White Paper

Technology Adoption Roadmap for Data and Analytics

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Gartner’s 2024 Technology Adoption Roadmap for Data and Analytics helps data, analytics, and IT leaders benchmark which technologies matter most for AI readiness. Covering 36 technologies and techniques, the roadmap shows where organizations are investing across AI-ready data, analytics and AI, and AI-ready governance. It helps businesses prioritize adoption plans, assess deployment risk, identify value drivers, and prepare their teams, data, and governance models for AI at scale.

As organizations move from AI pilots to real business adoption, execution remains difficult. The roadmap highlights that 75% of surveyed technologies are still being piloted, only 48% of AI POCs reach production, and the average POC-to-production timeline is 8.2 months. Talent availability, value measurement, governance, and AI-ready data remain major challenges. This whitepaper helps leaders understand which data and AI technologies are mature, valuable, risky, or still emerging.

What’s Inside

AI-Ready Technology Roadmap: A view of 36 technologies across AI-ready data, analytics, AI, and governance.
Adoption Status: Which technologies are in planning, piloting, deployment, or already deployed.
AI Readiness Challenges: Why many organizations still struggle to move AI from pilot to production.
Talent Constraints: How talent unavailability slows adoption of emerging data and AI technologies.
Business Value Drivers: How AI-ready technologies improve speed, agility, productivity, resilience, and business value.
AI-Ready Data: Which data technologies are helping organizations prepare for AI at scale.
Analytics and AI Technologies: Key areas such as GenAI, machine learning, foundation models, NLP, and decision intelligence.
AI-Ready Governance: Why governance, AI TRiSM, responsible AI, digital ethics, and ModelOps are becoming critical.