How Close to a Bottom are CRM, MSFT, ADBE, ORCL, SAP, NOW?

According to Goldman Sachs analyst Matthew Martino, investors need to consider six different aspects of how artificial intelligence might affect an enterprise software supplier’s business:

• Orchestration risk: The possibility that horizontal AI agent layers can bypass the platform and become the primary generator of value

• Monetization model: Whether a business model is tied to users, which makes it more vulnerable, or assets and data, making it more durable

• System-of-record ownership: If the platform governs approvals, compliance, and execution, it is harder to displace

• Data and integration moat: Whether workflows depend on proprietary signals, structured data, and operational records that live inside the platform and must be accessed through it

• AI execution: Whether the company is delivering real, embedded capabilities rather than conceptual roadmaps

• Budget alignment: Determines whether AI adoption increases or decreases the strategic priority of the category. 

For investors, the key takeaways might be:

• Pure workflow or UI-heavy tools are more exposed; systems handling intricate enterprise logic less so

• Subscription models linked to business scale rather than headcount tend to hold up better as AI automates tasks

• Core ERP, financial systems, CRM with compliance hooks, or regulatory platforms are harder to displace

• AI agents amplify the value of clean, governed, real-time data rather than replacing it

• Execution separates fast followers who reinforce their moat from those getting disrupted. Incumbents with domain data have an advantage here

• Look for categories where AI creates tailwinds, like data platforms, cybersecurity, vertical SaaS with complex compliance, or physical-to-digital workflows.

Company	Orchestration Risk	Monetization Model	System-of-Record Ownership	Data & Integration Moat	AI Execution	Budget Alignment
Salesforce (CRM)	Moderate (−) Agentforce agents could be orchestrated externally, but platform workflows limit full bypass	Strong (+) Shifted to agentic ELAs + consumption (per conversation/action); Agentforce ARR ~$800M+ and growing fast	Strong (+) Core CRM is authoritative for customer data, approvals, compliance	Strong (+) Deep customer interaction history, proprietary signals, Data Cloud integrations	Strong (+) Shipping real agents (Agentforce) with measurable ROI; Einstein embedded	Strong (+) AI boosts CRM priority & spend (more data, governance, agent infra)
ServiceNow (NOW)	Moderate-Strong (+) Complex, multi-system IT/service workflows hard for horizontal agents to fully orchestrate	Strong (+) Now Assist “Pro Plus” premium tiers + consumption upside; ACV >$600M–$1B run-rate	Strong (+) System-of-record for IT/service management, approvals, audit trails	Strong (+) Proprietary operational workflows + deep integrations across enterprise tools	Strong (+) Now Assist agents delivering real value; infrastructure fully cloud-native for AI scale	Strong (+) AI adoption increases strategic priority of service/ops platforms
Oracle (ORCL)	Strong (+) Deep ERP/supply-chain/finance processes resist simple agent bypass	Moderate-Strong (+) Mix of license + cloud consumption; moving toward outcome-based	Strong (+) Authoritative ERP/finance/supply chain system-of-record with compliance hooks	Strong (+) Massive proprietary enterprise data across finance, supply chain, HR	Strong (+) Using AI to build full automated processes (not just copilots); ahead on domain execution per some peers	Strong (+) AI tailwinds for database/cloud infra spend
Workday (WDAY)	Moderate (−) HR/finance copilots can partially bypass UI; more replicable workflows	Moderate (−) Still largely seat/user-tied; slower shift to consumption	Strong (+) Core HR/finance system-of-record for employee data & compliance	Moderate (−) Data is relatively standardized vs. highly proprietary; easier for AI to replicate externally	Moderate (+) Has copilots but viewed as lagging some peers on full agentic execution	Moderate (+) AI helpful but could shift some budget away from traditional HCM suites
SAP (SAP)	Strong (+) ERP complexity & regulatory workflows make full orchestration bypass difficult	Moderate-Strong (+) Cloud shift + some consumption elements; historical pricing power	Strong (+) Dominant global ERP system-of-record for finance, supply chain, compliance	Strong (+) Deep structured operational data + decades of integrations	Moderate-Strong (+) Embedding AI into core ERP; fast-follower re-architecture	Strong (+) AI increases need for governed ERP data & execution layers
Adobe (ADBE)	Moderate (−) Generative tools could let agents bypass some creative workflows/UI	Moderate-Strong (+) “Generative Credits” + consumption model for Firefly; shifts value capture to usage	Moderate (+) Creative asset system-of-record but less regulatory/compliance weight	Moderate-Strong (+) Proprietary creative workflows + Firefly-trained data moat	Strong (+) Firefly & generative AI delivering real embedded capabilities; strong execution in content	Moderate-Strong (+) AI boosts content creation budget but compresses some per-seat value
Snowflake (SNOW)	Moderate (−) Data platform can be bypassed as pure backend; agents query elsewhere	Strong (+) Consumption-based (compute/data usage); Cortex AI adds monetization vectors	Moderate (+) Strong data platform but not always the business process system-of-record	Strong (+) Data cloud moat + governance; AI amplifies need for clean, governed data	Strong (+) Cortex AI services shipping real capabilities on customer data	Strong (+) AI dramatically increases data volume/query spend (force multiplier)
MongoDB (MDB)	Moderate (−) Flexible document DB can be commoditized by agents using open formats	Strong (+) Consumption-based usage; vector search/AI integrations drive upside	Moderate (+) Application data store but rarely the final system-of-record	Moderate-Strong (+) Developer-friendly data + vector capabilities; less proprietary than ERP data	Moderate-Strong (+) Vector search & AI app tools executing well; benefits from AI dev boom	Strong (+) AI apps drive more database consumption and developer spend

