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ZDNET Highlights
- AI-native software providers will challenge traditional SaaS.
- The rising cost of AI infrastructure presents a challenge.
- More native-AI vendors mean more options for small businesses.
Be prepared to see more solutions from ‘AI-native’ software companies in the coming months and years. This trend means new interfaces, different cost considerations, and new ways of building and working with applications. Just as cloud-native vendors flooded the market with software-as-a-service (SaaS) and platform-as-a-service (PaaS) offerings a decade ago, we may see a glut of new AI-based applications.
this is the word of new Study Consultant by Deloitte. It’s not like SaaS vendors are going away any time soon. Currently, the top 10 SaaS providers account for more than half of the software market capitalization. The total market is expected to grow by 11% between 2024 and 2025, from $3.6 trillion to $4 trillion.
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But market dynamics are changing rapidly. SaaS and traditional software companies are already under pressure to replace per-license pricing with outcome-driven pricing.
The study’s authors predicted, “Competition will heat up as AI-native challengers begin to chip away at market leaders in business processes and create new market segments previously unserved by software.”
“In addition, new entrants are growing rapidly and disrupting the market with lean operating models.”
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This shift has interesting implications for developers, engineers, designers, and product managers, who will need to reorganize or change their operations and skills.
So, which service sectors are changing? The study points to several areas, including the following:
- Development of AI as an interface: “Over the next few years, AI-powered systems are expected to increasingly function as the primary interface in many software applications,” the report said. “Fierce competition among software companies to become the primary interface layer is expected to retain customers within their platforms and provide providers with access to agent telemetry.”
- Growing Prominence of AI Orchestration Platforms: Traditional applications are evolving into collections of autonomous AI agents. Monitoring and managing agents will require AI orchestration platforms.
- Struggle to control calculation costs: The study predicts that costs associated with AI infrastructure “will squeeze margins for software companies into 2026”. “Additional costs from using larger language models, investing in new agentic products, and hybrid pricing may put pressure on future revenues and margins.”
This new environment will be especially beneficial for small and medium-sized businesses (SMBs). “AI-first software lets SMBs operate like enterprises, providing advanced capabilities at a fraction of the cost,” Ayo Odusote, Deloitte’s software and platform leader, told ZDNET.
“With increasing competition from AI natives, buyers including SMBs will have more choices and therefore more power, potentially driving down costs. Plus, low-code and no-code platforms mean you don’t need access to expensive technical talent to build the software.”
Still, smaller enterprises “will need to carefully manage the upfront investment, particularly around data preparation, integration and governance,” warned Odusot. “The long-term savings and productivity benefits are real, but the cost benefits come from disciplined deployment and measurable business results, not from experimentation alone.”
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The rise of a new class of AI-native vendors also means an embarrassment of riches – with many new options. “Since there is more competition and more choices in this space, it can be difficult for SMBs to decide on software vendors,” Odusote said. “Do they go with an established vendor, or look for someone new who can potentially offer more innovation at a lower cost and take on risk?”
Competition has intensified between incumbents and AI-native challengers, “many of whom are focused on highly specialized use cases,” he said. “That dynamic is creating more options, especially for SMBs who may prefer modular, targeted solutions rather than large, monolithic platforms.”
We are seeing the formation of an “AI-powered software layer across industries,” Odusote said. “Smaller startups are capitalizing on specialized workflow and vertical-specific AI applications, which could result in a more diverse and innovation-rich marketplace. For SMBs, this could translate into more tailored solutions and competitive pricing.”
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He further said, there is also a need for workforce development to adopt AI solutions. “The transformation to AI-first is as much about workforce development as it is about technology. Organizations that successfully scale AI are redesigning roles and building AI literacy across the enterprise.”
Key skill areas required include data management, vendor evaluation, workflow redesign, and cross-functional collaboration between business and technical teams.
