The AI Boom Is Becoming a Credit Story: What a Technology Reversal Could Mean for U.S. Businesses

Artificial intelligence may transform the global economy. But the debt, contracts, private financing, and international supply chains supporting the AI investment race could expose businesses to significant risk if expected returns do not materialize.

Artificial intelligence is no longer merely a technology story.

It is increasingly a financing, infrastructure, energy, international trade, and contract story.

The world’s largest technology companies are committing enormous amounts of capital to data centers, advanced semiconductors, cloud infrastructure, electrical equipment, cooling systems, networking capacity, and long-term energy supplies. Much of that investment was initially supported by the substantial cash generated by large technology companies.

As the scale of spending has increased, however, more of the AI buildout is being financed through corporate debt, private credit, special-purpose entities, long-term leases, capacity-purchase agreements, and other arrangements that may not be fully visible on the balance sheets of the best-known AI companies.

The Bank for International Settlements has now warned that this growing network could amplify a downturn if anticipated AI revenues and productivity gains fail to justify the scale of investment.[1]

The warning should not be interpreted as a prediction that artificial intelligence will fail or that a financial crisis is inevitable.

AI could produce substantial productivity improvements and generate returns sufficient to support much of the current investment. But technological importance does not guarantee that every company, project, loan, data center, or valuation associated with the technology will succeed.

The internet transformed the economy even though many companies and investors suffered enormous losses after the dot-com boom. Railroads, electricity, and telecommunications all produced lasting economic value while also experiencing periods of excessive investment and financial distress.

The same distinction applies today:

AI can be revolutionary while parts of the AI investment boom remain financially unsustainable.

For U.S. business owners, the immediate question is not whether they should abandon artificial intelligence. It is whether their contracts, financing, data, intellectual property, international operations, and vendor relationships can withstand a sudden change in the AI market.

What the BIS Actually Warned About

The BIS estimates that the five largest technology hyperscalers will spend more than $1 trillion on AI-related capital expenditures during 2025 and 2026.[1]

That spending is helping support economic growth. It is also creating increasingly complicated financial relationships among:

• Technology hyperscalers;

• AI model developers;

• Semiconductor companies;

• Cloud providers;

• Specialized computing providers;

• Data-center developers;

• Construction contractors;

• Energy companies;

• Private credit funds;

• Banks;

• Insurers; and

• Institutional investors.

The concern is not simply that technology-company share prices might fall.

The broader risk is that a decline in AI investment could impair companies whose revenues, loans, leases, construction projects, and valuations depend on the continued expansion of the AI infrastructure market.

If a hyperscaler postpones or cancels data-center projects, the effects could reach contractors, developers, equipment manufacturers, landlords, energy suppliers, lenders, and local businesses that expected to benefit from the project.

If an AI laboratory loses financing, it may reduce its purchases of computing power. That can affect the cloud company or specialized computing provider that built capacity in reliance on the AI laboratory’s commitments.

If private lenders sustain losses in AI-related investments, they may respond by reducing credit to unrelated middle-market companies.

The risk is therefore one of financial transmission.

A problem originating in one part of the AI ecosystem could move through contracts and credit relationships into other industries.

How the AI Boom Is Being Financed

The financing structures behind the AI expansion deserve attention because they determine who bears the loss if projected revenues do not materialize.

Corporate Debt

Large technology companies have increasingly issued debt to finance long-term AI investments.

The BIS reported that hyperscaler corporate-bond issuance exceeded $100 billion in 2025. Much of that debt has maturities exceeding five years, reflecting the long construction and investment horizons associated with data centers and related infrastructure.[2]

Debt can be an efficient way to finance productive assets. The risk arises when the assets do not produce sufficient returns, become technologically obsolete, or depend on customers that cannot fulfill their commitments.

Special-Purpose Entities and Joint Ventures

Some AI infrastructure is financed through separate legal entities rather than directly on a technology company’s balance sheet.

A special-purpose entity may acquire or construct a data center using equity from several investors and debt supplied by private lenders. A hyperscaler may hold only a minority ownership interest while agreeing to lease the facility or purchase computing capacity for many years.

Economically, the hyperscaler has made a substantial long-term commitment. Legally and financially, however, much of the associated debt may remain within the separate entity.

These structures are not inherently improper. They are commonly used in project finance, real estate, energy, transportation, and infrastructure.

The concern is that investors and counterparties may not fully understand:

• Which entity owns the asset;

• Which party guarantees the debt;

• Whether the technology company can terminate its commitment;

• Whether the same asset supports several obligations;

• Who bears construction overruns;

• What happens if anticipated capacity is no longer required; and

• Whether the project can obtain replacement customers.

