Goldman Sachs Sees AI Spending Exceeding $900 Billion in 2026

Key Takeaways

• Goldman Sachs forecasts AI hardware and intellectual-property spending will exceed $900 billion by end-2026 and reach $1.4 trillion by end-2027, nearly 4% of the US economy.
• Goldman projects 8% US business-investment growth in 2027, versus a 4.2% consensus forecast; it estimates AI investment will add 0.6 percentage points to GDP growth, or 0.2 points excluding semiconductors.
• IBM rose 11.7% as investors focused on enterprise AI systems; it reported $17.1 billion in third-quarter revenue, 9% software growth and $8.0 billion in first-nine-month free cash flow.
• A shopping test found risky websites in 8% of ChatGPT answers and 4% of Gemini answers, compared with 15% for Perplexity; smaller brands faced such links about twice as often as larger ones.
• ChatGPT and Google product results can contain omissions or inaccurate details and links; OpenAI expanded its Agentic Commerce Protocol to product discovery and ended in-chat Instant Checkout in March 2026.
• CoreWeave’s strong quarter lifted AI and chip stocks; a separate report about a possible Nvidia board move weighed on Nvidia shares after hours, but did not establish that CEO Jensen Huang would be removed.
• Laplace Insights and Palos will use PSIMON to support monitoring of the Palos-Mitchell Alpha Fund, while Palos portfolio managers retain investment decisions.
• China’s AI diagnostic-device count rose from 8 in 2020 to 298 in 2024, but deployment remained concentrated in tertiary hospitals despite lower geographic inequality.
• Lotte Innovate and Thales plan an AI security-monitoring service using Imperva technology; Checkmarx cites a drop in median vulnerability weaponization time from 840 days to 1.6 days.
• A 401(k) example shows a 0.75% AI fund costs $1,400 more annually than a 0.05% index fund on $200,000 and would need 0.7 percentage points of annual pre-fee outperformance to cover the fee difference.

Goldman expects AI spending to reach $1.4 trillion by 2027

Goldman Sachs forecasts annual spending on AI related hardware and intellectual property will top $900 billion by the end of 2026 and reach $1.4 trillion by the end of 2027. That would equal nearly 4% of the US economy. Goldman says AI will remain the main driver of business investment growth, even as borrowing costs and investor scrutiny pose concerns. It expects US business investment to grow 8% quarterly in 2027, compared with a 4.2% consensus forecast.

Goldman sees AI as a major driver of US business investment in 2027

Goldman Sachs forecasts annual spending on AI related hardware and intellectual property will exceed $900 billion by the end of 2026 and reach $1.4 trillion by the end of 2027, nearly 4% of the US economy. The bank expects AI investment, including semiconductors, to add 5.3 percentage points to 2027 capital spending growth and 0.6 percentage points to US GDP growth. Without semiconductor investment, it estimates the gains at 4.3 percentage points for capital spending and 0.2 percentage points for GDP. Goldman forecasts US business investment will grow 8% quarterly in 2027, almost double the 4.2% consensus forecast. It says election related concerns about data center rules pose only limited risks to AI investment.

Goldman expects AI investment to lift US business spending in 2027

Goldman Sachs predicts annual spending on AI related hardware and intellectual property will rise above $900 billion by the end of 2026 and reach $1.4 trillion by the end of 2027. The total would equal nearly 4% of the US economy. Goldman estimates AI investment, including semiconductors, will add 5.3 percentage points to 2027 capital spending growth and 0.6 percentage points to GDP growth. Excluding semiconductors, the estimated boosts are 4.3 percentage points and 0.2 percentage points. The bank forecasts quarterly US business investment growth of 8% in 2027, compared with a 4.2% consensus forecast.

