Salesforce and Adobe make the same AI-growth bet, but differ on how they would charge customers

Salesforce and Adobe are both betting that artificial intelligence will help pull their subscription-based software businesses back into a higher-growth phase. In a market write-up published by Yahoo Finance via Trefis, the central question is not whether AI is expected to become a major software spending driver, but whether the two companies’ different AI pricing approaches could shape how quickly revenue grows after the initial AI rollout.

The Trefis piece links the companies through a shared investment premise: that AI features and deployments will increase customer demand, renewals, and expansions for enterprise software providers. Salesforce, which sells customer relationship management software and adjacent enterprise tools under a subscription model, is grouped with Adobe, which sells creative and document software and related cloud services, on the assumption that AI capabilities will deepen usage.

Where the analysis says the two companies part ways is in how they charge for AI. Salesforce and Adobe both offer AI functionality embedded in their platforms, but the pricing mechanics determine how easily customers can scale usage as AI becomes more valuable. In the framing presented in the article, Salesforce and Adobe do not rely on the same monetization logic, which becomes important when investors estimate how quickly AI could translate into incremental revenue.

Because the published write-up focuses on the broader “AI will drive growth” thesis rather than a detailed breakdown of each firm’s specific billable unit economics, it does not provide, in the material available here, a full inventory of pricing tiers, add-on structures, or contract terms. As a result, the comparison of “how they charge for it” is best understood as a high-level contrast, not a line-by-line assessment of product packaging.

Salesforce has continued to position AI as a core part of its product roadmap and customer experience strategy, and it operates a newsroom that typically highlights AI-related product updates and partnerships. However, the Trefis article referenced in this report does not cite those updates in a way that allows the comparison to be tested against concrete, disclosed pricing elements in this brief.

The sector backdrop for both companies is that enterprise software buyers are weighing whether AI increases value enough to justify higher subscription spend, longer contract commitment, and new seat or usage-based fees. If AI pricing aligns well with how customers deploy models and workflows, software vendors generally have more room to monetize expansion. If it is mismatched, adoption can be slower or can lead to more scrutiny of ROI.

What remains unclear from the cited post is the degree to which either company’s AI monetization is structured around add-on usage, seat expansion, or platform-level tiering, and whether those details are consistent across regions and customer types. Without those specifics, it is not possible to verify from this packet alone which company’s approach is more tightly connected to AI consumption and which could face greater friction during upsells.

Investors watching the next quarter-to-quarter updates will likely focus on whether AI-driven demand appears in subscription metrics, whether customers expand beyond initial AI pilots, and whether each company’s reported performance suggests that AI features are translating into durable revenue growth rather than one-time experimentation. For now, the common thread is the same: both companies want AI to drive a re-acceleration, but the monetization pathway is the differentiator.