Marc Benioff believes that AI will increase the value of Salesforce, rather than reduce it.
Speaking to the Wall Street Journal, the Salesforce CEO spoke out against investor concerns that AI could destroy enterprise software companies, pushing back on the possible “SaaS-pocalypse” idea.
This reflects a broader debate in the market about whether AI will disrupt SaaS business models or strengthen their role in enterprise technology.
“People think we have our back against the wall when in fact the opportunity has never been greater,” he said.
In an earlier interview with CNBC in March, Benioff reaffirmed that there is no evidence that AI is hurting SaaS demand.
“Our customers are doing more with AI, but to say there’s some kind of SaaS-pocalypse going on?
“We don’t see it in our pipelines, and we don’t see it in our numbers.”
Misplaced Fears of AI Disruption
Benioff argues that the fears of AI wiping out SaaS are misplaced, as investors express concerns that AI agents could reduce the need for human workers, undermining the traditional per-seat pricing model used by Salesforce and similar firms.
In his interview, Benioff claimed that AI is not replacing enterprise software but instead increasing its importance, arguing that managing customer data, workflows, and enterprise trust cannot simply be replicated by standalone AI tools.
Leading AI campaigns are more likely to partner with platforms like Salesforce, he suggests, as enterprise-grade systems require integration, security, and compliance capabilities that go beyond raw AI models.
With Salesforce actively repositioning itself to align with this shift by embedded AI into its products, early results show productivity gains in areas such as customer service or internal support, including the automation of routine queries and reduced workloads.
Benioff also argues that Salesforce’s evolving business model has helped to ensure the firm’s longevity, acknowledging that whilst AI may reduce the number of human users, which challenges per-seat pricing, he frames this shift as a transition rather than a threat.
Having introduced usage-based metrics such as Agentic Work Units to measure the output of AI systems rather than the number of employees, this allows Salesforce to move from selling access to software to selling outcomes generated by AI-driven software.
Investor Concerns Over AI Disruption
The wider outlook, however, remains concerned that AI represents a structural threat to the SaaS model rather than an incremental improvement.
This includes fears that AI agents can automate many of the tasks currently performed by human workers, particularly in customer service, sales operations, and internal workflows.
If fewer employees are needed to maintain workflow productivity, companies may reduce the number of software seats required, directly undermining the subscription-based pricing model that companies like Salesforce depend on, representing a near-term financial risk.
AI could also reduce the need for standalone software as new generative tools become increasingly capable of writing code, building applications, and orchestrating workflows through natural language.
As a result, businesses could start creating their own lightweight tools instead of paying for expensive, pre-built SaaS platforms, eroding the differentiation and pricing power of SaaS providers.
There is also a broader shift in where value may sit in the technology stack, as concerns grow that value could move away from application-layer companies like Salesforce and toward AI model providers or infrastructure companies.
By making AI the primary interface for workflows, SaaS platforms risk being reduced to back-end systems with less pricing leverage, likely compressing margins and leading to lower valuations across the sector.
Uncertainty around current business models also drives recent concerns, as the transition from per-seat pricing to usage-based or outcome-based pricing is not yet fully proven at scale, meaning increased uncertainty for whether AI-driven revenue streams can replace or exceed traditional SaaS growth.
Furthermore, despite Salesforce seeing improved results from embedding AI, other organizations continue to find that the technology still struggles with complex or nuanced interactions, requiring significant data preparation before it works effectively.
By challenging the stability of data readiness, integration, and reliability, this creates a gap between the long-term promise of AI and the short-term financial outlook, contributing to negative perceptions in the market.
The Pricing Model Uncertainty
AI could threaten to reshape or weaken the economics of SaaS, even in cases where revenue is stable; there is potential disruption to the traditional software model.
If automation leads to fewer users while pricing shifts to usage or outcomes, revenue visibility and growth rates may become less predictable, and could create pressure on valuations, especially for companies that rely heavily on subscription scale and expansion within large workforces.
This outcome also depends on how effectively SaaS providers integrate AI into their platforms and retain control over customer workflows and data, meaning if companies like Salesforce succeed in positioning themselves as essential infrastructure for AI-driven operations, they may preserve or even expand their role in the enterprise stack.
If unsuccessful, value could shift toward AI-native tools or model providers, leaving traditional SaaS platforms with reduced pricing power.
