Service-as-a-Software: How AI Can Perform Work for Businesses

Artificial intelligence is fundamentally reshaping not just how we work, but what work means. The past decade saw the rapid rise of Software-as-a-Service (SaaS) models, where companies could access powerful tools via the cloud instead of traditional software licences. Today, we’re witnessing the evolution of this concept into something new: Service-as-a-Software (SaaS 2.0)—a business model where AI doesn’t just provide tools but performs tasks.

The Shift from Selling Software to Selling Work

The essence of SaaS 2.0 is simple: companies are no longer buying static software solutions. Instead, they are purchasing AI-powered services capable of executing complex tasks autonomously. This is a major departure from traditional SaaS, where software products were sold with user licences or subscriptions. In the Service-as-a-Software model, AI doesn’t just enable work; it does the work.

This paradigm shift is led by AI-driven services that go beyond automated recommendations or analytics. A leading example is “Sierra,” a company at the forefront of this change. Sierra isn’t in the business of selling software licences or cloud-based tools. Instead, its AI systems actively perform tasks—like engaging with customers, solving service issues, or even managing workflows in real time. Sierra’s AI operates on a pay-per-resolution basis, highlighting how the traditional notion of software “products” is being replaced by AI-driven services.

How Service-as-a-Software is Changing Business Models

In essence, companies like Sierra are not offering an AI solution as a product—they are offering a service. This is comparable to the shift seen during the initial SaaS revolution. Where businesses once bought physical software on CDs, then transitioned to cloud-based subscriptions, they are now paying for work done by AI. Rather than paying for a tool that automates certain tasks, clients are paying for the outcome—the completed work itself.

This model holds several advantages. Businesses gain access to AI-driven services without the burden of training staff to use complicated software or manually configuring algorithms. AI companies, on the other hand, can monetise their expertise and capabilities in a more dynamic and scalable way. This opens up massive opportunities in industries where outcomes matter more than tools: customer service, logistics, supply chain management, legal analysis, and many more.

The Economic Opportunity: Scaling AI-Powered Services

What makes Service-as-a-Software so appealing is its alignment with the gig economy and the increasing flexibility in labour. In traditional SaaS, scaling a business often meant selling more licences or seats. But in the Service-as-a-Software model, the potential for scaling is directly tied to increased demand for specific services. As AI systems like Sierra’s become more capable of complex and nuanced tasks, the variety and volume of work that can be automated increases significantly.

For instance, Sierra’s AI-driven customer resolution service can handle basic inquiries with minimal human intervention. As these systems become more advanced, they are increasingly capable of handling more sophisticated queries and even resolving disputes—tasks traditionally handled by customer support agents. The more tasks the AI can handle autonomously, the more scalable and profitable the model becomes.

What Service-as-a-Software Means for the Future of Work

While AI-powered services create significant economic opportunities, they also challenge traditional workforce structures. As companies shift towards buying work as a service, roles focused on repetitive, rule-based tasks are likely to diminish. In contrast, roles involving human oversight, strategic thinking, and creative problem-solving will grow in importance.

The transition to Service-as-a-Software also creates opportunities for companies to become more agile and responsive. By integrating AI-driven services, businesses can automate time-consuming processes, freeing up human employees to focus on higher-value work. The impact is two-fold: businesses can scale efficiently, and employees are empowered to focus on tasks that require uniquely human insights.

Ethical Considerations: Transparency and Accountability

However, as with any major technological shift, this new model comes with challenges. Businesses adopting Service-as-a-Software will need to consider issues of transparency, accountability, and fairness in automated decision-making. If AI is handling sensitive customer interactions or legal tasks, there must be clear mechanisms in place to review and explain AI-driven actions.

Companies must also ensure that their AI systems aren’t reinforcing biases or making decisions that lack ethical oversight. As AI becomes more central to delivering services, establishing trust with customers will be critical.

A New Economic Opportunity?

The rise of Service-as-a-Software signals a profound shift in how companies approach AI. It’s a move from selling products to delivering outcomes, and from relying on static tools to embracing AI as a dynamic partner. For businesses like Sierra, this means moving beyond automation to offering scalable, AI-driven services that adapt to changing needs in real-time.

Richard Foster-Fletcher 🌎 (He/Him) is the Executive Chair at MKAI.org | LinkedIn Top Voice | Professional Speaker, Advisor on; Artificial Intelligence + GenAI + Ethics + Sustainability.

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