The rise of agentic artificial intelligence (AI) is redefining the enterprise landscape, providing organizations with task-focused solutions that promise efficiency and precision. Unlike its general-purpose generative AI counterparts, agentic AI specializes in executing specific tasks, often linked to operational decision-making.

However, a critical question looms over its adoption: How will AI agents be priced? With diverse pricing models emerging, CIOs must navigate this evolving landscape to find the best approach for their business needs.


Agentic AI: A New Frontier in Enterprise AI

Agentic AI is gaining traction in the enterprise. In June 2025, Forrester identified it as one of the top emerging technologies. Its application focuses on operational intelligence, making it invaluable for industries such as customer service, logistics, and financial management.

Organizations like Salesforce and ServiceNow have already integrated agentic AI into their ecosystems, but the pricing of these AI agents remains a point of contention. Salesforce, for example, offers:

  1. Free Conversations: 1,000 conversations included with its CRM.

  2. Bundled Subscription: Integrated into its success plan.

  3. Pay-As-You-Go: $2 per conversation a la carte.

These tiers reflect the broader struggle to balance usage-based pricing with the need for predictability and cost control.


Emerging Pricing Models: What Works Best for Your Business?

Aaron Levie, CEO of Box, identifies four core pricing models that could shape the future of agentic AI:

1. Task-Based Pricing

This model charges customers based on the traditional labor the AI replaces. It provides a clear ROI, as it ties the cost of the AI agent to measurable productivity gains.

2. Outcome-Based Pricing

Here, pricing depends on the completion of specific tasks or desired outcomes. While intuitive for business users, disputes can arise over whether a goal was successfully achieved, making this model best suited for well-defined tasks like resolving customer service issues.

3. Cost-Plus Pricing

This approach calculates underlying operational costs (e.g., compute, latency, storage) and applies a margin. While transparent, this model may lack the alignment with value delivery that enterprises prefer.

4. Subscription-Based Pricing

Unlimited access via a per-seat subscription creates predictability. However, its utility diminishes when user seats are limited, potentially leaving untapped value on the table.


Why Per-Conversation Pricing Stands Out

The per-conversation model is gaining popularity due to its simplicity and fairness. By charging for every meaningful interaction, enterprises can scale their usage based on demand. As Boston Consulting Group’s Sesh Iyer notes, this model is ideal for organizations with sporadic AI requirements.

However, challenges persist. Token-based consumption models—charging for input and output tokens—are emerging as an alternative but often come with cost variability that enterprises may struggle to manage.


The CIO’s Dilemma: Balancing Predictability and Flexibility

CIOs face a complex decision: balancing financial predictability with operational flexibility. Jeremy Burton, CEO of Observe, cautions against consumption-based pricing, highlighting its potential to cause budgetary overruns. He recommends hybrid models that combine transparency with performance-based incentives, giving enterprises the best of both worlds.

To make informed decisions, CIOs must:

  • Analyze usage patterns to project costs accurately.

  • Diversify agent vendors to prevent lock-in.

  • Align pricing models with organizational priorities.


Virtual Delivery Centers: The Game-Changer for AI Deployment

One of the most transformative approaches to adopting agentic AI lies in the Virtual Delivery Center (VDC) model. A VDC is a dynamic, cloud-based operational hub that offers unmatched scalability and flexibility. It redefines how organizations access and deploy AI agents, talent, and resources, making it a cornerstone of modern enterprise strategy.

What is a Virtual Delivery Center?

A VDC operates as a plug-and-play solution in the cloud, allowing businesses to scale resources and capabilities in real time. Unlike traditional offshore centers, VDCs eliminate geographic constraints, offering enterprises access to a global talent pool while maintaining complete control over operations.

How VDCs Transform AI Agent Pricing

VDCs provide the perfect testing ground for different AI pricing models. Enterprises can experiment with per-conversation, subscription, or outcome-based approaches without the overhead of fixed infrastructure. This flexibility enables organizations to adapt to market demands and optimize costs.

Key benefits include:

  • Scalable Deployment: Scale AI agent usage up or down instantly based on business needs.

  • Cost Efficiency: Avoid long-term commitments and infrastructure costs associated with traditional delivery centers.

  • Global Talent Access: Tap into a diverse pool of AI experts and operational specialists.

  • Predictable Costs: Leverage subscription-based or hybrid pricing models within a controlled environment.

  • Operational Resilience: Ensure seamless operations by integrating VDCs with existing enterprise ecosystems.

The Strategic Advantage

For CIOs, the VDC model is not just a cost-saving measure—it’s a strategic enabler. By integrating VDCs into their operations, organizations can:

  • Drive faster AI adoption.

  • Enhance agility in responding to market changes.

  • Maintain a competitive edge through continuous innovation.

Imagine a scenario where an enterprise deploys a VDC to manage customer service operations. The VDC could host agentic AI solutions, seamlessly handling customer interactions, troubleshooting issues, and optimizing workflows—all while offering a transparent, predictable cost structure.

This ability to experiment with and refine pricing models in a virtual, low-risk environment gives enterprises a significant edge in the evolving AI landscape.


Conclusion: Preparing for the AI-Powered Future

As agentic AI continues to evolve, so too will its pricing models. For CIOs, staying ahead requires not just understanding these models but also aligning them with broader enterprise strategies. The Virtual Delivery Center is an essential component of this strategy, offering a flexible, scalable, and cost-effective platform for AI deployment.

In the end, success lies in embracing transparency, prioritizing predictability, and leveraging innovative solutions like VDCs to transform operations and unlock the full potential of agentic AI.

 

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