AI驱动集成

Table ofContentsAI-Driven Integration Evolution01Convergence of AI and Integration Platforms02Overcoming Key Challenges03Realizing the Future Benefits of AI05Effective by Design06Planning for Success with IntegrationPowered by AI04 explored how staying ahead of technologicalchange—whether through cloud, big data, mobile, IoT,or AI—enables a seamless information flow acrossapplications, partners, and devices. A strategicapproach to integration is central to that vision.Industry data backs this up. According toGartner®2“by2028, 75% of spend will be on software withgenerative AI (Gen AI) functionality, as emerging usecases unlock new efficiencies and capabilities insoftware solutions.” Capgemini’s own report,Turbocharging Software with Gen AI3, found that80% of organizations increased their Gen AIinvestments in the past year. Though adoption is stillmaturing, it’s expected that by 2026, over 80% ofsoftware professionals will be leveraging Gen AI intheir work.Before diving deeper into the discussion, it’s vital toemphasize the importance of a robust, modernizedintegration strategy. Research consistently shows adirect link between such a strategy and businessperformance. InForrester’s Developer Survey 20234,nearly twice as many respondents with a defined APIstrategy reported year-over-year revenue growthcompared to those without one. Conversely,organizations lacking an integration strategy werealmost twice as likely to report stagnant ordeclining revenue.The message is clear: AI-poweredintegration is not just a technicalshift—it’s a strategic imperative.Now is the time to build thatfoundation and deploy at scaleand adopt.Orchestrating Excellence with Business APIs and Application IntegrationGartner, Forecast Analysis: GenAI Spending in Software Markets, Arunasree Cheparthi, Amarendra , et al., April 3, 2025GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationallyCapgemini Research Institute: Turbocharging software with Gen AI, 2024 As the pace of digital transformation accelerates,businesses are demanding faster, more scalable, andmore intelligent solutions. Ignoring its potential is nolonger an option.We are witnessing a significant evolution in integrationtechnologies to cater to these requirements. With GenAI going mainstream and agentic AI on the horizon,the convergence of AI and integration marks a newchapter in software engineering. Our focus for thispoint of view is on how AI—especially Gen AI—willreshape integration across the Software DevelopmentLifecycle (SDLC), from design and development todeployment and operations.This convergence offers a powerful opportunity tocreate software systems that are more efficient,insightful, and adaptable. AI-assisted integrationdoesn’t just automate processes - it elevates howintegration teams operate, delivering meaningfultransformation across the entire software engineeringvalue chain.To remain competitive and future-ready, organizationsmust embrace this shift and craft a strong AI-poweredintegration strategy. Those who master AI-assistedintegration will position themselves for sustainablegrowth and long-term success.Our previous publication,Orchestrating Excellencewith Business APIs and Application Integration1,12(Accessible to Gartner clients only)and is used herein with permission. All rights reserved.34Forrester Developer Survey 2023 AI-DrivenIntegration Evolution01IntegrationPowered by AI Integration Platform as a Service (iPaaS) platforms havealways aimed to simplify the integration of disparatesystems, applications, and data sources. However,integration platforms are undergoing a fundamentalshift as AI and integration platforms converge to createintelligent, human assisted automation that adapts andlearns from user interactions and system behaviors. Thissynergy has transformed iPaaS platforms intoHarness tangible benefits of iPaaS powered by AI in integrationsoftware engineering1.Efficiency:AI can auto-generate code for integration flows and thus minimizes the need for manualcoding. AI can suggest optimal integration patterns based on historical data. AI can also acceleratetesting and deployment with automated validations.2.Adaptability:iPaaS powered by AI can learn from historical data and adapt in real-time to makeintegration flows more context aware. This could apply to business logic and schema structure inintegration and offer context aware recommendations for the workflows.3.Scalability:iPaaS powered by AI can enhance the scalability of integration platforms, businesses cangrow without being bogged down by technical limitations. AI can dynamically scale platform resourcesbased on throughput and processing workload and can optimize performance through continuouslearning and feedback loops.4.Foster innovation:The AI automation within Integration software engineering life cycle can free upIntegration engineers and will allow them to focus on driving innovation. intelligent, adaptative and