Goldman says AI spending will drive US investment through 2027

Goldman Sachs expects annual spending on AI related hardware and intellectual property to exceed $900 billion in 2026 and reach $1.4 trillion by the end of 2027, nearly 4% of the US economy. It estimates AI investment, including semiconductors, will add 5.3 percentage points to 2027 capital spending growth and 0.6 percentage points to US GDP growth. Without semiconductor spending, the expected gains fall to 4.3 percentage points for capital spending and 0.2 percentage points for GDP. Goldman forecasts quarterly US business investment growth of 8% in 2027, compared with a 4.2% consensus forecast. It says higher borrowing costs and concerns about data center regulation pose only limited risks to AI investment.

Goldman forecasts $1.4 trillion in AI investment by 2027

Goldman Sachs forecasts annual spending on AI related hardware and intellectual property will reach $1.4 trillion by the end of 2027, nearly 4% of the US economy. The article compares that forecast with Bureau of Economic Analysis figures showing US companies invested $933.9 billion at an annual rate in information processing equipment in the third quarter of 2026. By the article’s calculations, that equipment supplied $270.6 billion of the $534.3 billion increase in business investment from the third quarter of 2025 to the third quarter of 2026. Goldman says AI investment will add 5.3 percentage points to 2027 capital spending growth and 0.6 percentage points to GDP growth, or 0.2 points for GDP without semiconductors. The article notes it reviewed Reuters’ report, not Goldman’s original note, and that the 2027 figures are forecasts.

Goldman Sachs sees AI spending reaching $1.4 trillion by 2027

Goldman Sachs expects US spending on AI hardware and intellectual property to reach an annual rate of $1.4 trillion by the end of 2027, nearly 4% of the US economy. The bank forecasts spending will pass $900 billion by the end of 2026, with data centers, semiconductors and computing equipment supporting growth. It estimates AI investment, including semiconductors, will add 5.3 percentage points to capital spending growth and 0.6 percentage points to US economic growth in 2027. Without semiconductor investment, those contributions would be 4.3 percentage points and 0.2 percentage points. Goldman forecasts US business investment will grow 8% in 2027, nearly double the 4.2% consensus forecast.

Goldman Sachs says AI will lead US business investment growth in 2027

Goldman Sachs forecasts annual spending on AI hardware and intellectual property will reach US$1.4 trillion by the end of 2027, nearly 4% of the US economy. The bank expects spending to exceed US$900 billion by the end of 2026 and says AI will remain the main driver of business investment growth in 2027. It sees limited risk to AI investment from concerns about borrowing costs, debt funded expansion and possible data center rules after Democratic victories in the US midterm elections. Including semiconductor investment, AI spending could add 5.3 percentage points to 2027 capital spending growth and 0.6 percentage points to US GDP growth. Goldman forecasts 8% US business investment growth in 2027, compared with a 4.2% consensus forecast.

Goldman Sachs projects $1.4 trillion in AI spending by 2027

Goldman Sachs forecasts annualized US spending on AI hardware and intellectual property will reach $1.4 trillion by the end of 2027. The bank says AI investment, excluding semiconductors, could add 4.3 percentage points to capital spending growth and 0.2 percentage points to US GDP growth in 2027. It expects US business investment to grow 8% that year, nearly double the 4.2% consensus forecast. The article also reports that AI stocks lifted the US market on Wednesday, with cloud chip rental company CoreWeave rising 24.7% after reporting a smaller loss than analysts expected and making announcements aimed at easing industry concerns.

IBM gains as investors shift from costly AI infrastructure

Investors have been selling highly valued AI companies amid scrutiny of large data center costs, while IBM shares rose 11.7% to near $245 after falling 5% in late October. The article links IBM’s performance to investor interest in software and systems that help large companies use AI within their own networks. IBM reported third-quarter revenue of $17.1 billion and adjusted earnings of $2.95 per share, both above forecasts. Software revenue rose 9% year over year, and free cash flow for the first nine months reached $8.0 billion, up 8%. The article says IBM’s hybrid cloud, on-premises systems and watsonx governance platform serve regulated organizations that cannot place confidential data in public cloud models.

