The ‘SaaSpocalypse’ narrative continues to dominate investor outlooks, with fears that AI development is threatening the value of software companies. However, I believe that this is not a SaaSpocalypse, but instead a period of natural selection for the software industry – where the strong will thrive.
Chief of Staff and AI Lead at Forterro.
Widespread AI adoption is raising the bar, so SaaS providers must focus on delivering differentiated and highly valuable outcomes. Providers that are built on broad, undifferentiated offerings and don’t deliver clear, evolving value will soon go extinct and be replaced by simple AI solutions.
In contrast, software companies with true specialization, deep customer understanding, and defensible moats are well placed to strengthen and evolve their position in the AI era.
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Deep customer knowledge
In the industrial mid-market, AI development needs to be grounded in practical applications. Manufacturers operate in physical, industrial environments where the priority is building and delivering the parts and products that power the real economy.
We know our customers are not looking to build the software themselves, or experiment with ‘vibe coding’, but instead they want their existing trusted technology partners to level-up their platforms in a secure, structured way.
Deep industry expertise, knowledge of specialized workflows, and decades of intricate data are the critical factors that pinpoint where real value can be delivered to customers. These elements are the most difficult for AI disruptors to attempt to simulate or replicate.
The impact of AI will meaningfully reshape how software is developed and delivered, but providers should continue to rely on established data moats and security frameworks.
The SaaS providers that own the bank of knowledge that existing software provides and capitalize on this deep expertise during AI adoption are the ones that will stand the test of time. Investing in AI platforms and agents that transform that knowledge into autonomous action will deliver exactly what customers need: improved decision making, elevated efficiency through margin expansion, and increased resilience.
One thing that remains constant is the pressure businesses are under to deliver more for less. To succeed at this critical juncture, software companies need to help businesses do just that through tactical and differentiated applications of AI within workflows.
Embedding AI securely with clear governance
Layering AI into workflows is a practical, high-impact way for businesses to scale without increasing expenditure significantly. When AI agents are embedded and trained in systems, they can automate routine tasks, surface actionable insights in context, and guide users through next-best actions. This frees up time for higher-value work.
When embedding AI tools, providers must prioritize governance by establishing clear guardrails, processes, and secure systems. Role-specific training is critical to ensure AI is embedded in workflows effectively while keeping business data secure.
Added AI capabilities play a central role in workforce development. As workflows become more intelligent, employees should be supported to build new skills to deliver higher-value work, while customers benefit from more responsive and capable systems.
Recognizing a natural progression beyond surface level AI integration, focusing on analysis, judgement and continuous improvement. To achieve this, providers can embed AI agents directly into the software environments that customers already depend on. In doing so, end users can enhance capability without introducing unnecessary risk or disruption to core operations.
AI does not replace expertise or SaaS; it raises the baseline and helps teams develop the skills needed to deliver more value.
Protecting margins
The industry is now moving beyond early enthusiasm for AI towards a more grounded understanding of its true cost and impact. As organizations begin to grapple with the realities of implementation, integration, governance and ongoing running costs, the conversation is becoming more balanced.
This shift will further separate those delivering meaningful, embedded value from those relying on surface-level AI features.
In periods of economic uncertainty and volatile market conditions, which is increasingly a global reality, companies need to build resilience through intelligent decision making and forward thinking. Where costs, energy prices, transport, and supplier availability shift quickly, manufactures are often relying on lagging indicators and manual spreadsheets that are outdated as soon as they are shared.
This latency be combatted by AI that is directly embedded into SaaS that can combine internal and external data to inform likely price changes and ideal buying windows.
Crucially, because these insights sit inside the platform customers utilize day to day, predictive recommendations are delivered in context with the right insight at the right moment. Real-time visibility into performance, supported by AI, allows businesses to act with greater confidence in uncertain conditions.
For customers, this translates to stronger margins, better outcomes, and increased business resilience. So, end-point users can experience an intuitive and informative platform that makes their job easier.
Going beyond the “either or” narrative
AI and SaaS are converging. Organizations that invest in both the technology and the capability to use it effectively will see the greatest return. With the right governance and a clear understanding of customer needs, AI becomes a force multiplier for the value SaaS already delivers, not a replacement for it.
The conversation needs to center on the customers using SaaS, who don’t want experimentations with code but technology they can trust delivered with clear process, security and reliability.
Ultimately, this is not the end of SaaS, but an inflection point to differentiate software providers. Those that embed AI meaningfully within trusted products and maintain genuine specialization will emerge stronger through this period of natural selection. Organizations that invest in both technology and the human capability to use it effectively will see the greatest return.
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