longer paying solely for access to software; they’re also compensating software providers based on measurable outcomes achieved through their AI services—for example, generation of AI-generated responses, number of queries processed, or number of completed tasks. Therefore, the move to AI pricing models signifies a stronger alignment between cost and the value of service delivery.
The shift from subscription-based business models to outcome-based pricing for AI services will be one of the most significant transformations in software-as-a-service (SaaS) history. Historically, SaaS businesses have used predictable (monthly or annual) subscription pricing based on user tier/or number of users, and/or a set number of features.
From Subscription to Outcome-Based Models
However, AI creates a challenge to SaaS providers because, unlike traditional software, output from AI systems is subject to a variety of factors that may be unpredictable (actual usage, volume of data, and intensity of computational resources used), so providers face an expensive challenge in developing pricing/number to estimate the value of AI service based on these variables.
Due to uncertainty about the end customer value attributable to AI services, SaaS providers must adjust their pricing strategies. Instead of charging for access to their SaaS software, providers are increasingly charging for service deliverables based on the number of responses generated by the application (i.e., number of AI-generated responses, number of queries processed, and/or number of tasks completed) that the end customer received.
How Are Tech Giants Influencing This Transformation?
Companies such as Microsoft and Google have the infrastructure, resources, and expertise for new models that require levels of scale, infrastructure, cloud computing, and artificial intelligence capabilities unavailable to most companies; however, because they already provide infrastructure for AI usage through their cloud services, they also can redefine industry norms based on their power and influence.
The recent modifications within their respective platforms appear to suggest a move toward:
Billing for AI services by usage.
- Pricing by tiers related to performance; and
- Incorporating AI-related costs into a broader range of cloud products or services.
This fundamental change will enable these companies to monetize their artificial intelligence innovations while also giving businesses greater pricing flexibility.
Impact on SaaS Organizations
The transition to an outcomes-based model will have a significant impact on all SaaS organizations, especially those that incorporate or implement artificial intelligence features.
The following is a list of some of the challenges these organizations may face:
- The ability to predict costs associated with variable levels of usage; increased expectations from customers to demonstrate tangible results; and acquiring new pricing methods/strategies, as well as redefining their overall business model.
- At the same time, there are also opportunities that exist for many SaaS organizations because of the transition to a model based on the outcomes they provide to customers:
- Distinguishing products and services from competitors through performance-based offerings; aligning offerings with the expectations of customers; and generating higher revenue by developing and delivering more services that produce greater value.
SaaS organizations that are less than mid-sized or considered start-ups will face a far more challenging transition to an outcome-based pricing model because they lack the economies of scale and access to the same resources as larger SaaS organizations.
Cost Relevant To The Enterprise Vs. The Value Of The Enterprise.
From an enterprise perspective, pricing models offer businesses flexibility but also introduce uncertainty. Businesses now have the ability to manage and optimize their expenses by only paying for what they use. Fluctuating costs, however, can complicate the budgeting process.
Due to this shift in pricing models, organizations are being forced to rethink how they evaluate their software investments, not only considering the cost of a software solution but also measuring their return on investment (ROI) through productivity and efficiency improvements, and ultimately, business outcomes.
As AI pricing evolves, enterprises are being encouraged to take a more strategic approach to their technology spending.
Cloud Infrastructure’s Role
The cloud plays an important role in enabling these new pricing models to succeed, primarily because of the large number of computing resources used for AI workloads and the ability of cloud providers to leverage their existing infrastructure to provide scalable, on-demand computing resources.
By incorporating AI costs into cloud billing, businesses (like Microsoft and Google) can provide their clients with a seamless pricing experience while still retaining control over how they allocate resources.
Additionally, by integrating and tracking usage on a granular basis into cloud billing, businesses will be better able to monitor and manage their AI costs in real time.
An Industry Shift Towards Outcome-Based Pricing
Outcome-based pricing will not apply only to AI; rather, it will be part of a broader trend across the software industry toward value-based pricing models.
With increased competition and customer demand for transparency, companies face greater pressure to justify their pricing structures. Because AI outputs are measurable, AI provides a strong foundation for this transition.
This industry shift is likely to affect pricing strategies across other areas of software development, leading to dynamic performance-based pricing models.
Conclusion
If pricing models are hard to understand or unpredictable, businesses may reduce or stop investing in AI; conversely, if pricing models are easy to understand and competitively priced, businesses are more likely to consider implementing AI solutions.
The changing landscape of AI pricing underscores the delicate balance between driving innovation through pricing models and providing solutions that are usable and accessible to customers. Companies should strive to develop pricing models that are both financially rewarding for the company and also easy to understand and equitable for all customers.
Source: Accelerating Frontier Transformation with Microsoft partners
