Subscription accumulating Surprises or Subscription as you Scale?
For a few, it’s that sneaky service that starts cheap but gradually stacks up, with each little feature or user adding up—until suddenly, you’re wondering why you’re paying as much as your office rent for software you thought was a steal!
Multi-year lock ins, limited control, limited customization and uncertainty in security makes them feel over-rated.
For others, it grows as you grow, and vice-versa. They treat it as Subscription as you Scale.
SaaS applications have been the go-to choice for companies looking to optimize operations without the burden of infrastructure maintenance. From CRM systems like Salesforce to project management tools like Asana, businesses enjoyed the quick setup and ease of use. These platforms promised to deliver cutting-edge technology with minimal commitment—an appealing offer for fast-paced environments.
However, as organizations scaled, some began to recognize the limitations of these external solutions. High subscription costs, lack of customization, and concerns about data security started to overshadow the initial allure. This growing dissatisfaction prompted many to reconsider their software strategies.
News is signaling the change: The fintech firm Klarna called off long-standing partnerships with Salesforce and Workday amid in-house AI systems and consolidation initiatives. Below are the transcripts of their CEOs voice below:
“There are large ongoing internal initiatives that are a combination of AI, standardization, and simplification. As an example, we just shut down Salesforce. Within a few weeks, we will shut down Workday. We are shutting down a lot of our SaaS providers, as we are able to consolidate.” Klarna CEO, Sebastian Siemiatkowski
“I’ve had several of my friends reach out to him (Sebastian Siemiatkowski) because he hasn’t said where he’s managing his data…how he is managing and sharing this information? How is he achieving compliance, governance of his company? What is he doing? Salesforce CEO, Marc Benioff
Revenue growth for SaaS giants in the past few years and quarters has gone stagnant and signals winds of change.
Docusign, leader in e-signatures SaaS, shows signs of stagnant to declining growth.
Source: https://s22.q4cdn.com/408980645/files/doc_financials/2025/q2/FINAL-Q2-25-Quarterly-Earnings-Deck.pdf
Smartsheet, a collaboration and project management SaaS leader shows of stagnant growth rate.
Source: https://s202.q4cdn.com/318750635/files/doc_financials/2025/q2/Q2-25-Earnings-Call-Deck_FINAL.pdf
With advancements in AI technologies, businesses are increasingly choosing to develop in-house solutions tailored to their specific needs. Here are some compelling reasons driving this trend:
1. Customization Over One-Size-Fits-All
SaaS solutions often offer a standardized approach that may not align with a company’s unique requirements. For instance, Netflix initially relied on various SaaS tools for data analytics. However, as their data needs grew, they developed their own in-house AI systems, enabling them to deliver personalized recommendations more effectively. This level of customization enhances user experience and drives customer engagement.
2. Cost Efficiency in the Long Run
While SaaS solutions can be cost-effective at first glance, the cumulative costs of subscriptions can become exorbitant. Airbnb faced this issue with its customer service operations, where they initially relied on third-party tools. By investing in in-house AI chatbots, Airbnb not only reduced long-term costs but also ensured their customer service aligned perfectly with their brand ethos.
3. Data Security and Compliance
Data security is a growing concern, especially with increasing regulations like GDPR. Companies are more cautious about sharing sensitive information with third-party SaaS providers. For example, American Express decided to build in-house AI solutions to manage transactions and customer data securely. This shift allows them to maintain control over their data while adhering to strict compliance standards.
4. Agility and Innovation
The fast-paced nature of modern business requires companies to pivot quickly in response to market changes. In-house AI solutions provide the agility necessary for rapid innovation. Tesla is a prime example; by developing its AI systems for autonomous driving internally, the company can iterate quickly and stay ahead of competitors reliant on external solutions.
5. Talent Utilization and Culture
Building in-house AI solutions not only fosters innovation but also enhances company culture. Organizations like Spotify have successfully created internal AI teams that contribute to their product development. This investment in talent not only drives technological advancement but also promotes a culture of learning and growth within the organization.
The journey from monolithic software systems to SaaS (Software as a Service) solutions and now to composable applications marks a strategic shift that prioritizes flexibility, scalability, and rapid innovation.
Monolithic architectures were once the cornerstone of enterprise IT. These systems were built as large, self-contained applications, where each component was tightly integrated into a single codebase.
The rise of SaaS solutions over the last decade has been a game-changer. Companies no longer needed to build and maintain complex software infrastructures on-premises.
In response to the limitations of both monolithic systems and SaaS silos, the concept of composable applications has gained traction.
Source HFS Research
Netflix: Moving Away from Off-the-Shelf Solutions Netflix has long been a leader in AI innovation, but its journey is particularly illustrative of the SaaS-to-in-house trend. In the early stages, Netflix relied on SaaS solutions for data analytics and content recommendation. However, as the company’s needs became more complex, it invested heavily in building proprietary machine learning models for content recommendation, personalization, and even content production. This shift allowed Netflix to tailor its algorithms to the unique behaviors and preferences of its user base, resulting in a more engaging and personalized user experience.
JPMorgan Chase: In-House AI for Fraud Detection The financial services industry is another area where the transition from SaaS to in-house AI solutions is taking hold. JPMorgan Chase, one of the world’s largest banks, has developed its own AI tools for detecting fraudulent transactions. While SaaS solutions for fraud detection exist, the bank found that its unique transaction patterns required more sophisticated models than those provided by third-party vendors. By investing in its own AI team and infrastructure, JPMorgan Chase has been able to build a more robust fraud detection system that adapts quickly to new threats, saving millions in potential losses.
Walmart: AI for Supply Chain Optimization As one of the largest retailers globally, Walmart relies on AI to optimize its vast supply chain. Initially, it used SaaS solutions for inventory management and demand forecasting. However, to better align with its unique requirements, Walmart has since developed in-house AI models for demand forecasting, inventory management, and logistics optimization. This shift has enabled Walmart to respond more quickly to changes in demand, reducing out-of-stock scenarios and improving overall supply chain efficiency.
Spotify: Custom AI for Music Recommendations Spotify’s recommendation algorithms are a cornerstone of its user experience, setting it apart from competitors. While SaaS solutions for recommendation engines are available, Spotify decided early on to build its own machine learning models. The company’s in-house AI models analyze listening habits and even the audio properties of tracks to create highly personalized playlists like “Discover Weekly.” This focus on in-house AI allows Spotify to iterate quickly, integrating new data sources and refining its algorithms to better serve its 500 million users.
Innovate fast or die. Need re-thinking of engagement models, flexibility, security and the ever-evolving tech. Lock-ins will get locked.
Assess before you retire. Not all organisations of different scale can afford to achieve TCO, compliance & governance. The complexities and benefits shall be carefully evaluated.
Worxwide can conduct process audit, vision workshops to discover the as-is and to-be and help design a productive organization from build vs buy decisions to effectively consult & implement SaaS based CX solutions across sales, marketing and service. Discover our capabilities here: https://worxwide.com/growth-consulting/
Worxwide is a digital growth consulting firm, helping companies win more business with RFP/bid writing, boosting sales productivity with sales automation & transformation, driving experience led growth with user experience design, and boosting sales via AI led CX and omni-channel customer experience.