AI Adoption & SaaS Consolidation | The Current Thing #6 - Postdigitalist

The promises of generative AI have completely disrupted the tech world. Nowadays, it seems like there’s little happening outside its sphere. In this context, regardless of your job role, it's key that you separate the signal from the vaporware.

One of the most interesting phenomena of the generative AI boom is a practice called "vibe-coding". Vibe-coding consists of developing an app by prompting an AI, instead of writing the code "by hand". While vibe-coding falls short in complex use cases, it's great for non-techies developing simple apps. For instance, project trackers, inventory trackers, and simple CRMs are very easy to vibe-code.

In short, vibe-coding may be a threat to B2B SaaS platforms. If you can code fully custom tools for your team and host them on the same platform, why would you pay for dozens of different SaaS tools, work through their learning curve, and tolerate their limitations?

In this post, we'll do a quick overview of the state of SaaS in the age of generative AI. Are we walking towards a future of further SaaS consolidation, or is the SaaS space in real trouble?

Forecasting Three Key Trends in AI Adoption and SaaS Consolidation

Shift toward in-house custom software development fueled by AI adoption

One of the most significant trends emerging from AI adoption is the shift toward in-house custom software development. AI-powered development tools dramatically reduce the time, cost, and complexity of building bespoke applications.

The emerging category of AI-powered no-code platforms offers everything from simple experiences for non-techies, to developer-grade toolkits for those who want to streamline their development process without fully relinquishing code. 

This trend may seem particularly appealing to organizations seeking to reduce their IT spend. There’s an interesting possibility that “low-tier” SaaS platforms (those that are only fancy kanbans) will be replaced by custom-made solutions. 

However, in this uncertain context, and with the promise of AI “making software development obsolete”, one may assume that SaaS budgets are shrinking. That’s not true - budgets are actually increasing, but shifting towards AI platforms instead of “regular” software.  

Between 2024 and 2025, average monthly AI-related spending per organization is projected to increase by 36%, from approximately $63,000 to $85,500. Moreover, the proportion of companies allocating more than $100,000 per month to AI tools has more than doubled—from 20% to 45%. This surge underscores how AI is becoming a central pillar of enterprise technology investments.

SaaS consolidation around closed AI ecosystems

The second major trend is the ongoing consolidation of SaaS offerings around closed AI ecosystems. When we look at the vendor landscape, consolidation is evident. Public cloud providers and generative AI tool vendors command the lion’s share of AI budgets—11% and 10%, respectively—highlighting the concentration of spending within a relatively small group of dominant players.  

As organizations increasingly rely on a few dominant SaaS providers for AI infrastructure and services, the market dynamics shift toward oligopoly. This concentration may lead to higher prices and less diversity in software options but could also accelerate innovation by focusing resources on a smaller number of platforms.

Proliferation of AI-enhanced SaaS delivered via centralized APIs, increasing costs

The third trend is the proliferation of AI-enhanced SaaS products delivered centrally through major players’ APIs. This model allows businesses to access powerful AI features without building them from scratch, democratizing AI capabilities across industries.

However, embedding AI into SaaS products comes at a cost. The addition of new, expensive AI-driven features to “traditional” SaaS products has increased their average price. It’s estimated that new AI features have driven a 10% increase in average SaaS pricing. On the other hand, while centralized API delivery enables scalability and ease of integration, it also concentrates pricing power in the hands of a few major players. 

It’s essential to evaluate the trade-offs between leveraging AI-enhanced SaaS for rapid innovation and managing escalating costs. Strategic vendor management and cost optimization will be critical in this environment.

How to Grow a Product in the Era of AI Adoption & SaaS Consolidation

Beware the AI hype cycle

AI is everywhere, but not every AI feature delivers real value. Many companies rush to integrate AI, only to end up with “checkbox” features that don’t solve meaningful problems or justify their costs. Before investing in AI, rigorously validate whether it could improve your product and align with customer needs. Otherwise, you risk bloating your roadmap and confusing your value proposition.

Integration isn’t a panacea

With SaaS consolidation, integration is often touted as a growth lever. However, integrating with other platforms can be resource-intensive, slow, and fraught with technical and business risks. APIs break, partners pivot, and the integration you spent months building may become obsolete. Prioritize integrations that are truly essential to your core users, and be wary of spreading your team too thin.

Prepare to sell

As SaaS buyers consolidate their stacks, they’re increasingly focused on cost savings and operational efficiency. Now you’re not only competing against companies developing alternative products, you’re competing against the possibility that someone may “vibe-code” your product in a couple of hours. Product teams must demonstrate clear, quantifiable ROI—and be prepared for longer sales cycles and more scrutiny from procurement teams.

Focus & rethink success metrics

Growth is no longer just about user acquisition or flashy AI features. In this market, retention, customer satisfaction, and sustainable revenue matter more than ever. Be prepared to sunset underperforming features and focus relentlessly on what delivers real, lasting value.

Key Takeaways

The twin forces of AI adoption and SaaS consolidation are reshaping the software spend landscape and redefining how organizations develop and consume technology. With AI budgets soaring and SaaS ecosystems concentrating around dominant providers, companies face critical decisions about where to invest, build, and buy.

Forecasted trends point to a future where in-house AI-driven custom development grows, SaaS consolidation deepens, and AI-enhanced software proliferates through centralized APIs, each trend bringing unique benefits and challenges.

Businesses that understand and strategically respond to these dynamics will be best positioned to innovate efficiently, control costs, and maintain their competitive advantages.

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