The defining question for ServiceNow and Salesforce in 2027 is no longer whether they can articulate compelling agentic use cases. It is whether those use cases begin driving meaningful consumption on their platforms. Both companies have been messaging that opportunity for months, but 2027 should show whether early momentum can translate to sustainable growth.
In TBR’s opinion, the decision to pursue a more embedded services posture with FDEs suggests two things: Agentic AI technology has reached a point where vendors are willing to raise the stakes and work directly with customers to enable hands-on adoption support, and AI value remains very hard to deliver. By putting boots on the ground, vendors are betting that the right FDE paired with the customer’s technical talent can identify the opportunities for agentic automation that overcome these adoption hurdles, expand usage, and convert AI experimentation into repeatable commercial value.
The AI market is not failing to meet its promise, but it is still early in translating that promise into broad-based economic value. Three years into the GenAI cycle, the largest pools of revenue remain concentrated in the infrastructure layers required to train, deploy and scale frontier models. That concentration is rational given the scale of compute demand, but it is not a sustainable end state if AI is to become a true enterprise productivity platform.
KPMG appears to be attempting to move the competitive battleground from implementation speed to governed operations. If the market evolves in this direction, partners and competitors will need to clarify their roles and demonstrate credibility in an environment where agentic transformation is treated less as a discrete project and more as a continuously governed system.
TBR Insights Live session: How PaaS revenue will outpace SaaS revenue among cloud software vendors, why SaaS incumbents will position SLMs as a foundational part of their AI strategies, and whether the question, “Will AI be the death of SaaS?” will remain relevant
Enterprise customers are prioritizing the modernization of their existing SaaS estates rather than adding new applications, driven by market saturation, accumulated technical debt, and a growing imperative to become AI-ready. As IT buyers shift their focus toward modern platforms, traditional SaaS leaders should expect their PaaS segments to continue significantly outperforming their core SaaS businesses in revenue growth.
The emerging pattern of multicloud security consolidation has direct implications for both Amazon Web Services (AWS) and Microsoft, as enterprises reassess detection pipelines, governance models and operating frameworks heading into 2026. Although AWS remains well positioned in analytics-heavy workloads, the company needs to reevaluate its long-established “building block” approach, especially as peers deliver more integrated platforms. For Microsoft, its strengths will continue to be with organizations where Microsoft 365 already anchors their identity and collaboration strategies.
Today, SaaS is far from dead, but it has reached an unmistakable inflection point. The model that reshaped enterprise software over the last 20 years has reached maturity just as a new layer of intelligence is forming above it. The result is a market that still depends on SaaS but no longer treats it as the strategic center of gravity. What once looked like a stable, compounding growth engine now looks more like baseline infrastructure supporting a different kind of workflow. As a result of this shift, the market is wondering whether SaaS applications will continue to define enterprise workflows or whether that role is shifting to AI-native platforms and agentic systems.
Join TBR for a discussion on the most critical elements of a successful hyperscaler partnership and partner perceptions of Amazon Web Services, Microsoft and Google Cloud
In 2025 no conversation is complete without recognizing the platform implications of agentic workflows. Behind the scenes, Sage is preparing for an agent-first architecture by integrating emerging frameworks, such as Model Context Protocol (MCP) or Agent 2 Agent (A2A), directly into its platforms. The long-term goal is to coordinate these through super agents and plug into the broader agent ecosystem (Salesforce, Microsoft, Google), but this is still only part of the long-term road map.