What should you be considering in your AI pricing strategy?
In this episode of the LogiSense Podcast, Tim Neil sits down with pricing and finance strategy expert Niyati Shah to explore how AI is transforming pricing strategies across industries. They discuss the challenges and opportunities of AI-driven monetization, from dynamic pricing models to token-based consumption and hybrid revenue strategies.
Whether you're navigating the shift from subscriptions to AI-enhanced pricing or seeking insights on investor expectations, this conversation offers invaluable takeaways for B2B leaders looking to optimize revenue in the age of AI.
What you'll learn:
- AI is Disrupting Pricing Models - Companies are leveraging AI to optimize pricing strategies, moving from traditional models (e.g., subscriptions, per-user fees) to more dynamic and predictive pricing structures, such as usage-based or tokenized models.
- Hybrid Monetization Strategies Are Gaining Traction - Businesses are experimenting with a mix of subscription and consumption-based pricing to balance revenue predictability with flexibility. Investors are particularly focused on how AI monetization strategies impact long-term financial stability.
- Data-Driven Decision Making is Critical - AI enables deeper insights into customer behavior, helping businesses optimize renewal strategies, upsell opportunities, and product development. Companies must integrate their financial and CRM systems to extract meaningful, real-time data.
- Dynamic and Personalized Pricing is the Future - AI-powered pricing strategies are shifting towards personalized and flexible models that adapt based on customer usage, market conditions, and business needs. This trend, already common in B2C (e.g., Uber, airlines), is expanding into B2B SaaS.