Buy Crypto
Pay with
USD
USD
Buy & Sell
Hot
Supports Visa, Mastercard, SEPA & more
P2P
0 Fees
Flexible trading, zero fees
Gate Card
Use your crypto for payments worldwide
Markets
Trade
Basic
Advanced
Futures
Futures
Access hundreds of perpetual contracts
TradFi
Gold
One platform for global traditional assets
Options
Hot
Trade European-style vanilla options
Unified Account
Maximize your capital efficiency
Demo Trading
Introduction to Futures Trading
Learn the basics of futures trading
Futures Events
Join events to earn rewards
Demo Trading
Use virtual funds to practice risk-free trading
Earn
Launch
CandyDrop
Collect candies to earn airdrops
Launchpool
Quick staking, earn potential new tokens
HODLer Airdrop
Hold GT and get massive airdrops for free
Pre-IPOs
Unlock full access to global stock IPOs
Alpha Points
Trade on-chain assets and earn airdrops
Futures Points
Earn futures points and claim airdrop rewards
Investment
Square
Square
Post, share, and explore crypto trends
Live
moments live
Live crypto market analysis
Chat
Chat with crypto traders
News
What is happening in crypto
flower_head
More
Promotions
AI
Others
TradFi
WCTC S8
Rewards
AIG

American International Group Price

AIG
$74.74
+$1.54(+2.10%)

*Data last updated: 2026-04-30 19:59 (UTC+8)

As of 2026-04-30 19:59, American International Group (AIG) is priced at $74.74, with a total market cap of $39.59B, a P/E ratio of 15.61, and a dividend yield of 2.43%. Today, the stock price fluctuated between $72.89 and $75.65. The current price is 2.53% above the day's low and 1.20% below the day's high, with a trading volume of 4.49M. Over the past 52 weeks, AIG has traded between $72.89 to $75.65, and the current price is -1.20% away from the 52-week high.

AIG Key Stats

Yesterday's Close$74.16
Market Cap$39.59B
Volume4.49M
P/E Ratio15.61
Dividend Yield (TTM)2.43%
Dividend Amount$0.45
Diluted EPS (TTM)5.72
Net Income (FY)$3.09B
Revenue (FY)$26.77B
Earnings Date2026-04-30
EPS Estimate1.90
Revenue Estimate$7.03B
Shares Outstanding533.88M
Beta (1Y)0.601
Ex-Dividend Date2026-03-16
Dividend Payment Date2026-03-30

About AIG

American International Group, Inc. offers insurance products for commercial, institutional, and individual customers in North America and internationally. The company's General Insurance segment provides general liability, environmental, commercial automobile liability, workers' compensation, casualty, and crisis management insurance products; commercial, industrial, and energy-related property insurance; and aerospace, political risk, trade credit, portfolio solutions, crop, and marine insurance. It also provides professional liability insurance products for a range of businesses and risks, including directors and officers, mergers and acquisitions, fidelity, employment practices, fiduciary liability, cyber risk, kidnap and ransom, and errors and omissions insurance. In addition, this segment offers personal auto and property insurance, such as auto, homeowners, umbrella, yacht, fine art, and collections; voluntary and sponsor-paid personal accident; supplemental health products; extended warranty insurance products; and travel insurance products. Its Life and Retirement segment offers variable annuities, index and fixed annuities, and retail mutual funds; and financial planning and advisory services; record-keeping, plan administrative, and compliance services; and term life and universal life insurance. It also provides stable value wrap products, and structured settlement and pension risk transfer annuities; and corporate- and bank-owned life insurance and guaranteed investment contracts. This segment sells its products through independent marketing organizations, independent insurance agents, financial advisors, direct marketing, banks, and broker-dealers. The company was founded in 1919 and is headquartered in New York, New York.
SectorFinancial Services
IndustryInsurance - Diversified
CEOPeter Salvatore Zaffino
HeadquartersNew York City,NY,US
Official Websitehttps://www.aig.com
Employees (FY)22.10K
Average Revenue (1Y)$1.21M
Net Income per Employee$140.09K

American International Group (AIG) FAQ

What's the stock price of American International Group (AIG) today?

x
American International Group (AIG) is currently trading at $74.74, with a 24h change of +2.10%. The 52-week trading range is $72.89–$75.65.

What are the 52-week high and low prices for American International Group (AIG)?

x

What is the price-to-earnings (P/E) ratio of American International Group (AIG)? What does it indicate?

x

What is the market cap of American International Group (AIG)?

x

What is the most recent quarterly earnings per share (EPS) for American International Group (AIG)?

x

Should you buy or sell American International Group (AIG) now?

x

What factors can affect the stock price of American International Group (AIG)?

x

How to buy American International Group (AIG) stock?

x

Risk Warning

The stock market involves a high level of risk and price volatility. The value of your investment may increase or decrease, and you may not recover the full amount invested. Past performance is not a reliable indicator of future results. Before making any investment decisions, you should carefully assess your investment experience, financial situation, investment objectives, and risk tolerance, and conduct your own research. Where appropriate, consult an independent financial adviser.

