Table of contents
A. The Basics: Consideration in Traditional vs. Automated Contracts
In traditional contracting, consideration is carefully negotiated and documented. It can be as straightforward as a company paying for a service or as complex as an exchange of mutual obligations, like a business partnership agreement. Lawyers and negotiators ensure that what’s being exchanged is fair, adequate, and enforceable.
In automated contracting, the principle of consideration remains intact, but its execution is radically different. Smart contracts, those self-executing agreements powered by blockchain, automatically transfer cryptocurrency, trigger payments, or release digital assets once pre-set conditions are met. AI-driven platforms match obligations with consideration instantly, ensuring seamless transactions without human intervention.
But here’s the catch: What happens when consideration isn’t just about money? Can AI recognise goodwill, informal services, or future commitments in the same way a human negotiator would? This is where things get interesting.
B. Real-World Use Cases: How Automated Consideration Works in Practice
1. Instant Payments in E-Commerce and Supply Chain Contracts
Imagine a global supply chain where suppliers and buyers no longer deal with late payments or disputes over invoices. Platforms like Tradeshift and SAP Ariba integrate AI-driven smart contracts that release payments automatically upon fulfillment of predefined conditions, such as successful delivery and verification via IoT sensors.
Challenge: What if a shipment is technically delivered, but there’s a defect that a human negotiator might have spotted? Automated systems struggle with subjective assessments like product quality or service satisfaction, which can lead to unintended transactions.
2. Decentralised Finance (DeFi) and Crypto-Based Consideration
In DeFi lending platforms like Aave or Compound, borrowers receive loans by locking up crypto assets as collateral. The smart contract enforces repayment by automatically liquidating assets if the borrower fails to meet obligations. Consideration here isn’t just cash, it’s digital assets with fluctuating value.
Challenge: Unlike traditional banks that may renegotiate loan terms based on borrower hardship, smart contracts execute mechanically. What if the borrower’s collateral crashes in value due to market volatility? Automated contracting lacks the flexibility that human decision-makers provide.
3. AI-Powered Subscription Agreements and Digital Services
Services like ChatGPT Plus, Perplexity AI Pro, or AWS cloud subscriptions operate on automated contracts where payments are deducted based on usage. The AI assesses the user’s plan and adjusts consideration dynamically, no human intervention required.
Challenge: What if an AI miscalculates usage? If a company’s AI overcharges for API calls or server bandwidth, does an automated contract leave room for dispute resolution, or is the customer forced to accept machine-driven billing errors?
4. Non-Monetary Consideration in AI Partnerships
Companies collaborating on AI research often enter into agreements where consideration isn’t cash, it’s data, algorithms, or intellectual property rights. For example, an AI startup might grant a corporation access to its proprietary machine learning model in exchange for cloud infrastructure credits.
Challenge: Unlike clear-cut financial transactions, the value of data and algorithms is subjective. Can AI-driven contracts fairly assess whether one party’s contribution is equal to another’s? What happens if one side feels shortchanged?
5. Custobots and AI-Powered Consumer Transactions
With Custobots (AI-powered purchasing assistants), consumers are no longer manually accepting offers; instead, their digital assistants autonomously negotiate and agree to terms. Say your Custobot automatically books a flight for you at the lowest price, what if the airline later claims the fare was an error?
Challenge: Can automated contracting ensure fairness when one party (the consumer) doesn’t even manually review the contract? If AI systems misinterpret pricing glitches as legitimate offers, is the contract enforceable?
As these examples show, automated contracting performs well when value is clearly defined and measurable, but it struggles when nuance or subjectivity enters the picture.
C. Legal and Business Challenges: What You Need to Watch For
1. Recognition of Non-Monetary Consideration
Automated systems are great at handling structured inputs like currency or token transfers. But what happens when the “value” being exchanged is goodwill, shared data, or a collaborative effort that unfolds over time? Traditional contracts can acknowledge and protect intangible contributions, but AI-driven platforms are still learning how to “see” these forms of value. If your deal involves co-branding rights, algorithmic improvements, or IP licensing, make sure there’s human oversight. The tech just isn’t there yet to fully understand abstract or relational consideration.
2. Dispute Resolution in Automated Consideration
When contracts execute automatically, mistakes can be costly, and fast. If an AI system misfires and transfers funds prematurely or assigns value incorrectly, how do you fix it? Some blockchain-based platforms are experimenting with dispute resolution protocols, but most systems lack a built-in "undo" button. Businesses need to build in failsafe clauses, manual override options, or dispute resolution layers (like oracles or human arbitration triggers) to safeguard against errors that arise in fully automated consideration exchanges.
3. Regulatory and Compliance Issues
Let’s face it, contract law isn’t uniform across borders. What counts as sufficient consideration in California might not fly in Germany. And if your AI system is auto-executing contracts across regions, it needs to understand those nuances. Spoiler alert: most don’t. Businesses deploying automated contracting tools must ensure they’re embedded with jurisdictional filters or pre-programmed with legal boundaries to avoid violating local laws, especially in highly regulated sectors like finance, insurance, or healthcare.
4. Flexibility vs. Rigidity
Smart contracts are brilliant at sticking to the script, but what if the script needs to change? In real life, parties renegotiate, waive terms, or revise expectations mid-stream. Automated contracts, by design, are rigid; they do what they’re told, even if business needs shift. To counter this, companies can explore hybrid contracting models that allow AI to handle execution but leave room for human input at critical junctions, like pausing execution, amending consideration terms, or revisiting agreement scopes.
D. Final Thoughts: Is the Future of Consideration Fully Automated?
Automated contracting is transforming business efficiency, but it’s not without its pitfalls. As AI and smart contracts continue to reshape industries, businesses must carefully navigate the trade-off between speed and flexibility, automation and human oversight.
At the end of the day, consideration is what makes a contract meaningful. Whether you’re in e-commerce, finance, AI development, or supply chain management, the key question is: can your automated contracting strategy account for the complexities of real-world value exchange? To find out get in touch with White Bison.