And even if all that is correct, the palpable investor fears about how to value enterprise software firms do not seem to be abating. But some analysts think a “new normal” valuation level is close to stabilizing. 

Software Segment	Current/Projected "Floor" P/E (Forward)	Historical Context
Mega-Cap SaaS (Microsoft, SAP)	28x – 32x	35x+
High-Growth / "Rule of 40" (ServiceNow, CrowdStrike)	45x – 55x	80x – 100x+
Mature / Cyclical Enterprise (Salesforce, Oracle)	18x – 24x	25x – 30x
Infrastructure / Dev Ops (Datadog, Snowflake)	50x – 60x	100x+
Mid-Market / "Broken" SaaS	12x – 16x	25x

In 2021, software was valued on Enterprise Value/Revenue (often 15x–20x). 

Analysts now believe the stable floor is EV/Free Cash Flow or Forward P/E. 

For a standard healthy software company, a 5x–6x revenue multiple is now considered "stable," whereas 10x or more is reserved only for elite AI-winners.

Analysts at firms including Goldman Sachs and Morgan Stanley believe "legacy" enterprise software could fall further (P/E of 12x–15x) if they cannot prove AI utility.

Based on those estimates, there is considerable danger of further downside.  

Company	Est. Forward P/E (FY 2026)	Trend vs. 5-Year Average	Valuation Driver
Microsoft	22.4x – 23.2x	~30% Compression	Balanced by Azure AI growth and office productivity dominance.
Adobe	23.5x – 25.0x	~20% Compression	Premium maintained due to Firefly AI integration in Creative Cloud.
Salesforce	20.8x – 22.0x	Significant Reset	Shift toward margin expansion and buybacks over aggressive M&A.
Oracle	18.8x – 19.5x	Relatively Stable	Lifted by OCI (Oracle Cloud Infrastructure) demand for AI training.
SAP	21.0x – 22.5x	~15% Compression	Resilient due to "sticky" ERP migration to S/4HANA Cloud.
Workday	43.1x – 43.5x	>50% Compression	Transitioning from high-growth SaaS to a mature HCM platform model.

Analysts at J.P. Morgan and Bessemer note that legacy firms are now strictly valued on their ability to maintain a combined growth and profit margin of 40 percent (“the rule of 40”). Firms falling below this are seeing P/E multiples dip into the mid-teens.

Also, private consensus is that software multiples will not return to 2021 levels unless the 10-Year Treasury falls below three percent. As long as rates remain "higher for longer," analysts are modeling a permanent 20-percent haircut on terminal valuation multiples compared to the last decade.

source: MacroMicro