Presented by EdgeVerve
Supply chains are where legacy integration models reach their limits. As partner networks expand and operational volatility increases, traditional middleware struggles with cost and complexity. That’s why supply chain has emerged as a proving ground for automation-based integration platforms as a service (iPaaS), a next-generation model designed to absorb continuous change without rewriting the stack.
This article takes a look at today’s supply chains, the limitations of legacy integration, how automation changes the iPaaS model, the potential downsides of the upgrade, and the questions leaders should ask if next-generation iPaaS makes sense for them.
why now? Supply chains have stepped up their integration models
Supply chains have always been complex. The new thing is the pace of change. The network now includes hundreds of suppliers, logistics providers and distributors, each running different systems and data standards.
At the same time, expectations for real-time visibility and rapid response are also increasing. The global supply chain visibility software market, which is the problem area that automation-led iPaaS aims to address, was estimated at approximately $3.3 billion in 2025 and is projected to triple by 2034. But enterprises clearly need more than just visibility.
Industry surveys show that more than 90% of supply chain leaders are reworking their operating models in response to volatility, including tariff changes, and more than half report using AI in at least some supply-chain functions. (See this 2025 PwC survey.) That combination — Structural changes and new automation expectations — Throws light on integration.
The legacy integration does not exactly match the ground reality. Traditional integration architecture involves fixed partners, predictable schema, infrequent changes, and general stability. That model worked when supply chains were slower and more centralized.
Today’s supply chains operate under diverse conditions. Partners are constantly added and removed. Data structures evolve with new products, regulations, and sustainability requirements. The old corner cases are no longer so extraordinary.
Limitations, problems and pitfalls of legacy integration
Let’s look a little closer at the status quo. In supply-chain environments, legacy integration approaches struggle with the same structural limitations:
- Inflexibility and poor scalability as the number of partners increases
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High upfront and ongoing costs driven by custom development
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Requires heavy maintenance to keep the integration running
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Lack of specific IT resources needed for changes
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Heterogeneous systems and applications between partners
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Brittle point-to-point (P2P) integrations that don’t age well
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Code-dependent data mapping and transformation
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Various tools for B2B integration and internal applications
In many enterprise domains, outdated and brittle P2P integration — To cite just one of these limitations — Creates discomfort. In supply chains, this causes disruption. Missed or delayed messages can result in shipment delays, excess inventory, or planning decisions based on outdated data.
That’s why technology integration debt accumulates so quickly here. Some other enterprise domains combine that level of external dependence with the need to keep operations running continuously.
What changes in next-generation iPaaS, and why AI matters
Next-generation iPaaS platforms don’t just move integration to the cloud. This is already at stake in the broader iPaaS market, which analysts have been tracking for a dozen years. The decisive change is how new platforms handle change. Instead of treating integrations as static assets, they manage integrations as living workflows.
The automation-led iPaaS emphasizes faster partner onboarding, reusable process logic, and AI-assisted mapping that reduces manual effort when changing schema. (And the changes they make, whether to JSON APIs or event payloads or compliance data.) Errors also surface earlier and are easier to control.
Because supply-chain data mix semi-structured documents, inconsistent partner conventions, and structured transactions with context-dependent exceptions, they are a natural candidate for AI-assisted normalization and validation. When used correctly, AI reduces human effort without eliminating governance.
Cost and sensitivity to disruption
Supply chains operate under tight economic constraints. Margins are thin, disruptions are costly, and technology investments must be justified quickly. Long, highly customized integration programs are difficult to defend.
Automation-led iPaaS better aligns with this reality, with a blend of AI-powered migration tools, no-code low-code configuration with helpful co-pilot, out-of-the-box (OOB) support for standards, connectors, and more to enable accelerated migration.
While integration upgrades have a reputation for being disruptive, the emerging adoption pattern for next-generation iPaaS looks different. Here we are seeing supply chain leaders introducing platforms sequentially, allowing old systems to run while new automation absorbs the change.
The goal is not to stop operations, but to reduce the “blast radius” of change. Or to change metaphors, in this case, it really is possible to keep the plane in the air while slowly rebuilding the supply-chain integration engine.
Questions supply chain leaders should ask
Overall, it resets the decision. Rather than treating AI-powered iPaaS purely as a technology upgrade, supply chain leaders may be better served by asking a few operational questions:
- How quickly can we onboard or offboard a trading partner today? What slows down that process?
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Where do integration failures emerge first: the IT dashboard, or missed deliveries and distorted inventory signals?
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How much human effort does it take to maintain mappings, handle exceptions, and match data when the format changes?
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Are our integration workflows designed to absorb volatility, or do they assume stability that no longer exists?
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If parts of our supply chain become more autonomous — As with agentic AI — Will our integration layer enable this, or block it?
Let’s stop at that last question. Autonomous agents do not replace integration; They depend on it. Any system capable of functioning still requires controlled access to data and reliable execution across all systems. Automation-based iPaaS provides the required foundational functions: event-driven workflows, permissions, observability, and the ability to work across organizational boundaries.
“If you can make it there…”
Supply-chain leaders aren’t considering integration upgrades because they want better middleware. They are doing this because instability has become permanent. Because the associated costs and complexity have created an insurmountable and unbearable stress.
Automation-based iPaaS promises relief to this highly stressed enterprise domain. With apologies to Frank Sinatra, if it works in supply chains, it’s likely to work anywhere.
N. Shashidhar is SVP and global head of product management at EdgeVerve.
VentureBeat newsroom and editorial staff were not involved in the production of this content.
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