Ten Criteria to Use in Clearly Defining Dispute Resolution Processes and AI Workflows

Jim Bergman

As artificial intelligence becomes more embedded in contract management, procurement, and shared services, the need to define dispute resolution processes that integrate both human and machine workflows is growing. Whether you’re managing supplier disagreements, customer claims, or internal compliance issues, clarity in how disputes are resolved – and how AI supports that resolution – is essential.

Here are ten criteria to guide the definition of dispute resolution processes and AI workflows, with examples from healthcare, education, manufacturing, logistics, finance, and faith-based organizations.

1. Contractual Alignment

Ensure that dispute resolution workflows are grounded in the contract’s terms. AI systems should be trained to recognize triggers based on specific clauses, timelines, and thresholds.

Example: A healthcare AI system flags a breach when service levels fall below the contractual minimum for three consecutive months.

2. Trigger Definition and Thresholds

Clearly define what constitutes a dispute trigger – missed milestones, non-performance, data anomalies – and set thresholds for AI detection and human review.

Example: In manufacturing, an AI model identifies a dispute trigger when defect rates exceed 2% for two consecutive shipments.

3. Stakeholder Mapping

Identify who is involved at each stage – legal, procurement, operations, AI analysts – and clarify their roles in both manual and automated workflows.

Example: A university’s facilities contract includes AI-generated alerts, but escalation decisions are made by the campus operations team.

4. Data Traceability and Auditability

Ensure that all AI-generated decisions and dispute flags are traceable to source data. Human reviewers must be able to audit the logic and evidence behind each alert.

Example: A logistics firm uses AI to detect delivery delays, but each alert includes GPS logs, timestamps, and vendor communication history.

5. Communication Protocols

Define how disputes are communicated – tone, channel, timing – and ensure AI-generated messages are reviewed for clarity and relational appropriateness.

Example: A faith-based nonprofit uses AI to draft initial dispute notices, but ministry leaders review and adjust tone before sending.

6. Resolution Pathways

Outline the steps for resolution – negotiation, mediation, arbitration – and specify which are AI-supported and which require human judgment.

Example: A financial institution uses AI to recommend remediation plans, but final approval comes from compliance officers.

7. Integration with Operational Systems

Embed dispute resolution workflows into existing systems – contract management platforms, ERP tools, CRM dashboards – so AI can act on real-time data.

Example: A retailer’s AI system integrates with its inventory and vendor portals to detect and resolve promotional misalignments.

8. Flexibility and Override Mechanisms

Allow human stakeholders to override AI decisions when context or relational nuance requires it. Document overrides for learning and refinement.

Example: A hospital overrides an AI-generated breach notice due to a vendor’s documented emergency response delay.

9. Confidentiality and Ethical Safeguards

Ensure that AI workflows respect confidentiality, data privacy, and ethical boundaries – especially in sensitive sectors like healthcare and faith-based services.

Example: A ministry’s AI system redacts donor data before generating dispute summaries for external review.

10. Continuous Learning and Feedback Loops

Design workflows to learn from each dispute – whether resolved by AI or humans – and refine future detection, messaging, and escalation logic.

Example: A construction firm’s AI system updates its risk model after each dispute resolution, improving future accuracy.

Final Thought: Structure Enables Wisdom

Defining dispute resolution processes and AI workflows is not just about automation – it’s about stewardship. These ten criteria help organizations build systems that are clear, fair, and adaptive. Whether you’re managing contracts in the public sector, education, logistics, or ministry work, clarity in how disputes are detected, communicated, and resolved is the foundation of trust and performance.

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Published by Jim Bergman

Jim Bergman is a commercial contract professional with global experience spanning the USA, Latin America, UK, Europe, China, South Korea, Japan, India, SE Asia, the Middle East, Africa and Australia. He has worked on a wide range of direct and indirect spend categories in numerous sectors, developing a deep knowledge of services, goods and technology procurement and sales. Across this wide array of commodity and services experience, Jim has found the keys to success in maximizing value for money through customer-supplier relationships founded on innovative category management and strategic sourcing practices, key performance metrics and measures, as well as Total Cost of Ownership principles and collaborative contracting tenets. He has shared his knowledge through advisory engagements, as well as in developing and delivering training programs both on-line and in classrooms, in both open-enrollment and internal environments. Jim has assisted his clients through all phases and steps of contracting, negotiation, strategic sourcing and bidding processes, demonstrating value generation in excess of $250 million. His audiences and clients have included over 7,000 attorneys and commercial professionals students from over 1,000 corporations and public-sector entities.

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