As enterprises race to modernize supply chains and core operations, AI is muscling its way into the world of smart contracts. Business leaders are discovering that AI-enhanced smart contracts and analytics tools can unlock new efficiencies—but only if they’re deployed with the same rigor they promise to automate.
AI-enhanced smart contracts do come with significant challenges. Without careful implementation, they can introduce new vulnerabilities, from biased or poor-quality data feeding automated decisions to opaque algorithms that complicate audits or dispute resolution. Yet when these systems are built on clean data, transparent governance and interoperable architecture, the upsides are substantial. Faster execution, real-time quality checks and predictive insights can streamline operations and generate measurable ROI, especially in complex supply chains where small efficiencies multiply quickly.
Blockchain pioneers have a unique vantage point in this moment. They’ve spent years navigating immutable ledgers, decentralized architectures and cross-platform integrations—precisely the terrain where AI-enabled contracting now lives. Here, two members of the Senior Executive Blockchain Think Tank—experts in blockchain, distributed ledger technology, smart contracts and more—discuss why and how businesses should implement AI-enhanced smart contracts.
“By balancing strategy, governance, risk management and controls, companies can realize value while keeping their operations safe.”
Set Clear Goals and Favor Open Standards
Bojan Ilic has spent more than 30 years helping organizations navigate risk, security and complex global operations. As Chairman and Global Director of Swiss Security Solutions LLC, he works with clients who need high-assurance systems that can stand up to operational pressure. That perspective shapes how he views AI-enhanced smart contracts: full of promise, but only valuable when guardrails are as strong as the automation itself.
“Smart contracts with AI can make things more efficient, build trust and save money—but they also come with risks,” Ilic says.
He emphasizes that clarity and alignment must come before deployment. That includes avoiding closed ecosystems that limit transparency and slow down adaptation when conditions shift, as well as building contracts that can evolve responsibly.
“Companies should set clear goals and choose vendors with open standards,” Ilic says. “Make sure code is audited and can be updated, and allow cross-platform integration.”
For Ilic, the strategic payoff of AI-enhanced smart contracts is real but can only be achieved when their implementation is executed with care and due diligence.
“By balancing strategy, governance, risk management and controls, companies can realize value while keeping their operations safe.”
“Don’t rely on demos. Require live-data results and stress-test with your own volumes.”
Demand Transparency and Test Real-World Performance
Donna Mitchell is a digital transformation specialist specializing in AI, Web3 and healthcare innovation. Now serving as CEO of Mitchell Universal Network LLC, she helps C-suite leaders home in on technology that drives measurable ROI. Her take on AI-enhanced smart contracts is clear: The value is there, but only when businesses look past demos and understand how these systems behave under real operational stress.
“AI-enhanced smart contracts speed execution, cut errors and enforce compliance, but their value depends on data quality and vendor maturity,” Mitchell explains.
Their real advantage, she says, lies in automations that help leaders stay ahead of issues instead of reacting to them: predictive alerts, quality checks and instant audit trails. Those capabilities can help enterprises catch problems before they cascade across the supply chain and create expensive downstream delays.
However, Mitchell cautions leaders not to be swayed by impressive vendor pitches, adding that it’s essential to validate performance—and not just by looking at track records. AI systems that run flawlessly in controlled environments can falter when exposed to the scale, variability or complexity of actual business operations.Â
“Don’t rely on demos,” she says. “Require live-data results and stress-test with your own volumes.”
Mitchell also recommends favoring open, interoperable systems to prevent lock-in and demanding transparent AI governance to ensure trust, accountability and resilience. And for companies just getting started?
“Build in human oversight and auditability. Start small, then scale.”
Practical Moves to Strengthen AI-Enhanced Contracting Strategies
- Set clear goals before deploying AI-enhanced smart contracts. Establishing what the contract must accomplish helps prevent misalignment and reduces the risk of implementing features that add complexity without boosting performance.
- Choose vendors that use open standards. Open standards offer more flexibility, improve transparency and help companies avoid being boxed into rigid or proprietary ecosystems.
- Ensure contract code is audited and updatable. Regular audits and the ability to revise code help organizations maintain security and adapt quickly to operational or regulatory changes.
- Allow for cross-platform integration from the start. Interoperability reduces friction across partners and systems, making automation more reliable and scalable.
- Validate vendor maturity with live-data testing. Real operational inputs reveal whether a solution can handle your organization’s scale, complexity and performance requirements.
- Look past demos and stress-test with your own volumes. Controlled scenarios rarely expose weaknesses that surface under production-level conditions.
- Leverage predictive alerts, automated quality checks and audit trails. These capabilities strengthen compliance, improve decision-making and help teams detect issues before they become costly.
- Build in human oversight and auditability. Even the most sophisticated AI requires human judgment to ensure accountability, guide exceptions and maintain trust across stakeholders.
Turning AI-Powered Contracts Into Enterprise Advantage
AI-enhanced smart contracts have the potential to become a defining feature of modern enterprise operations, yet their success hinges on choices leaders make right now. The technology’s value emerges only when organizations pair ambition with discipline, demanding transparency, interoperability and real-world validation long before automation goes live.
As AI becomes more tightly woven into contracting and supply chain systems, companies that build resilient, auditable and adaptable architectures will not only reduce risk, but also position themselves to compete in markets where speed and accuracy define advantage. When businesses approach AI-enhanced smart contracts with clear goals, rigorous testing and strong governance, they can translate automation into meaningful operational gains.