Private Credit

Private credit funds have become important lenders to technology, software, data-center, and infrastructure companies.

Unlike traditional bank loans or publicly traded bonds, private-credit arrangements may have limited public disclosure. Loan values may also be based on periodic estimates rather than continuous market trading.

The BIS reported that direct-lending funds quadrupled their allocation to AI and information-technology businesses during the preceding five years, reaching approximately 15% of their portfolios. Separate BIS research found that outstanding private loans to software-as-a-service companies had grown from approximately $8 billion in 2015 to more than $500 billion by the end of 2025.[3]

The risk is not confined to companies developing AI.

Some software companies may be disrupted by AI at the same time private lenders are financing the companies building AI infrastructure. A private-credit portfolio could therefore be exposed to both sides of the transition.

Circular Financing

The BIS also identified what it describes as circular financing.

In a simplified example:

1. A semiconductor company or hyperscaler invests in an AI laboratory or specialized cloud provider.

2. The recipient uses the investment or related financing to purchase chips or computing capacity from the investor or an affiliated participant.

3. Those purchases become reported revenue or long-term contractual commitments within the AI ecosystem.

4. The increased revenue and demand support additional valuations, borrowing, or investment.

The arrangement may reflect genuine commercial demand. But when the purchaser depends on financing from the seller or another participant in the same ecosystem, the relationships can make it more difficult to determine how much demand is independently sustainable.

If one participant reduces funding, the same action may reduce another participant’s customer demand and projected revenue.

Why This Matters to Businesses Outside the Technology Industry

A business does not need to own technology stocks or build data centers to be affected.

Credit Could Become More Difficult to Obtain

If AI-related assets are sharply repriced, lenders may become more conservative across their portfolios.

A private-credit fund facing losses or redemption requests may tighten underwriting, increase interest rates, reduce loan sizes, demand additional collateral, or decline to refinance existing borrowers.

That response may affect a manufacturer, professional-services firm, distributor, retailer, or logistics company that has no direct involvement with AI.

Financial institutions respond to uncertainty by reassessing risk. They do not necessarily limit that reassessment to the industry in which the original losses occurred.

Businesses approaching a loan maturity should therefore avoid assuming that current credit terms will remain available.

Customers May Reduce Spending

Companies selling construction, electrical, engineering, real-estate, energy, cooling, security, staffing, software, or consulting services into the AI ecosystem may be especially exposed.

A customer may appear financially strong because it has a significant contract with a prominent technology company. But the business should determine:

• Whether the customer or another entity signed the underlying agreement;

• Whether the agreement can be terminated for convenience;

• Whether revenue depends on construction milestones;

• Whether the customer has received committed financing;

• Whether the project is subject to permits or utility approvals;

• Whether payment depends on financing draws;

• Whether the parent company has guaranteed the obligation; and

• Whether the customer has other meaningful sources of revenue.

A supplier’s financial security should not be evaluated solely by the name of the end user associated with the project.

AI Vendors May Consolidate, Fail, or Change Their Services

Thousands of businesses now depend on AI vendors for customer service, drafting, research, cybersecurity, marketing, analytics, human-resources functions, document processing, and internal decision-making.

Some providers are well capitalized. Others rely on continued venture funding, cloud credits, investor support, or access to computing capacity at favorable prices.

If financing contracts, some AI providers may:

• Increase prices;

• Reduce service levels;

• Limit computing access;

• Eliminate products;

• Sell the business;

• Change subprocessors;

• Modify data-use terms;

• Restrict customer exports;

• Terminate free or discounted plans; or

• Enter insolvency or restructuring proceedings.

The operational question is not merely whether another AI tool exists. It is whether the business can retrieve its data, workflows, prompts, configurations, audit history, and outputs in a form that can be transferred to another provider.

A Technology Sell-Off Could Affect Consumer and Business Demand

The BIS noted that U.S. equities now represent approximately 64% of the MSCI global index. It also observed that household equity exposure has increased relative to both wealth and income.[1]

A major decline in technology valuations could therefore reduce household wealth and consumer confidence. It could also reduce corporate spending, hiring, acquisitions, and investment.

The International Monetary Fund has estimated that a moderate correction in AI-related stock valuations, combined with tighter financial conditions, could reduce global output. The IMF has also recognized the opposite possibility: successful AI adoption could increase productivity and economic growth.[4]

The outcome is not predetermined. Businesses should nevertheless prepare for both scenarios.

The International Effects Could Be Significant

The AI supply chain is inherently international.

