesMachine learning engineers, data scientists, AI researchers
Median employees at startups62
AI talent demandGrowing significantly as more companies pursue AI
Salary competitionStartups struggle to match FAANG companies
Specialized hardware needsTPUs for accelerating AI workloads
Hardware access challengesTPUs are expensive/hard to access for startups
  • These startups are packed with talent; for instance, OpenAI, one of the most prominent AI startups in the world, has around 500 employees.
  • AI startups stay agile with teams of around 62 employees, but as they grow, the demand for specialized AI talent increases significantly as more companies pursue AI solutions.
  • AI startups seek scarce talents like machine learning engineers, data scientists, and AI researchers to build their innovations. 
  • When recruiting these professionals, they struggle to match the high salaries of big tech companies like Facebook, Amazon, Apple, Netflix, and Google (FAANG).
  • As AI models grow more complex, startups need specialized hardware like Google’s TPUs to accelerate training, but acquiring these expensive chips remains difficult compared to the resources of large tech firms.

Struggles of AI Startups

  • Finding experienced AI talent is extremely challenging. 
  • According to Gartner, demand for AI talent exceeded supply by 58% in 2022.
  • We have to compete with big tech companies who can offer higher salaries and benefits.
  • 31% of AI companies cite data management as their top challenge, per S&P Global.
  • It is hard to predict customer needs due to the disruptive nature of AI.
  • Dynamic technology makes maintaining a competitive advantage difficult.
  • The complex value proposition takes time to communicate.
  • AI Startups incur high computing infrastructure costs (CAPEX/OPEX).
  • Requires expensive integration with existing systems. 
  • Ongoing monitoring and improvements add to costs.

Achieving Product-Market Fit for AI Startups

ThemeKey PointsExamples
Identifying Problems– Validate real customer problems

– Focus on meaningful, urgent issues

Building Solutions– Create competitive advantages

– Requires technical and business skills

– ChatGPT: 10M users, $100M funding

– Casetext: 5,000 customers, $50M funding

– Zipline: 1M deliveries, $225M funding

  • Must identify and validate real customer problems through research and testing.
  • Should focus on meaningful, urgent, and widespread issues.
  • Examples like Grammarly (30M users, $200M funding) and UiPath (8,500 customers, $2B funding) have achieved product-market fit.
StartupCustomers/UsersFundingProduct
Grammarly30 million$200 millionWriting assistant
UiPath8,500$2 billionRobotic process automation
ChatGPT10 million$100 millionConversational AI
Casetext5,000$50 millionLegal research
Zipline1 million deliveries$225 millionMedical drone delivery

Key Challenges Going Forward

ChallengeStatisticsSource
Maintaining innovation85% of CEOs view innovation as vital

21% consider their firms innovative

Capgemini Research Institute
Managing expectations62% would trust the brand more with transparent, ethical AI useCapgemini Research Institute
Regulations40% of US AI startups dealing with regulatory complianceBrookings
  • A disquieting reveals that 85% of CEOs view innovation as vital. However, a measly 21% consider their firms innovative. 
  • Trust is a rare commodity in the age of data breaches. For AI, discretion is not just courageous but survival.
  • According to Capgemini, 62% of customers would trust a brand more if it uses AI in a transparent and ethical way. 
  • AI’s regulatory landscape is like navigating a corn maze blindfolded. From GDPR to the CCPA, these are more than just acronyms but stumbling blocks. Regulatory compliance remains a complex challenge for AI startups.
  • Brookings states that 40% of American AI startups are jumping through these regulatory hoops, making compliance a checkbox and a survival skill.

Conclusion

The AI startup landscape shows immense promise, but responsible growth requires overcoming ethical challenges, job loss, and responsible innovation. With prudent self-regulation and collaboration, AI pioneers can achieve great progress equitably. Realizing AI’s full potential demands cautious optimism grounded in wisdom.

References

  1. https://news.crunchbase.com/venture/vc-funding-falling-report-data-q2-2023-global/
  2. https://news.crunchbase.com/venture/vc-funding-falling-report-data-q2-2023-north-america/
  3. https://kpmg.com/cn/en/home/media/press-releases/2023/08/vc-investment-in-china-sees-growing-optimism.html#:~:text=VC%20fundraising%20in%20China%20during,to%20dispense%20to%20growing%20companies.
  4. https://news.crunchbase.com/venture/asia-funding-drops-china-india-israel-h1-2023/
  5. https://news.crunchbase.com/transportation/embark-trucks-closes-autonomous-vehicles/
  6. https://www.forbes.com/sites/petercohan/2023/05/30/generative-ai-7-trillion-ecosystem-invest-in-nvidia-microsoft-adobe-and-more/
  7. https://www.bloomberg.com/news/articles/2023-05-25/vc-giants-accel-sequoia-scour-portfolio-startups-for-ai-risk#xj4y7vzkg
  8. https://www.nasdaq.com/articles/ai-startup-hugging-face-valued-at-$4.5-bln-in-latest-round-of-funding
  9. https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market
  10. https://www.forbes.com/advisor/business/ai-statistics
  11. https://www.grandviewresearch.com/industry-analysis/cloud-ai-market-report
  12. https://www.insidermonkey.com/blog/5-best-funded-ai-startups-in-2023-1175183/
  13. https://www.globaldata.com/store/report/artificial-intelligence-market-analysis/