Future of Software Monetization with Agentic AI—Interview with Industry Expert Arjun Bhalla
The SaaS (Software as a Service) model transformed how businesses consume software. Offering cloud-based solutions with predictable subscription costs, SaaS allowed businesses to quickly access tools, improving retention, convenience, and enabling rapid monetization for providers. However, as the SaaS market grew, inefficiencies emerged, such as unused licenses and oversimplified pricing models like per-user or per-usage. Enter Agentic AI—AI-powered systems that perform tasks autonomously, manage workflows, and make decisions. These advancements are reshaping software pricing, focusing less on usage and more on outcomes.
We spoke with Arjun Bhalla, an expert in SaaS and AI business models, about the future of software pricing in the age of Agentic AI. He is based in San Francisco, USA and has over a decade of experience scaling Software and AI businesses at ServiceNow, Adobe, and consulting for many others.
How is Agentic AI changing the SaaS landscape?
Arjun Bhalla: SaaS was a game-changer, allowing businesses to access tools on a subscription basis. But as the market grew, inefficiencies became apparent. Agentic AI is shifting the focus from consumption-based pricing to outcome-based pricing. AI systems now handle tasks like customer service or content creation, which reduces the need for human licenses. This makes traditional user- or usage-based pricing less relevant, and businesses need to adapt to value-driven models.
How should businesses rethink pricing for AI-driven software products?
Arjun Bhalla: Traditional pricing models based on seat or usage need to evolve. Pricing should now be tied to the outcomes delivered by AI, such as completed tasks or solved problems. This shift ensures businesses pay for results, not just access. For instance, platforms like Intercom could charge based on the number of tickets resolved by AI, rather than the number of agents.
Can you provide examples of how companies can implement outcome-based pricing?
Arjun Bhalla: For example, Canva could price based on the number of designs created, not the number of users. Intercom might charge based on AI-resolved support tickets, and Salesforce could base pricing on the number of AI-powered interactions. This approach aligns the price with actual value delivered, making it more transparent and cost-effective for businesses.
How does this model help businesses lower their total cost of ownership?
Arjun Bhalla: Traditional models often result in businesses paying for unused licenses or features. With outcome-based pricing, customers only pay for the value they receive, such as tasks completed by AI. This reduces waste and lowers the total cost of ownership, as companies only pay for the outcomes they use, not unused resources.
What’s next for software pricing as AI continues to evolve?
Arjun Bhalla: As AI technology progresses, pricing will continue to shift from user-based models to performance-based models. Businesses will increasingly pay for the results AI systems deliver, making pricing more aligned with value. This will not only foster transparency but also drive better customer satisfaction and long-term growth for providers.
Conclusion
Agentic AI is transforming software pricing by moving away from user-based models and focusing on outcomes. By adopting outcome-based pricing, businesses can better align with customer needs, ensuring they pay only for the value delivered. As AI continues to reshape the market, companies that embrace this shift will be positioned for success in a rapidly evolving digital landscape.
Disclaimer: The views and opinions shared in this article are those of the interviewee and do not represent the views of any current or previous employers. This content is intended for informational purposes only and does not endorse or support any specific company, organization, or product.