Advanced chips may be designed in one country, manufactured in another, packaged elsewhere, installed in a data center in a fourth jurisdiction, and used to process information belonging to customers around the world.

A change in investment or regulation in one country can therefore affect several others.

Semiconductor and Equipment Supply Contracts

AI infrastructure depends on specialized semiconductors, servers, networking equipment, power systems, cooling technology, and construction materials.

Businesses purchasing or supplying these products should address:

• Allocation during shortages;

• Forecasting requirements;

• Noncancelable orders;

• Deposits and progress payments;

• Delivery schedules;

• Price adjustments;

• Currency changes;

• Tariffs and duties;

• Export-license delays;

• Product substitution;

• Technology obsolescence;

• Warranty rights; and

• Treatment of inventory if a project is canceled.

A supplier may demand a noncancelable multiyear commitment because it must reserve manufacturing capacity. The buyer may need that capacity but should understand the cost of reducing its order if AI demand changes.

Export Controls Will Continue to Shape AI Investment

Advanced computing chips, semiconductor-manufacturing equipment, software, and technical information may be subject to the U.S. Export Administration Regulations.

Restrictions may depend on:

• The technical classification of the item;

• Destination;

• End user;

• End use;

• Entity List status;

• Military or intelligence affiliations;

• Semiconductor-manufacturing activity;

• Supercomputer applications;

• Reexports and transfers; and

• Foreign-direct-product rules.

The United States has continued to impose and revise controls affecting advanced computing and China-related AI capabilities.[5]

A decline in AI valuations would not eliminate those restrictions. In fact, financially distressed companies may create additional diversion risk if they attempt to sell equipment, transfer technology, or find replacement customers in restricted markets.

Contracts should prohibit unauthorized resale, reexport, transfer, remote access, and prohibited end uses. They should also provide sufficient rights to investigate the ultimate consignee and suspend performance when necessary for compliance.

U.S. Investment in Certain Foreign AI Businesses May Be Restricted

The U.S. Outbound Investment Security Program regulates certain investments by U.S. persons involving specified artificial-intelligence systems, semiconductor technologies, and quantum technologies connected to China, Hong Kong, and Macau.

Depending on the technology and transaction, an investment may be prohibited or require notification to the U.S. Department of the Treasury.[6]

The rules can be relevant not only to traditional acquisitions but also to certain:

• Equity investments;

• Convertible financing;

• Greenfield investments;

• Joint ventures;

• Limited-partner investments; and

• Transactions involving entities with covered-country connections.

A U.S. investor seeking discounted assets after a market correction must still conduct regulatory due diligence. Financial distress does not make an otherwise prohibited investment permissible.

Similarly, a U.S. company entering a joint venture to acquire data-center capacity, AI models, or technical talent abroad should evaluate outbound-investment and export-control restrictions before signing.

European AI Regulation Will Affect U.S. Companies

Many U.S. AI providers and business users will also encounter European Union requirements.

The EU AI Act applies according to the role of the company, the type of system, the risk classification, and the connection between the AI activity and the European market.

Obligations for providers of general-purpose AI models began applying in August 2025. The European Commission’s enforcement powers concerning those obligations begin in August 2026. Additional transparency requirements concerning certain AI-generated and manipulated content also become applicable in August 2026.[7]

Financial pressure will not excuse noncompliance.

If an AI provider reduces its compliance staff, changes its model, transfers operations, or replaces subprocessors, the provider and its business customers may still have obligations involving:

• Technical documentation;

• Transparency;

• Copyright policies;

• Risk management;

• Model information;

• Human oversight;

• Cybersecurity;

• Recordkeeping; and

• Disclosure of AI-generated content.

U.S. businesses acquiring an AI company, purchasing its assets, licensing its model, or assuming its customer contracts should determine whether they are also inheriting European regulatory obligations.

Cross-Border Data Obligations Do Not Disappear During Financial Distress

An AI provider may process personal, confidential, regulated, or proprietary data in several jurisdictions.

If the provider experiences financial distress or is acquired, customers should know:

• Where their data is located;

• Which legal entity controls or processes it;

• Whether it may be transferred in a sale;

• Which subprocessors have access;

• Whether the customer can retrieve it;

• How quickly the provider must delete it;

• Whether deletion can be verified;

• What happens to backup copies;

• Whether model training rights continue; and

• Which country’s law applies.

A contract provision allowing assignment in connection with a merger or asset sale may permit customer information and contractual rights to move to a new owner.

The customer should consider whether consent, notice, termination, or data-return rights are appropriate when the acquiring party is a competitor, foreign entity, or company operating under different privacy and security standards.

