Agentic-native Platforms are Creating a New Technology Business Model
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For decades, the enterprise technology industry operated on a simple principle: software companies built products, and services firms helped enterprises implement, customize, and operate them. The relationship was highly complementary, but the businesses themselves remained largely separate.
Today, however, the rise of agentic AI platforms is beginning to challenge that longstanding division. As enterprises move toward outcome-driven AI systems, we are witnessing a structural shift that is pulling software and services into a much deeper and more integrated relationship. The implications could reshape how technology is bought, sold, deployed, and monetized over the next decade.
There were good reasons why software vendors rarely built large services organizations and why services firms rarely succeeded as software companies.
The two industries are built on fundamentally different business models. Software companies require distinct investment philosophies, talent models, sales motions, and marketing capabilities. Their brand promise is straightforward: we provide the best technology platform, and customers should use it largely as designed.
To maintain scalability, software vendors carefully protect the integrity of their products. Product managers act as gatekeepers, balancing customer requests against the need to keep the platform standardized and sustainable. Customization typically occurs through configuration layers, APIs, and extensions that sit outside the core product.
Services firms operate very differently. Their brand promise is not standardization; instead, they focus on adaptation. Their objective is to do whatever is necessary to help clients achieve business value. They customize workflows, integrate systems, modify processes, and build layers around software products to better fit specific business needs.
These differing philosophies created a healthy ecosystem. Software firms provided stable technology platforms, and services firms ensured those platforms delivered business outcomes. Enterprises benefited from both.
Underlying this market structure was an important reality: traditional enterprise software was designed to be stable and controlled.
Applications such as ERP, CRM, and supply chain platforms evolved carefully over time. While upgrades occurred periodically, the underlying architecture remained relatively predictable. This stability made it possible for software and services organizations to operate independently while still working effectively together. The separation was not a flaw; it was designed as a feature of the system. For most enterprise workloads today, that model continues to work extremely well and will likely remain relevant for years to come.
What is changing is not the traditional software stack. What is emerging is an entirely new category of technology: agentic-native platforms.
In previous discussions, I have described these environments as being built around a combination of ontologies, digital twins, and an agentic fabric that continuously observes, predicts, and acts. This architecture is increasingly becoming the foundation for advanced AI-enabled business systems.
Unlike traditional software, these systems are inherently dynamic. The ontology evolves as the business evolves. The digital twin expands to represent broader portions of the enterprise. New agents can be created, deployed, modified, and retired continuously. Business expertise becomes embedded directly into the technology stack, creating a constantly evolving relationship between the platform and the enterprise. The result is a system that is dramatically more dynamic than anything most enterprises have previously managed.
At the same time, these platforms are far more customized. While there are opportunities to leverage common components across clients, the business logic, workflows, and agent interactions often become highly specific to each organization.
This evolution changes more than technology architecture. It changes the commercial relationship. Traditional software pricing models, particularly per-seat licensing, often make little sense in an agentic environment. Increasingly, value is tied to transactions completed, processes automated, or business outcomes achieved.
That pricing model reflects a deeper truth: enterprises are no longer purchasing technology, but instead, they are purchasing results. Delivering those results requires a much tighter integration between software and services than the market has historically provided. The brand promise is shifting from separation to integration.
Customers increasingly care less about where the software ends and the services begin. What matters is whether the combined solution produces measurable business outcomes.
As enterprises begin developing high-value agentic platforms, they are discovering that traditional vendor relationships may not be sufficient. These environments require ongoing adaptation, deep business expertise, continuous engineering, and close alignment between platform evolution and business objectives. In many cases, that level of integration is difficult to achieve when software and services are provided by entirely separate organizations.
This does not mean the traditional software model disappears; the truth is far from it. Existing enterprise systems will remain foundational for the foreseeable future. However, a new category of technology business is emerging alongside it. These businesses combine software, services, and ongoing operational responsibility into a single integrated offering focused on outcomes rather than products.
For providers that execute well, the economics can be highly attractive. For enterprises, the returns can be even more compelling because the model is directly linked to business value creation.
We can already see evidence of this shift. AI platform providers such as OpenAI and Anthropic have increasingly expanded their services capabilities and customer engagement models. There are undoubtedly multiple reasons for this, but one underlying factor is clear: achieving enterprise adoption requires deeper involvement in implementation, integration, and business transformation. Unlike before, the technology alone is not enough.
As organizations seek to embed AI into core business operations, software providers are finding that they need greater influence over how their platforms are deployed and used. The old boundaries between software and services become harder to maintain when success depends on continuous collaboration. The broader trend is becoming increasingly obvious.
The software and services industries are not converging because either model failed. They are converging because agentic AI systems demand a new form of partnership. The secular forces driving this change are powerful, and they point toward a future where business outcomes, not products or labor, become the organizing principle of enterprise technology.
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