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Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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The enterprise AI landscape is rapidly evolving, with major players racing to embed AI capabilities into their platforms. Salesforce's Agentforce and ServiceNow's Now Assist AI Agents represent two distinct approaches to this market, each with different monetization strategies that reveal much about their vision for AI in the enterprise space.
For SaaS executives navigating these waters, understanding the nuances between these offerings isn't just about technical capabilities—it's about recognizing how these monetization models might impact your long-term technology investments and strategy.
The Core Offerings: What Are These AI Agent Platforms?
Salesforce Agentforce
Salesforce's Agentforce, announced in June 2024, represents a comprehensive AI agent platform built on the company's Einstein 1 platform. It allows businesses to create, deploy, and manage purpose-built AI agents across various customer and employee touchpoints.
The platform leverages Salesforce's extensive CRM data and industry knowledge to create agents that can handle complex customer service inquiries, support sales teams, and streamline operations across departments.
ServiceNow Now Assist AI Agents
ServiceNow's Now Assist AI Agents, introduced in March 2024, is focused primarily on workflow automation within the ServiceNow ecosystem. These agents are designed to handle IT service management, employee workflows, and customer service operations, with a strong emphasis on automating repetitive tasks and providing intelligent assistance to users.
Two Distinct Monetization Approaches
The most striking difference between these offerings lies in their monetization strategies, which reveal their underlying business philosophies.
Salesforce's Multi-Tiered, Use Case-Based Pricing
Salesforce has adopted a use case-specific approach to monetization with Agentforce. According to industry analysts, the pricing structure includes:
- A base platform fee for access to the Agentforce infrastructure
- Additional charges based on specific agent deployments (sales, service, commerce, etc.)
- Pricing tiers based on complexity and capabilities of deployed agents
- Usage-based components including API calls and processing capabilities
This approach aligns with Salesforce's traditional strategy of selling specialized solutions for different business functions. According to Gartner, Salesforce is positioning Agentforce as a premium offering with pricing that reflects the specific business value delivered in each domain.
ServiceNow's Enterprise-Wide, User-Based Model
ServiceNow has taken a different approach with Now Assist AI Agents, opting for:
- A simpler, user-based licensing model integrated into existing ServiceNow subscriptions
- Enterprise-wide access with fewer additional charges for specific use cases
- A focus on delivering AI capabilities as an enhancement to existing workflows rather than as standalone products
According to Forrester Research, ServiceNow's approach emphasizes delivering AI capabilities across the entire platform rather than as specialized tools for specific departments, reflecting its workflow-centric business model.
Strategic Implications for Enterprise Customers
These different monetization models have significant implications for enterprise buyers:
Total Cost of Ownership Considerations
For organizations heavily invested in Salesforce, Agentforce offers deep integration but potentially higher costs as deployments scale across use cases. A Deloitte analysis suggests that while initial implementations may seem comparable in cost, the total investment can diverge significantly as deployments expand.
ServiceNow's model may provide more predictable costs and easier budgeting for organizations looking to deploy AI broadly across workflows, although customization for specialized use cases may require additional investment.
Alignment with Business Structure
Companies with distinct, specialized departments might find Salesforce's model better aligned with their budgeting and organizational structure, as it allows for targeted investments in specific business functions with clear ROI measurement.
Organizations with more integrated operations and cross-functional workflows might benefit from ServiceNow's approach, which enables enterprise-wide AI capabilities without navigating multiple licensing tiers.
Implementation and Adoption Considerations
Beyond pure pricing, these models influence how organizations implement and adopt AI technologies:
Salesforce Agentforce: Specialized Excellence
The use case-based monetization encourages targeted, high-impact implementations:
- Focused rollouts for specific departments with clear business cases
- Potentially deeper functionality in specialized areas
- More granular control over AI investments and scaling
- Ability to prioritize deployment based on ROI potential
ServiceNow Now Assist: Enterprise-Wide Transformation
The user-based model encourages broad adoption across the organization:
- Easier deployment across multiple workflows and departments
- Potentially faster organization-wide adoption
- Simpler procurement and licensing management
- Focus on improving the entire workflow ecosystem rather than point solutions
The Future Evolution of These Models
Both companies are likely to refine their approaches as the market matures. Industry analysts from IDC predict that:
- Salesforce may introduce bundled offerings that combine popular agent use cases as the market matures
- ServiceNow may develop more specialized agent capabilities while maintaining its user-based pricing approach
- Both may introduce more consumption-based elements as organizations scale their AI usage
Making the Right Choice for Your Enterprise
For SaaS executives evaluating these platforms, the decision extends beyond technical capabilities to strategic alignment:
Consider Your Organization's AI Strategy
- Is AI adoption primarily targeted at specific high-value functions, or part of a broader transformation?
- Does your budgeting process favor departmental technology purchases or enterprise-wide platforms?
- How do you measure and attribute the value of AI investments?
Evaluate Your Existing Technology Landscape
Organizations heavily invested in either ecosystem may find economic advantages in staying with their primary vendor, but should carefully model long-term costs based on expected adoption patterns.
Plan for Scale
Both models present different economic characteristics at scale:
- Salesforce's model may show increasing costs as more use cases are deployed, but with targeted value
- ServiceNow's approach potentially offers more predictable scaling costs but may require additional investment for highly specialized applications
Conclusion
Salesforce Agentforce and ServiceNow Now Assist AI Agents represent not just competing products but fundamentally different philosophies about how AI should be monetized and deployed in enterprise settings.
Salesforce's use case-based approach reflects its heritage in specialized business solutions, promising deep capabilities tailored to specific functions. ServiceNow's user-based model aligns with its workflow-centric vision, positioning AI as an enhancement to existing processes across the organization.
For enterprise buyers, the choice between these models should be guided not just by immediate needs but by long-term AI strategy, organizational structure, and how technology investments are budgeted and evaluated. As both platforms continue to evolve, understanding these monetization approaches provides valuable insight into how each vendor envisions AI's role in the enterprise—and which vision best aligns with your organization's future.