Disclaimer

The content on this page is provided for informational purposes only and does not constitute investment advice, financial advice, or trading recommendations. Gate shall not be held liable for any loss or damage resulting from such financial decisions. Further, take note that Gate may not be able to provide full service in certain markets and jurisdictions, including but not limited to the United States of America, Canada, Iran, and Cuba. For more information on Restricted Locations, please refer to the User Agreement.

Other Trading Markets

AIG
CFD
Trade

Hot Posts About American International Group (AIG)

TroyMuYi

TroyMuYi

10 hours ago
Is AI truly humanity's future or humanity's disaster? The bigger the fish, the larger the bones. The larger the bones, the smaller the meat. So the bigger the fish, the smaller the fish. That last sentence was a joke. But in the current capital markets, almost every participant assumes the same hypothesis: the more powerful AI is, the more profitable tech giants become, and their stock prices should be higher. This hypothesis supports the record highs of the S&P 500, the 18 consecutive gains of the Philadelphia Semiconductor Index, and Nvidia’s rush toward a $5 trillion market cap. But precisely this seemingly obvious logic hides an unavoidable and deadly paradox—if AI really becomes very powerful, future capital expenditures should be sharply reduced, and the stock market built on extreme spending will fall from its peak. Conversely, if AI isn’t powerful enough, spending will also be disproven, and the stock market will crash. Either way, the endpoint is the same. ---1. The Edge of the Paradox: Two Paths, One Ending We place the unprecedented $650 billion in capital expenditure by the four major tech giants in 2026 on a scale, then ask a simple question: what will happen after this money is spent? The first path: AI fails. This is currently the most perceptible crack. OpenAI’s CFO has issued an internal warning that if the company’s revenue growth isn’t fast enough, it may not be able to pay future data center contract costs. This global money-burning AI company lost about $12 billion in Q3 last year, with user growth and revenue both below internal targets, and market share being eroded by Anthropic and Google Gemini. As the largest “buyer of chips” in the entire supply chain, it has plainly told the market: I may not be able to afford the next computing bill. Buyers run out of money, and orders will naturally be cut. Oracle signed a five-year, $300 billion computing contract with OpenAI, and the stock plummeted on the news. AMD and Nvidia were dragged down simultaneously. This is just the first domino. When the financial holes at the application layer propagate down to infrastructure, the entire “selling shovels” chain of orders will collapse. Next year, giants will have to drastically cut capital spending because downstream customers no longer want to pay sky-high computing costs. This is a clear logical chain: AI fails → application layer can’t monetize → reduce computing orders → revenue from chip sellers collapses → stock market top is locked in. The second path: AI succeeds. This is where the true sharp edge of the paradox lies. Suppose everything goes smoothly, and the $650 billion investment produces an extremely powerful AI. It can code, create, and make autonomous decisions, exponentially boosting enterprise efficiency. Then what? If the next-generation AI model’s training and inference efficiency are ten times the current, why do we still need such large computing clusters? If a smaller model can accomplish what today requires an entire data center, then do these data centers and servers filled with Nvidia GPUs need to keep expanding tomorrow? The essence of technological progress has always been doing more with less resources. After the steam engine’s popularization, no one kept horses. If AI truly becomes powerful enough to rewrite productivity, it will first rewrite its own cost structure. The cost per unit of computing power will plummet, and giants will find they only need half the current expenditure to maintain the same level of intelligence. At that point, maintaining the roughly $650 billion annual capital expenditure is not faith, but pure waste. This follows a similarly clear logical chain: AI succeeds → efficiency revolution → demand for computing power crashes → capital expenditure must shrink → revenue of chip sellers collapses → stock market top is locked in. Whether AI succeeds or fails, the next year must see a significant cut in capital spending. This is the sharpest part of the paradox—it doesn’t rely on pessimistic forecasts but on a simple economic principle: if investments don’t generate returns, they stop; if investments generate huge returns, only half the resources are needed to sustain the same output, so they also stop. ---2. The Limit of $650 Billion: Profits Can No Longer Sustain This paradox isn’t just a thought experiment; it’s being realized line by line in financial reports. Take Alphabet, Google’s parent company, as an example: its free cash flow in 2026 is expected to plummet from about $73.3 billion in 2025 to roughly $8.2 billion—a nearly 90% drop. Not only Google, but Bank of America analysts warn that by 2026, AI-related capital expenditures could account for up to 94% of these companies’ operating cash flows. Almost all the money recovered will be reinvested into data centers—an all-in gamble. And what’s the cost of this gamble? When the application layer can’t turn computing consumption into sustainable revenue, and downstream clients cut back IT budgets due to $110 oil prices, this $650 billion “investment” becomes an unrepayable debt. SoftBank repeatedly mortgaged its OpenAI shares, borrowing about $40 billion to invest in the same heavily loss-making company. This isn’t an isolated case; it’s a microcosm of the entire industry chain. Some are already betting on this logic. Investment bank Wedbush predicts that capital expenditure growth will slow down in the second half of 2026. Forrester forecasts that about 25% of AI investments will be delayed until after 2027 because financial returns can no longer support current burn rates. Goldman Sachs analysts also predict that cloud capital expenditure growth will sharply decline from 54% in 2025 to 26% in 2026. This isn’t a slow slowdown; it’s a cliff. ---3. Every “Spending Miracle” in History Ended the Same Way This isn’t the first time. In 2000, telecom giant WorldCom mortgaged its own stock to borrow hundreds of billions to lay fiber optic cables, betting on “internet traffic growing exponentially forever.” When the fiber was laid, demand didn’t keep up, WorldCom went bankrupt, dragging half of Nasdaq down. In 2008, AIG confidently believed its mortgage-backed securities had no risk, leveraged to the extreme, and when Lehman Brothers collapsed, the entire credit market froze instantly. Every time, people justified their top-tier investments with “this time is different”: the internet is different, fiber is different, real estate is different. Yet every time, when the music stops, the same physical laws take over the ruins—capital expenditure must be paid back with future cash flows, which are never shifted by optimistic expectations. The uniqueness of this AI wave is that it sets up an unsolvable paradox for itself. If it’s a bubble, it will burst like 2000. If it’s not a bubble and truly succeeds, it will use its own efficiency revolution to end the limit-spending that fuels this bubble. The more powerful AI becomes, the more resource-intensive its computing needs. The more resource-intensive, the less capital expenditure is needed. The less capital expenditure, the heavier the fall for the semiconductor supply chain supported by roughly $650 billion orders. ---4. Conclusion This paradox doesn’t need any external negative news to intensify. It’s not a hypothesis waiting for financial reports to disprove, nor a variable dependent on oil prices or geopolitical shifts. It’s the core logical fracture of this super bull market—the current valuation of US stocks is built on the assumption that “AI will forever require exponential growth in computing power.” But if AI truly becomes revolutionary, the first thing it will do is end that very assumption. Whether it fails or succeeds, next year’s capital expenditure will slide from its peak. Once spending peaks, semiconductor revenues peak; once revenues peak, stock prices only have one direction. This is the logical endgame. In this endgame, the more powerful AI is, the lower future US stock prices may be. This isn’t a prediction; it’s a physical law sealed by $650 billion, $111 oil, about $135 billion in SoftBank debt, and a head of application layer giants even CFOs are warning about.
ETH+1.26%
0
0
0
0
ASatoshiApprentice