What Happens if an AI Vendor Enters Bankruptcy?

Financial distress presents issues that ordinary software agreements often do not adequately address.

Under Section 365 of the U.S. Bankruptcy Code, a debtor may, subject to court approval and applicable limitations, assume, reject, or assign certain executory contracts.[8]

The precise treatment of an AI, software, cloud, data, or intellectual-property agreement will depend on its terms and the applicable law.

A contractual clause stating that the agreement automatically terminates merely because one party files for bankruptcy may not operate as the customer expects.

The customer may also discover that its prepaid subscription, service credit, implementation deposit, or damages claim is treated as an unsecured claim.

This makes advance planning important.

Businesses should not assume that a general contractual right to “access their data” guarantees immediate operational control during a bankruptcy proceeding.

Contract Protections Businesses Should Consider

No single contract provision can eliminate the risk of vendor distress. Several provisions used together can materially improve a customer’s position.

Financial and Operational Due Diligence

Before entering a critical AI relationship, consider requesting information regarding:

• Ownership;

• Funding history;

• Insurance;

• Financial condition;

• Key subcontractors;

• Computing providers;

• Dependence on a single model or cloud company;

• Business-continuity procedures; and

• Data-center and geographic concentration.

The depth of the review should correspond to the importance of the service.

Data Portability

The agreement should identify:

• What data can be exported;

• Available file formats;

• Whether prompts and configurations are included;

• Whether audit logs are included;

• How frequently exports can occur;

• The cost of export;

• The time allowed after termination; and

• The provider’s deletion obligations.

A right to receive unusable files is not meaningful portability.

Transition Assistance

For critical services, the provider may be required to continue operating for a defined transition period and reasonably cooperate with a replacement vendor.

The contract should address the cost, duration, personnel support, and data transfers associated with the transition.

Service Continuity

Businesses should consider:

• Uptime commitments;

• Disaster recovery;

• Backup requirements;

• Recovery-time objectives;

• Recovery-point objectives;

• Alternative hosting;

• Notice of material financial distress;

• Notice of major service reductions; and

• Rights triggered by repeated failures.

Changes to Models and Subprocessors

An AI provider may depend on a third-party foundation model, cloud service, or specialized computing provider.

The customer should determine whether the provider may replace those dependencies without notice.

A change could affect:

• Accuracy;

• Security;

• data location;

• regulatory compliance;

• intellectual-property risk;

• functionality; and

• pricing.

The customer may need notice, objection, testing, or termination rights when a material dependency changes.

Intellectual-Property Rights

The agreement should identify ownership and permitted use of:

• Customer inputs;

• Prompts;

• Outputs;

• Fine-tuned models;

• Feedback;

• Custom configurations;

• Training data;

• Embeddings;

• Software integrations; and

• Improvements.

It should also address infringement claims, defense obligations, indemnification, exclusions, and the provider’s right to replace or discontinue a challenged product.

Pricing and Capacity Commitments

Long-term capacity agreements should be examined for:

• Take-or-pay obligations;

• Minimum usage;

• Automatic increases;

• Reserved capacity;

• Early-termination charges;

• Credits for unavailable capacity;

• Price-adjustment formulas;

• Benchmarking;

• Most-favored-customer provisions; and

• Rights when the technology becomes obsolete.

A business should avoid purchasing years of capacity merely because it fears being left behind.

Assignment and Change of Control

The customer may require notice or consent before the agreement is assigned to a new entity.

At a minimum, it should consider a termination right if the agreement is transferred to:

• A competitor;

• A sanctioned or restricted party;

• An entity in a high-risk jurisdiction;

• A company lacking adequate security;

• A buyer unwilling to honor existing data restrictions; or

• An entity whose ownership creates regulatory problems.

Limits on Prepayment

Discounted multiyear subscriptions can appear attractive, but substantial prepayment converts the customer into a creditor if the provider fails.

Businesses should compare the discount against:

• Vendor financial risk;

• Recoverability of the payment;

• Available security;

• Escrow arrangements;

• Milestone-based payments; and

• The cost of switching providers.

Businesses Financing AI Projects Need a Different Review

A company borrowing money to build an AI product, data center, or associated infrastructure should evaluate whether its financing assumptions match its contracts.

Important questions include:

• Are customer commitments binding?

• Can the principal customer terminate for convenience?

• Are capacity reservations actually prepaid?

• Does the customer guarantee the project debt?

• Is the loan recourse or nonrecourse?

• Which assets secure the debt?

• Are permits, electricity, land, or equipment conditions to funding?

