AI Driven Automation: The Threat and The Opportunity

The AI-Driven Automation Wave

Artificial intelligence has rapidly transformed how companies deliver customer service. From intelligent chatbots managing first-level inquiries to machine learning models anticipating customer needs, automation now handles a significant share of interactions that once required human agents. As this trend accelerates, it’s becoming clear that charging by the seat no longer reflects true value—leading the industry toward an interaction-based pricing model that charges based on the volume or complexity of support engagements.

What Is Interaction-Based Pricing?

After years of seat-based licensing dominating the market, the customer service software industry is now shifting to interaction-based pricing—charging for the number of tickets processed, chats handled, or usage events captured. By tying costs to actual interactions, this new model aligns pricing more directly with the value a customer receives and encourages product teams to double down on efficiency and outcomes.

Impact on Product Managers

1. Refining Value Metrics
   Product managers must pivot from measuring “seats sold” to looking at volume and quality of interactions—whether handled by AI chatbots or human agents. Key tasks include building real-time dashboards so customers can track ticket, chat, or call volumes and enabling them to manage spend effectively.

2. Flexible Pricing Strategies
   With AI now handling an increasing share of support traffic, product managers must collaborate with finance to develop usage-based or tiered plans. Seasonal fluctuations or sudden spikes in inquiries—perhaps driven by new product launches—need to be accommodated without penalizing customers.

3. Focus on Automation Value
   As AI plays a larger role, product managers must integrate and optimize automated workflows. By improving chatbot resolution rates or triage mechanisms, they enhance value for customers—who, in turn, see tangible cost savings.

Effect on Sales

1. New Messaging and Forecasting
   Sales professionals must shift from a straightforward seat count pitch to explaining how interaction volume translates into customer ROI. Contracts become more flexible and can start small, scaling as usage grows.

2. Incentivizing Post-Sale Growth
   Given that AI can expand usage rapidly, sales quotas and compensation will increasingly reflect consumption patterns. That means a closer relationship with Customer Success to ensure adoption and consistent upsell opportunities.

3. Data-Driven Forecasting
   Traditional seat-based forecasting gives way to more complex usage predictions. Sales leaders need new models to account for factors like automation-driven ticket deflection or spikes in seasonal inquiry volume.

New Realities for Customers

1. Smarter Budgeting
   Interaction-based pricing means customers pay only for their actual usage—human or AI-driven. Businesses must understand ticket/chat volumes to avoid sticker shock.

2. Visibility into Value
   With transparent dashboards and analytics, buyers can see exactly how many interactions AI handles versus human agents, and they can spot areas for cost-optimization or service improvement.

3. Flexible Contracts
   Companies should negotiate contracts that allow them to scale their usage tiers up or down. As AI evolves, support volumes might shift drastically, and flexible terms will ensure costs stay aligned with real needs.

AI-driven automation has flipped the script on customer service operations, making it evident that seat-based pricing is increasingly outdated. By embracing interaction-based pricing, providers can offer a fairer, more transparent cost structure that rewards innovation and efficiency—whether through human agents, AI chatbots, or a combination of both. This shift impacts product managers, sales teams, and customers alike, prompting more adaptive strategies and deeper collaboration to ensure continued success in a constantly evolving marketplace.