Broad industry support used to be enough to define vertical software. Solutions were designed to cover the common needs of the industry, and that was generally the expectation. That’s changed in two ways.
First, the level of specificity. Supporting an industry at a high-level has reached its limits – the real differences show up in sub-industries and micro-verticals. A beverage producer, for example, operates with strict process, quality, and compliance requirements, and expects capabilities like lot traceability across raw ingredients, shelf-life, and quality management to be delivered built-in, but also configurable to meet their needs.
Second, how customization is handled. It used to be acceptable – and often expected – for the customer to manage customizations through upgrades. Now, those customizations are the responsibility of the solution provider during the upgrade process.
Most platforms can still meet the general requirements of industries like manufacturing, nonprofit, healthcare, and financial services – that’s the baseline. Where things start to break down is in how well those systems reflect how work gets done across their organization: how decisions are made, how processes connect, and how information moves from one step to the next. This is also what’s pushing the market toward more integrated solutions that work across the business.
At a certain point, adding more features doesn’t solve the problem. Depth requires context, an understanding of where complexity shows up and how work happens in practice.
That level of context is difficult to build into one purpose-built application. In practice, the expertise needed to solve for those workflows often sits closer to the customer. It lives with industry specialists, partners, and developers who spend their time inside these industries, solving the same problems and refining how those workflows work best over time. It requires a flexible platform and integrated solutions where best practices can be reflected and still be adapted for unique customer needs.
As more solutions come together, expectations around how systems work together are changing. There’s an expectation that workflows and data connect across them, so teams have a consistent view of the business and can generate insight from it.
That’s also changing how the ecosystem fits into the product. It’s not just a way to extend coverage or add optional capability – it’s part of how the system works, through solutions that connect, share data, and support workflows across the business.
Rather than trying to build every industry-specific workflow into a single roadmap, platforms need to be designed to bring that depth in, whether through tightly integrated solutions, co-development, or more targeted offerings in industries like nonprofit, manufacturing, and financial services. The goal is not to replicate that expertise, but to make it usable and accessible within the system.
At Sage, our AI Developer Solutions enable partners to build solutions that integrate directly into finance and operations workflows. For example, DataBlend developed its PopdockAI Agent, which connects data across finance systems to deliver real-time insights and automate tasks like reconciliation and forecasting.
A strong platform foundation becomes even more important in this model. It provides the shared data, security, governance, and core workflows that everything else builds on. Having consistency is what allows additional capability to operate in a reliable, controlled way, rather than creating more fragmentation.
Specialized capability is now brought directly into the experience, rather than living alongside core systems through integrations and add-ons that required stitching together different systems, data models, and controls. The difference is not just where that capability sits, but how seamlessly it works within the broader system. This matters most in areas where the gap between a general system and how the business functions has historically been the hardest to close.
Take industries like insurance, lending, or construction. A general system can process transactions, but it doesn’t reflect how those businesses operate. In insurance, it’s policy, claims, and commissions. In lending, it’s the flow between loan systems and finance. In construction, it’s certified payroll and job costing. These are core workflows. Solutions like PolicyConnect and Lending Management, alongside industry workflows like certified payroll, bring that context into the system so teams work in one place that fits how the business runs.
The same approach is also starting to extend into AI. Instead of treating it as something separate, new capabilities are being embedded directly in the flow of work. This makes it possible to apply AI to specific workflows where that depth already exists, while maintaining the same standards for security, governance, and control on which the rest of the system depends.
Expectations of vertical solutions have already changed. Broad industry support gets you into the conversation, but depth without the pain of customization is what makes the difference.
The platforms that stand out will be the ones designed to bring the right expertise into the system and make it usable in the flow of work. This won’t come by trying to cover every use case themselves, but by being open by design: supporting specialized capability without losing consistency or control.