ASatoshiApprentice

01-11 15:31
Two decades have passed since the 2008 financial crisis nearly destroyed AIG. Back then, the insurance giant's near-collapse triggered government bailout and sent shockwaves across global markets. Now, as AIG inches back into risk-taking mode, it raises an interesting question: are we truly learning from history, or just repeating it? The irony isn't lost on anyone watching crypto markets. Traditional finance keeps finding new ways to lever up and push boundaries. When institutions like AIG start regaining appetite for complex bets, it often signals the market's collective amnesia about systemic risk. Real assets, digital assets—the patterns rhyme across decades. For Web3 participants paying attention, this behavioral cycle offers a crucial lesson. Whether it's traditional finance or decentralized protocols, risk appetite follows predictable waves. Understanding these macro-economic tides helps inform better portfolio decisions and timing strategies. History may not repeat, but it sure does echo.
18
5
0
0
GasWaster

GasWaster

01-11 12:09
Two decades have passed since the financial crisis nearly toppled the global economy, and AIG—once the poster child for "too big to fail"—is gradually repositioning itself back toward riskier assets. The insurance giant's pivot offers a sobering reminder about market cycles and portfolio management. After a near-death experience that required a government bailout exceeding $180 billion, AIG spent years deleveraging and stabilizing. Now, as markets have recovered and economic conditions shifted, the company is inching back into more aggressive positioning. This pattern reveals something crucial: even institutions with catastrophic failure experiences eventually drift back to risk-taking. The question isn't whether markets will cycle again—it's when. For crypto investors and traders, AIG's gradual return to risk is a textbook case study. It shows how institutional appetite ebbs and flows, how complacency creeps in after recovery, and why portfolio diversification remains non-negotiable. The lesson isn't to avoid risk—it's to respect it, and never forget what happened last time.
10
9
0
0