If you own an application with validation workflows, this is for you. There's a practical way to add AI that helps your team make better decisions—without replacing them, without security risks, and without a massive investment.
The idea is simple: put AI before your validation workflow. Let it analyze incoming data, flag issues, and provide recommendations. Your team still makes the final call. AI assists; humans decide.
What This Looks Like
How It Works
Your application sends data points to AI before the validation workflow. AI analyzes and returns recommendations. The workflow presents these to your team. They review, apply judgment, and decide.
That's it. No black-box automation. No removing humans from the loop.
Why This Matters
What you get:
- Faster decisions: AI pre-screens data and highlights what needs attention. Your team focuses on what matters.
- Better accuracy: AI catches patterns humans might miss. Humans catch context AI might miss. Both together are stronger.
- Consistent analysis: Every data point gets the same level of scrutiny. No more variations based on workload or fatigue.
- Audit trail: AI recommendations are logged. You can see what AI suggested and what humans decided.
Real impact: Teams report 40-60% reduction in review time for routine decisions, with better catch rates on anomalies.
Security: Sorted
Your data stays inside the enterprise. The corporate AMP AI platform handles this.
- No external APIs: AI runs inside your security perimeter.
- No data leakage: Nothing goes to third-party services.
- Full compliance: Meets existing data governance requirements.
- Audit ready: Complete logging of all AI interactions.
You focus on integration. The platform handles infrastructure and security.
The Operating Model
Two teams make this work:
AMP AI Platform Team
Owns infrastructure, security, model hosting. You consume their APIs.
AI COE (Your Level)
Builds integrations, tailors AI to your workflows, works with your business SMEs.
The AI COE Team You Need
Start lean. You need 4 people:
Recommended Team (4 Members)
| Role | What They Do |
|---|---|
| AI Solution Lead | Coordinates with AMP AI platform, manages delivery, talks to business stakeholders |
| Full Stack Developer | Builds the integration between your app and AMP AI, handles data pipelines |
| Prompt Engineer | Designs AI prompts, tunes response quality, handles edge cases |
| Data Engineer | Prepares data for AI consumption, ensures quality, optimizes throughput |
This team works with your existing Application Owners (who know the codebase) and Business SMEs (who own testing and validation).
Business SMEs own testing. They validate that AI recommendations actually make sense for your operations. Technology builds; business validates.
How to Enable This
Four steps to go live:
Pick One Workflow
Start with a single validation workflow that has clear data inputs. Don't boil the ocean.
Set Up the Team
Assign your 4-person AI COE. Connect with the corporate AMP AI platform team for API access.
Build + Test
Integrate your app with AMP AI. Run in shadow mode first—AI recommends, but doesn't block anything. Business SMEs validate outputs.
Go Live + Expand
Once validated, enable AI recommendations in the live workflow. Then pick the next workflow.
What Success Looks Like
You'll know it's working when:
- Your team spends less time on routine reviews
- Anomalies get caught earlier
- Decision consistency improves
- Your SMEs trust the AI recommendations (and know when to override them)
The goal isn't AI making decisions. It's AI making your team's decisions faster and better.
Next Step
If you own an application with validation workflows:
- Identify one workflow where AI analysis would help
- Talk to your leadership about standing up a small AI COE
- Connect with the corporate AMP AI platform team
Start small. Prove value. Scale from there.
