AI in data integration market seen reaching $54.07 billion by 2030

The Business Research Company says the artificial intelligence in data integration market is expanding quickly, rising from $23.42 billion in 2025 to a projected $54.07 billion by 2030. Growth is being driven by rising enterprise data volumes, cloud adoption and demand for automation as companies try to manage more complex data flows.

Why it matters: - AI is becoming a core tool for companies trying to manage larger, faster and more complex data environments. - The market’s growth points to stronger demand for automation, governance and analytics across enterprise systems. - The shift matters for organizations that need cleaner data, faster integration and better decision-making.

What happened: - The Business Research Company released an updated report on the artificial intelligence in data integration market on September 15, 2026. - The market was valued at $23.42 billion in 2025 and is projected to reach $27.76 billion in 2026. - The report forecasts the market will grow to $54.07 billion by 2030. - North America was the largest regional market in 2025. - Asia-Pacific is expected to post the fastest growth over the forecast period. - The report covers Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, the Middle East and Africa. - The report is available as a free sample and as the full market report.

The details: - The report says the market is growing at a 18.6% CAGR from 2025 to 2026. - It projects an 18.1% CAGR through 2030. - Enterprise data growth, cloud platform adoption, business intelligence demand, expanding enterprise application ecosystems and pressure to improve operational efficiency are fueling current growth. - Future growth is tied to generative AI adoption, predictive analytics demand, hybrid and multi-cloud expansion, tighter data governance rules and higher investment in intelligent automation. - Emerging trends include real-time data synchronization, self-service integration platforms, automated governance and compliance, API-driven connectivity and metadata-based integration frameworks. - AI in data integration uses machine learning and automation to connect, merge and harmonize data from different sources. - The approach is designed to improve processing speed, accuracy, adaptability, data quality, consistency and accessibility while reducing manual work. - The report highlights a rise in demand for AI-powered systems that can automate ingestion and scale across high-throughput sources. - In March 2024, Edge Delta said about 120 zettabytes of data were generated worldwide in 2023. - Edge Delta said that works out to about 337,080 petabytes a day and roughly 15.87 terabytes per person per day based on 5.35 billion internet users.

Between the lines: - The market outlook reflects a broader enterprise shift from manual data handling to automated integration layers. - The strongest demand appears to be coming from companies that need to combine governance with speed as data sources multiply. - Asia-Pacific’s faster growth suggests the next wave of adoption may come from markets still building out cloud and AI infrastructure.

What's next: - The market is expected to keep expanding as generative AI, hybrid cloud setups and automation tools become more embedded in enterprise workflows. - Demand should remain concentrated around real-time integration, compliance automation and API-based connectivity. - The report says future updates will include market attractiveness scoring, TAM analysis, company scoring matrices, Excel forecasting dashboards, hotspot infographics and updated graphics and tables.

The bottom line: - AI in data integration is moving from a niche efficiency play to a larger enterprise infrastructure market, with growth supported by rising data complexity and stronger automation needs.