AI Deployment Patterns for Business
Common patterns for deploying AI in business. From pilot to production.
Common patterns
Wrapper: Wrap existing process with AI layer. Lowest risk, lowest reward.
Embed: AI inside existing applications. Moderate risk and reward.
Replace: AI replaces existing process. Higher risk, higher reward.
New capability: AI enables previously impossible capability. Highest risk and reward.
Production considerations
Latency, accuracy, cost, monitoring, fallback. Each requires specific architecture decisions.
Bottom line
Match deployment pattern to risk tolerance and value potential.
Frequently asked questions
How to deploy AI in production?
Pilot first, measure, refine, scale. Pattern depends on risk tolerance and use case. Start with bounded deployments.
What deployment pattern is safest?
Wrapper pattern lowest risk. Augments existing process. Easier to roll back. Limited upside also.
When to replace process with AI?
Mature use cases, high confidence in AI quality, manageable failure modes. Higher reward but higher risk.
Fallback strategies?
Critical for production. Human escalation, alternative service, cached responses. Plan for AI failures.
Monitoring AI in production?
Quality metrics, latency, cost, errors. Continuous monitoring with alerts. Quality drift happens.
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