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IQVIA

iqvia.com · Health Care and Social Assistance · 73,662 employees

CompetitiveAgentic with governance#64

This score estimates how ready the organization appears to be to turn distributed AI experimentation into governed, reusable data workflows.

Score
83/100
Grade
A-
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Readiness snapshot

IQVIA is currently at the ai mature / scaled stage of the agentic data journey. Visible strengths include AI-Native Build Capacity and Talent + Leadership. The clearest next opportunity is AI Hiring Investment / Momentum. The score is based on observable technology, hiring, team, and leadership signals.

What this stage means

Stage · AI mature / scaled

The organization shows a production-shaped pattern across data, agents, evaluation, momentum, and leadership. The next challenge is organizational leverage: one trusted context and collaboration layer for humans and agents across the business.

The six conditions for governed agentic scale

The score rewards a connected operating pattern. No single model, tool, or hiring signal is enough on its own.

01 · Data Foundation
Is the underlying data layer usable by humans and agents? We look for modern warehouse or lakehouse infrastructure, ingestion, transformation, orchestration, BI, and retrieval or vector signals.
21.5/23
Strong
02 · AI-Native Build Capacity
Can the organization build agentic workflows, not just access a model? We look for agent frameworks, agent builders, MCP, AI workflow tooling, and AI-native technology breadth.
16.0/16
Strong
03 · Stack Balance / Tool Mix Quality
Do the visible tools form a coherent path from data to production? We assess whether modern data, retrieval, agents, and evaluation appear as a connected system.
12.3/13
Strong
04 · Eval, Observability, Governance
Can the organization measure, monitor, and control what its AI systems do? We look for evaluation, observability, safety, and governance signals.
9.3/14
Competitive
05 · AI Hiring Investment / Momentum
Is the organization actively investing in agentic capability? We measure recent hiring signals, project-level AI language, team breadth, and the seniority of hiring.
12.2/22
Partial
06 · Talent + Leadership
Is there visible ownership for scaling the work? We look for senior AI and data talent, leadership roles, and the highest role seniority detected.
12.0/12
Strong

Visible stack signals

Publicly observable technologies help indicate whether the organization has a coherent path from data to retrieval, agentic workflows, evaluation, and production.

Tool-mix flags
warehouse/lakehousetransformationdata orchestrationBIretrieval/vectorLLM provider/modelagent frameworkeval/observabilitylegacy analytics
Matched technologies
AWS RedshiftAWS SagemakerAi AgentsAlteryxAnthropic ClaudeApache AirflowApache ParquetApache SparkAzure Data FactoryAzure MLClouderaCursorDatabricksFAISSGoogle BigQueryGoogle GeminiH2O.aiIBM NetezzaInformatica PowerCenter / SuiteLangChainLangGraphLangSmithLookerMLFlowMcpMeta LlamaMicroStrategyMicrosoft CopilotMicrosoft Power BIMicrosoft SSISMilvusOpenAI ChatGPT / GPTPineconePolarsPrefectQlik (umbrella)Qlik SenseRaySisenseSnowflake

Hiring and ownership signals (last 3 months)

Recent hiring signals show whether capability is becoming an organizational priority, not just a technical experiment.

Matched AI jobs
155
Total jobs
1,974
AI job share
7.8%
Project AI mentions
18
Senior agentic roles
44
AI leadership
32
Distinct job functions
42
JD tech mentions
302

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Talk to the team about the next stage of your agentic data journey.

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