IBM’s cash flow and enterprise AI business draw investor interest

Investors have pulled back from some AI stocks as they question data center costs, but IBM rose 11.7% to trade near $245 after an earlier decline in late October. The article says institutions are moving toward software and systems companies that help large businesses deploy AI behind their own firewalls. IBM’s third-quarter revenue was $17.1 billion, and adjusted earnings reached $2.95 per share, beating estimates. Software revenue grew 9% year over year, while free cash flow for the first nine months was $8.0 billion, up 8%. IBM’s hybrid cloud and on-premises systems support regulated customers, and the company’s software offerings include Red Hat OpenShift and the watsonx governance platform.

AI Chatbots Sometimes Send Shoppers to Fake Retail Websites

A study by The Verge tested ChatGPT, Gemini, and Perplexity with shopping questions about 151 brands. Across 6,795 answers, all three chatbots sometimes showed risky sites, including fake stores, knockoff sellers, and inactive domains. Perplexity showed risky sites in 15 percent of answers, ChatGPT in 8 percent, and Gemini in 4 percent. Smaller brands faced these sites about twice as often as larger companies. Podqi CEO Trevor West advised shoppers to check a website before sharing personal or credit card information.

How Brands Can Fix Errors in AI Shopping Results

AI shopping tools such as ChatGPT and Google can show product cards with prices, ratings, and links based on information from across the web. The results may leave out a product, show incorrect prices or details, rank it below competitors, or send shoppers to a reseller instead of the brand. The guide explains how ChatGPT Shopping draws on merchant feeds, Shopify Catalog, product data providers, and public reviews, while Google uses its Shopping Graph and Merchant Center feeds. It recommends that brands check how their products appear and compare prices, stock, product details, and purchase links. OpenAI expanded its Agentic Commerce Protocol to product discovery in March 2026 and ended in-chat Instant Checkout that month.

Big Law Firms Should Show Clients What Their AI Spending Delivers

The article questions whether large law firms’ major AI investments will produce clear benefits for clients or mainly serve as marketing or a way to lower firms’ costs. It argues that firms should share evidence of how AI changes the services clients receive, rather than focusing on how much they spend. Possible benefits include lower fees, faster work, and better legal work products. The author says firms can show clients measurable results, such as time saved, reduced costs, or insights that affect a case or deal.

CoreWeave Lifts AI Stocks Before Nvidia Board Report Shifts Focus

CoreWeave reported a strong quarter, sending AI and chip stocks sharply higher. The story then shifted after a report said Nvidia’s board was preparing to remove CEO Jensen Huang, which weighed on Nvidia shares after hours. The article also flagged Federal Reserve rate-hike odds, oil, and Cisco’s scheduled report.

AI Stock Picks Could Cost a 401(k) Investor Thousands in Extra Fees

A 57-year-old investor with $200,000 in a 401(k) is considering an AI-managed fund that charges 0.75 percent, compared with 0.05 percent for a broad index fund. At that balance, the annual fees would be $1,500 and $100, a difference of $1,400, even if the AI fund loses money. Using an example of 7 percent yearly returns before fees, the article estimates the cheaper fund would grow to about $392,000 after 10 years and $767,000 after 20 years, compared with about $367,000 and $672,000 for the AI fund. It says the AI strategy would need to beat the index by 0.7 percentage points each year before fees to cover the added cost. The article recommends comparing fees and returns after fees, and considering higher contributions instead.

Laplace Insights and Palos bring AI signals to fund monitoring

Laplace Insights and Palos Wealth Management signed a multi-year agreement on November 12, 2026, to use Laplace’s PSIMON platform with the Palos-Mitchell Alpha Fund (PMAF). PSIMON uses machine learning to monitor daily watchlists, spot unusual changes in asset behavior, and estimate near-term volatility risk. Its signals will appear on the fund’s portfolio monitoring dashboard and support investment research, but Palos’s portfolio managers will continue to make all investment decisions. PMAF also uses equity derivatives and tail-risk hedging to manage exposure. PSIMON uses Laplace’s Asset Regime Intelligence technology to track changes in assets in relation to peers, sectors, and the broader market.

