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Converged Workloads: Enabling Real-Time Enterprise Intelligence and AI Innovation

Publisher IDC
Published Dec 06, 2025
Length 8 Pages
SKU # IDC20635551

Description

This IDC Perspective explores how hybrid transactional/analytical processing (HTAP), or converged workloads, is redefining enterprise data architecture. By combining transactional reliability with analytical intelligence, these environments eliminate latency between data creation and insight, enabling real-time decision-making, continuous intelligence, and the seamless use of AI within business operations.This document examines the technologies, market dynamics, and adoption strategies driving this convergence and provides guidance for IT and data leaders modernizing their database environments to support greater agility, intelligent automation, and accelerated AI-driven innovation."AI and automation depend on accurate and timely data. Converged workloads transform databases from static systems of record into living systems of intelligence, where every transaction becomes an opportunity for reasoning, adaptation, and action." — Devin Pratt, research director, Data Management, IDC

Table of Contents

8 Pages

Executive Snapshot

Situation Overview

The Rationale for Convergence

Technology Drivers Behind HTAP

Agentic AI as the Catalyst for Real-Time Data

Industry Momentum Toward Converged Workloads

IT Impact

Simplification and Autonomy

Performance and Scalability

Security and Governance

Business Impact

Real-Time Decisioning and Continuous Intelligence

Agility and Competitiveness

Accelerating Innovation

Advice for the Technology Buyer

Focus on High-Value, Real-Time Use Cases

Embed Governance and Observability Early

Adopt AI-Embedded Databases

Plan for Agentic AI Integration

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