• Can cost overruns be passed through?

• What happens if chip delivery is delayed?

• Does a customer downgrade create a default?

• Are there cross-defaults among project entities?

• Can the lender accelerate if projected utilization is not achieved?

• Are distributions prohibited if coverage ratios decline?

An impressive customer list does not necessarily mean that project revenue is legally committed.

The financing documents and customer contracts must be reviewed together.

Nine Steps U.S. Businesses Should Take Now

1. Identify Critical AI Dependencies

List the AI, cloud, software, data, cybersecurity, and infrastructure providers whose interruption would materially affect operations.

2. Determine Which Legal Entity Is Obligated

Confirm whether the contract is with the well-known parent company, a subsidiary, reseller, special-purpose entity, or recently formed affiliate.

3. Review Termination and Assignment Rights

Determine what happens if the vendor is acquired, restructures, changes control, discontinues the product, or enters insolvency proceedings.

4. Test Data Portability

Do not merely read the contract. Conduct an actual export and determine whether another system can use the resulting data.

5. Avoid Unmeasured Long-Term Commitments

Require a documented business case before signing multiyear AI, computing, or capacity agreements.

6. Review Financing Exposure

Determine whether AI investments are being funded with variable-rate debt, equipment leases, personal guarantees, or loans containing aggressive financial covenants.

7. Evaluate International Compliance

Examine export controls, outbound-investment restrictions, privacy requirements, data transfers, sanctions, and foreign AI regulations.

8. Create a Vendor-Failure Plan

Identify a replacement provider, transition timeline, data-migration process, responsible personnel, and acceptable period of service interruption.

9. Preserve the Opportunity

Risk management should not become a reason to avoid useful technology. Businesses should continue adopting AI where the investment can be measured, governed, and contractually protected.

How TEIL Firms Can Help

The current AI market presents two distinct risks.

The first is moving too slowly and losing legitimate opportunities to improve productivity, develop new products, serve international customers, and operate more efficiently.

The second is moving too quickly and entering expensive, inflexible, or inadequately protected relationships because a company fears being left behind.

The appropriate legal strategy is not automatic avoidance. It is disciplined adoption.

The Evans International Law Firms, LLC—TEIL Firms—helps U.S. and international businesses evaluate the contracts, intellectual property, financing, data, and trade-compliance issues surrounding AI transactions.

Our services include:

• AI vendor and technology-agreement review;

• Cloud, software, data-processing, and licensing agreements;

• AI procurement and implementation contracts;

• Data ownership, permitted-use, and model-training provisions;

• Intellectual-property and trade-secret protection;

• International data and vendor-risk analysis;

• Export-control and restricted-party review;

• Outbound-investment issue spotting;

• International joint-venture and technology-transfer agreements;

• Data-center, infrastructure, supplier, and capacity contracts;

• Change-of-control, assignment, and insolvency protections;

• Contract renegotiation and risk allocation; and

• Business-continuity and vendor-exit planning.

A targeted AI Contract and Global Risk Review can help a business determine:

• Where it is dependent on a single AI or cloud provider;

• Whether its data can actually be retrieved;

• Who owns its inputs, outputs, and customized systems;

• Whether the agreement permits material price or service changes;

• What happens if the provider is sold or financially distressed;

• Whether international regulations apply;

• Whether long-term commitments are commercially justified; and

• Which protections should be added before the company becomes more dependent on the technology.

Businesses should conduct that review before committing sensitive data, intellectual property, essential workflows, or several years of payments to an AI provider.

Conclusion

Artificial intelligence may ultimately justify enormous investments and transform global productivity.

That possibility does not make every AI investment sound.

The current boom is being supported by increasingly interconnected debt, private-credit, project-finance, lease, capacity-purchase, and investment relationships. If anticipated returns disappoint, losses could move from technology companies into construction, energy, software, financial markets, business lending, and the wider economy.

For U.S. businesses, the correct lesson is not that AI should be avoided.

It is that AI adoption should be treated like any other important international business transaction: with financial due diligence, enforceable contracts, intellectual-property protection, data controls, regulatory analysis, and an exit strategy.

The companies most likely to benefit from AI will not necessarily be those that spend the most or commit the earliest.

They will be those that can adopt the technology without surrendering control of their data, overextending their finances, violating international regulations, or becoming permanently dependent on a vendor whose future they have never evaluated.

This article is provided for general informational purposes and does not constitute legal, investment, tax, or financial advice. The rights and risks associated with a particular AI, financing, software, infrastructure, or international transaction depend on the parties, contract terms, applicable laws, and specific facts.