China’s AI diagnostic devices remain concentrated in top hospitals

A study of public hospital procurement in China from 2020 to 2024 found that AI-enabled diagnostic and screening devices spread across more regions but remained concentrated in top-tier tertiary hospitals. The number of devices rose from 8 in 2020 to 298 in 2024, while the population-based Theil-T index fell from 0.425 to 0.047 and the hospital-based index fell from 0.591 to 0.070. Yet tertiary hospitals had a location quotient of 2.154 in 2024, while the figure for secondary hospitals declined from 0.361 to 0.320. The share of total inequality linked to differences between hospital tiers within regions rose from 47.3 percent to 84.5 percent. Researchers Panpan Jiang and Lisha Cheng said that tracking regional distribution alone misses these disparities and that deployment monitoring should include hospital tiers.

Lotte Innovate and Thales team up on AI security service

Lotte Innovate plans to launch its AI Premium Security Monitoring Service in November, combining Thales technology with Lotte’s security monitoring platform. The companies signed a memorandum of understanding at Lotte Innovate’s Seoul headquarters on October 28. The partnership centers on Imperva’s Web Application and API Protection solution, which protects websites and application programming interfaces. Imperva’s web application firewall detects and blocks malicious traffic and unusual access attempts, while Lotte’s platform will help analyze and respond to threats. The companies also plan to offer security system deployment, continuous monitoring and operations, and joint sales to outside corporate customers. Thales acquired Imperva in December 2023.

Checkmarx urges app security teams to focus on removing risk

Checkmarx says security teams must do more than find software vulnerabilities as AI speeds up development and attackers use AI to create exploits. Cloud Security Alliance research cited in the article says the median time to weaponize a vulnerability fell from 840 days to 1.6 days, while Checkmarx’s 2026 report found that 75% of organizations knowingly release applications with vulnerable code. Checkmarx describes tools that use AI to improve detection, rank findings by attack risk, suggest fixes for human approval, and support developers as they write code. The article also cites research showing that 96% of developers have AI security tools in their IDEs, but only 18% use security checks while writing code, and that only 22% of organizations have formal AI governance policies. It urges security leaders to improve risk visibility, eliminate important risks, and maintain human oversight and governance as AI development grows.

Sources

• AI to stay dominant force behind US business investment in 2027, Goldman says
• AI to stay dominant force behind US business investment in 2027, Goldman says
• AI to stay dominant force behind US business investment in 2027, Goldman says
• Goldman Sachs sees AI driving U.S. business investment growth through 2027
• Goldman Sees $1.4T AI Investment; Tech Was 64% of Capex Gain
• AI spending to hit $1.4 trillion by 2027, drive US business investment growth, Goldman Sachs says
• AI to stay dominant force behind US business investment in 2027, Goldman says
• Goldman Sachs forecasts AI spending will hit $1.4 trillion by end of 2027
• AI stocks are sinking: Why is smart money buying IBM instead?
• AI stocks are sinking: Why is smart money buying IBM instead?
• AI chatbots are recommending fake retail websites, study finds
• AI Shopping Errors: What To Fix To Help Shoppers Choose Your Products
• Is Big Law ‘AI Gaslighting’ Us?
• Stock Market Today: CoreWeave (CRWV) Reignites the AI Trade, Then Nvidia’s (NVDA) Boardroom Takes Over the Story
• He Wants AI to Pick Winning Stocks for His $200,000 401(k). A 0.75% Fee Could Cost Him $1,400 More a Year Than a Low-Cost Fund. He'll Pay the Extra Fees Even if AI Picks Losers
• Laplace Insights and Palos Announce AI Collaboration for Investment Research and Portfolio Monitoring
• Medical Artificial Intelligence Procurement in China Concentrates Heavily in Tertiary Hospitals
• Lotte Innovate Partners With Thales on AI Security Service
• AI in AppSec: Why Finding Vulnerabilities Is No Longer Enough