The Appeal of Services as a Software
The age of traditional SaaS dominance is over. AI is dismantling moats and leaving companies scrambling for a new edge, as I explored in my last article, "In Search of a Moat: The Decline of B2B SaaS." The rapid advancement of AI technologies is eroding the competitive advantages that once protected SaaS companies, making differentiation increasingly challenging in a sea of emerging startups. As businesses navigate these shifting dynamics, a new and enticing paradigm is emerging—"services as a software."
Services as a software refers to a business model that combines the scalability and automation of software platforms with the personalized expertise and support of human services. Unlike traditional SaaS, which relies solely on recurring subscriptions and standardized features, this model integrates tailored service delivery directly into the software, providing clients with customized outcomes, ongoing engagement, and a hybrid solution that leverages both human and AI-driven capabilities.
While services as a software may not fit every business, it offers an optimal model for many AI-driven companies that don’t anticipate consistent daily usage but still deliver substantial value. Take the example of a travel agent: while AI excels at automating itinerary planning, it often falls short in capturing personal nuances—like your preference for boutique hotels or ensuring your trip aligns with your pace of travel. This is where human oversight bridges the gap, combining AI-driven efficiencies with empathy and attention to detail.
In the coming years, more businesses leveraging AI will adopt a services as a software model to keep humans in the loop and maintain quality. Here’s why:
I. Competition Will Push Down Prices of Traditional SaaS
The replicability of software solutions has intensified competition within the B2B market. As AI lowers development barriers, numerous players can swiftly enter the market, offering similar functionalities at reduced costs. This influx of competitors drives down prices for traditional SaaS, making it difficult for established companies to maintain their pricing power based solely on software features.
We’ve seen a similar pattern play out over the years across many classes of software. Features once offered as premium are now replicated by countless new entrants. As consumers struggle to differentiate products based on quality alone, businesses increasingly compete on price, driving prices downward. Simultaneously, the rise of AI raises consumer expectations, forcing companies to deliver better products at cheaper rates. AI only exacerbates this trend as more startups will emerge able to offer greater functionality at even cheaper prices.
Chamath Palihapitiya’s 8090 Solutions exemplifies this trend, focusing on products that achieve 80% functionality at just 10% of the cost of traditional enterprise software. This disruptive approach highlights how efficiency and affordability are reshaping markets, compelling incumbents to innovate or lose relevance.
II. AI is Good but We Still Value the Human Touch to Ensure Quality
While AI technologies offer impressive capabilities, the human touch remains invaluable in ensuring the quality and reliability of services. Humans possess the ability to understand nuanced client needs, interpret complex data contexts, and provide oversight that AI alone cannot achieve. This human expertise becomes a premium differentiator in the market.
One of the limiting factors of working with AI today is reliability, particularly concerning AI hallucinations and poor performance due to insufficient context. By keeping humans in the loop, businesses can ensure that their AI-driven tools are used appropriately and effectively, reducing the risk of errors and providing guardrails on outputs.
Keeping humans in the loop provides a failsafe and a way for other humans to better trust the output of AI. This is especially evident in professional services such as consulting, legal, and medical fields. While AI solutions can perform comparably to these professionals at a fraction of the price, they lack the ability to fully replace human judgment and empathy. For example, recent studies have shown that AI significantly outperforms doctors in diagnosing certain conditions; however, most people would still feel more comfortable being treated by a human doctor versus just artificial intelligence.
The success of large management consulting firms like Accenture pivoting their businesses to integrate AI further exemplifies this trend. Accenture has reported significant revenue of over $1B from consulting on generative AI, a field that has only emerged in the past 4 years. There is a strong appetite for human services that can leverage AI tools to deliver better outcomes, ensuring that clients receive the best of both worlds: the efficiency of AI and the reliability of human oversight. While these consulting firms are far from fully automated, they are beginning to lean into building more internal tools to transition toward a services as a software model. This hybrid approach not only enhances service quality but also builds stronger, trust-based relationships with clients, driving long-term loyalty and satisfaction.
III. Payment Structures are Friendly for Both Customers and Vendors
Flexible and customer-centric payment structures are essential for the services as a software model, benefiting both customers and vendors. Traditional subscription-based models often impose fixed costs regardless of usage, which can be inefficient for businesses with fluctuating needs. In contrast, flexible payment structures align costs with actual usage, providing financial benefits and fostering stronger client relationships.
Amazon Web Services (AWS) is a prime example of this approach from well before the era of Generative AI. AWS charges customers based on their actual usage of cloud services, allowing businesses to scale their expenses in line with their needs. This usage-based pricing model ensures that customers only pay for the resources they consume, enhancing cost-effectiveness and financial flexibility.
This model is particularly beneficial for vendors facing an influx of pure software competitors attempting to undercut prices. By adopting a usage-based or value-based pricing strategy, companies can better capture the value they deliver, ensuring that their revenue aligns with customer usage patterns. For instance, a services as a software model may involve a higher one-time payment upfront, coupled with ongoing managed services that provide additional value and support. This structure not only secures immediate revenue but also establishes a continuous relationship with the customer, allowing vendors to capture more value over time.
Moreover, adopting capped usage tiers can simplify pricing structures, making them easier for customers to understand and manage. Codeium provides an excellent example of creating tiered pricing based purely on AI usage (shown below). This approach provides transparency and predictability, which are highly valued by customers. It also helps vendors maintain a stable revenue stream while accommodating the varying needs of their clients.
While traditional subscription-based models have long been favored for their predictable, recurring revenues, the rapid development of AI is shifting the dynamics. With AI enabling faster product development and reducing the need for large teams, companies may find themselves less reliant on outside funding. This shift could diminish the pressure to achieve hyper-growth and instead prioritize sustainable, customer-centric models like services as a software, where revenue aligns more naturally with value delivered.
Conclusion
The emergence of services as a software marks a significant evolution in the B2B software landscape, driven by the transformative impact of AI technologies. This new paradigm addresses the diminishing competitive advantages of traditional SaaS models by integrating personalized services with scalable software solutions. As competition intensifies and the need for differentiation grows, businesses are increasingly adopting this hybrid approach to offer greater value and foster stronger client relationships.
As AI continues to drive innovation and reshape the market, embracing the services as a software model will be crucial for many businesses aiming to thrive in an increasingly competitive and dynamic environment. By focusing on customization, flexibility, and ongoing support, companies can build lasting relationships with their clients, ensuring sustained success and growth in the evolving B2B landscape.