AI Readiness Checklist for Growth-Focused Pharma Companies in India

Make smarter moves with AI. Find your true starting point, spot quick wins, and build a practical roadmap for scale.

A comprehensive assessment tool by Impactplus Ventures LLP

What you'll get

A clear snapshot of your current AI maturity

Priority areas to fix first

Identify quick wins and critical improvements

An action plan your team can follow

Practical steps to scale AI adoption

How it works

Rate each item, then calculate your AI Readiness Score.

✓ Fully in place | ◐ Partially implemented | ✗ Not yet addressed

Score: 0/160 Start
0/80 answered

Begin Your Assessment

Rate each item below based on your organization's current state. Your progress will be saved automatically.

1 Leadership & Strategic Alignment

Vision & Buy-in

Senior leadership has a clear vision for AI adoption in commercial operations
AI initiatives are linked to specific business outcomes (revenue growth, market share, productivity)
Budget allocation exists for AI pilots and scaling (minimum 2-3% of total marketing budget)
Board/Leadership discussions include AI as a strategic agenda item quarterly
Clear ownership defined for AI transformation (CTO/President)

Strategic Framework

AI use cases prioritized based on ROI potential and feasibility matrix
Documented AI roadmap aligned with 3-year business strategy
Success metrics defined for each AI initiative (prescription growth %, sales productivity)
Risk assessment completed for AI adoption (compliance, data security, change resistance)
Competitive analysis done on peer companies' AI initiatives
Section Score: 0 / 20

2 Data Foundation & Infrastructure

Data Quality & Availability

CRM/SFA adoption above 80% with regular, quality data entry by field force
Historical sales data available for at least 24 months (SKU-wise, territory-wise)
Doctor master database maintained with speciality, prescription potential, tier classification
Marketing spend data tracked by Promo Activity type and campaign
Competitor intelligence systematically collected and digitized

Technical Infrastructure

Cloud infrastructure or hybrid setup for data storage and processing
API integration capabilities with existing systems (ERP, CRM, BI)
Data governance policies defined (access controls, retention, privacy)
Regular data backup and disaster recovery mechanisms
Mobile/tablet infrastructure for field force digital enablement

Data Compliance

DPDP Act (2023) compliance framework implemented
HCP consent management system for digital communications
Data processing agreements with vendors/partners
Audit trail mechanisms for regulatory reporting
Information security policies aligned with ISO 27001 or equivalent
Section Score: 0 / 30

3 Organizational Capabilities

Digital Fluency Assessment

PMT members/Sales Managers/support staff at Corporate Office have basic understanding of AI/ML concepts (>60% score in assessment)
Zonal/Regional managers comfortable with data-driven decision making
Field force uses digital tools beyond basic CRM (e-detailing, WhatsApp business)
Marketing team experienced with digital analytics tools
IT team has cloud and API management capabilities

Skills & Training

AI literacy training plan exists for different roles
Internal champions/power users identified for AI initiatives
Partnership with training providers for upskilling programs
Documentation of best practices and use cases
Regular knowledge sharing sessions on AI applications

Culture & Change Readiness

History of successful technology adoption (ERP, CRM, digital marketing)
Open culture encouraging experimentation and learning from failures
Performance metrics include adoption of new tools/processes
Cross-functional collaboration mechanisms exist
Employee feedback channels for technology initiatives
Section Score: 0 / 30

4 Use Case Prioritization

Sales Force Optimization

Check areas ready for AI implementation:

Territory alignment
Call planning and HCP prioritization
Performance tracking and coaching (tools for Sales Review meets)
Incentive simulation and optimization
Attrition prediction and talent management

Marketing Excellence

Check areas ready for AI implementation:

Brand positioning and message testing
Campaign ROI measurement and attribution
Content marketing for HCP segments
Channel/Promo mix optimization
Competitive intelligence and response strategies

Strategic Planning

Check areas ready for AI implementation:

Demand forecasting by SKU/geography
New product launch planning
Portfolio optimization and resource allocation
Scenario planning
Resource Allocation
Section Score: 0 / 30

5 Implementation Prerequisites

Vendor & Partnership Readiness

Criteria defined for AI vendor selection
Proof of Concept (PoC) framework established
Integration requirements documented
SLA and performance benchmarks defined
Exit clauses and IP ownership clarified

Pilot Design

Pilot scope defined (geography/BU/brand)
Success criteria and go/no-go gates established
Pilot team identified with clear roles
Testing and validation protocols ready
Scale-up plan documented

Risk Mitigation

UCPMP compliance check for AI-generated content
Bias detection and fairness protocols
Explainability requirements for AI decisions
Fallback plans for system failures
Change management communication plan
Section Score: 0 / 30

6 ROI & Business Case

Financial Planning

TCO (Total Cost of Ownership) model for 3 years
ROI calculations for priority use cases
Budget allocation for licenses, implementation, training
Outcome-based pricing models explored
Cost-benefit analysis vs. traditional approaches

Value Measurement

Baseline metrics captured for before-after comparison
KPI dashboard design for AI initiatives
Attribution methodology for AI impact
Regular review cadence established (monthly/quarterly)
Success stories documentation process
Section Score: 0 / 20

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