Module 03

From Hype to Value:
Strategic Implementation

The most common failure mode in enterprise AI is "Solution in Search of a Problem". Successful adoption starts with identifying high-value friction points in your business, not with the technology itself.

1

To AI, or Not to AI?

AI is expensive and probabilistic. If a task can be solved with a simple rule (e.g., calculating tax), do not use AI. AI shines in messy, unstructured, and creative tasks where traditional code fails.

To AI, or Not to AI?

AI is powerful, but it's not a magic wand. Knowing when NOT to use AI is just as important as knowing when to use it.

Select a Problem Scenario

Calculate Monthly Tax

Computing exact tax based on fixed government brackets.

Recommended ApproachTraditional Code

Deterministic. Rules are fixed and explicit. AI is overkill and prone to minor errors (hallucinations) where precision is mandatory.

Benefit: Accuracy & Low Cost
2

The GenAI Value Spectrum

Generative AI is more than just chatbots. It is a creative engine, a coding partner, and a research analyst. Explore the different modalities of GenAI application below.

The GenAI Value Spectrum

From productivity boosters to creative engines.

Input Prompt
"How do I reset my router?"
Model Output
To reset your router, locate the small button on the back...
3

Selecting the Right Engine

You don't need a Ferrari to go to the grocery store. Similarly, you don't need GPT-4 for simple summarization tasks. Matching the model size (Nano, Pro, Ultra) to the task complexity is key to economic viability.

Model Selection Framework

Matching the engine to the vehicle.

Primary Constraint
Recommendation

Frontier Models

Highest intelligence. Best for coding, complex analysis, and creative writing. High latency and cost.

Example Models
GPT-4o, Gemini 1.5 Pro, Claude Opus
Reasoning
Speed
Cost
4

Measuring Success

How do you justify the investment? We translate technical metrics (like latency and token usage) into business KPIs (like productivity gains and customer retention).

Business Objective Alignment

Translating model performance into P&L impact.

+40% Efficiency

Productivity

Technical MetricTokens/Sec & Accuracy
Business KPITask Completion Rate
+15% Retention

User Engagement

Technical MetricRelevance Score (BERT)
Business KPISession Duration / Retention
-30% OpEx

Cost Optimization

Technical MetricContext Window Usage
Business KPICost per Transaction

Measuring Business Value

Moving beyond "Perplexity" to metrics that drive the P&L.

Key Performance Indicators (KPIs)

40%
Deflection Rate

Percentage of tickets handled without human agent.

-85%
Cost per Ticket

Reduction in operational cost per resolution.

+15%
CSAT Score

Improvement in customer satisfaction (24/7 availability).

The Strategy is set. Now let's build.

Understand the architecture required to execute this strategy effectively.

Go to Module 4: Architecture