Now Claude Managed Agents Threaten Edge Networks

Add edge networks such as Akamai, Fastly and Cloudflare to the list of enterprise software of service providers that might be disrupted or helped by growing use of language models and especially agents. 

And blame Anthropic for the recent concern. Claude Managed Agents, launched April 8, 2026 in public beta, handles sandboxed code execution, checkpointing, credential management, scoped permissions, and end-to-end tracing.

Investors seem to be pricing in only danger, but upside arguably also exists.

The core tailwind is simply volume. Cloudflare's CEO noted that if a human were shopping for a digital camera and might visit five websites, an AI agent doing the same task might visit 5,000. 

In fact, AI bot traffic across the Akamai network surged more than 300 percent since Akamai began tracking it, with AI training crawlers accounting for the largest share. 

One might point to earlier concerns about Akamai capital spending that has rattled equities of many types, but that does not seem to be the impetus for the declines of April 10. 

Fastly has noted that inference operations likewise are providing a big boost to its revenue. 

So why did Akamai stock sell off sharply, about 17 percent, on the news? Cloudflare sold off 13.5 percent on April 10. And Fastly sold off nearly 22 percent on the same day. 

Simply, Claude Managed Agents threatens to move much of that former “outsourced” or external traffic “in house.” Claude is now arguably getting into the infrastructure layer for agents, as a potential competitor. 

Impact area	Mechanism	Direction	Effect on CDNs	Who benefits	Source
Explosive growth in bot & agent traffic	Claude Managed Agents spawn long-running sessions that browse the web at machine speed — the Cloudflare CEO noted agents may visit 1,000× more sites than a human doing the same task. Akamai tracked a 300% rise in AI bot traffic across its network in 2025.	tailwind	More requests, bandwidth, and cache-hit pressure — CDNs must handle vastly more non-human HTTP volume.	All three; Cloudflare leading	TechCrunch
Edge inference & AI Gateway demand	Anthropic routes MCP tool calls through third-party services; CDNs like Cloudflare offer AI Gateway products that proxy and cache LLM API calls at the edge. Workers AI inference requests grew 4,000% YoY in Q1 2025.	tailwind	New high-margin inference and gateway revenue streams open up for CDNs that offer edge compute.	Cloudflare (Workers AI, AI Gateway); Fastly (semantic caching)	Klover.ai
MCP server hosting & orchestration	Claude Managed Agents connects to external services through MCP servers. Cloudflare extended its Workers platform with MCP Server Portals; Fastly offers edge orchestration for MCP-style workloads.	tailwind	CDNs become the natural 'control plane' for routing agent tool calls with low latency and built-in auth.	Cloudflare (MCP Server Portals); Fastly	Cloudflare blog
Bot management & agent identity	Agents generate traffic that is hard to distinguish from malicious bots. Akamai and Cloudflare must evolve bot management to allow legitimate agent traffic while blocking bad actors. Cloudflare & GoDaddy partnered specifically to separate trusted agents from scrapers.	tailwind	Increased demand for bot management, agent identity verification, and WAF rule updates.	Akamai (Bot Manager); Cloudflare (Bot Fight Mode)	The Register
DDoS & security complexity	AI agents can be weaponised or exploited. Cloudflare mitigated a 31.4 Tbps DDoS attack in Q4 2025; hyper-volumetric attacks grew 700% that year. Managed agent traffic is a growing attack surface.	tailwind	Higher security service revenue; CDNs are critical infrastructure for absorbing AI-amplified attack volumes.	All three; Cloudflare most exposed	Cloudflare 2026 report
Semantic caching of agent queries	AI agents issue repetitive or semantically-similar requests. Fastly's 'AI Accelerator' uses semantic caching to avoid redundant inference passes. Cloudflare AI Gateway adds response caching across providers.	tailwind	New caching product category; CDNs monetise the gap between raw inference cost and cached delivery.	Fastly (AI Accelerator); Cloudflare (AI Gateway caching)	Futuriom
Anthropic runs its own agent infrastructure	Claude Managed Agents runs on Anthropic's own infrastructure — sandboxed containers, state management, and orchestration are all handled in-house. This keeps a large slice of compute spend inside Anthropic's cloud, not CDN PoPs.	headwind	Enterprises that previously self-hosted agents (and used CDN edge compute for inference) may shift workloads onto Anthropic's platform instead.	Cloudflare Workers AI; edge compute providers	The New Stack
Disintermediation of traditional CDN caching	AI agents retrieve answers from Claude rather than browsing cached web pages, reducing human-driven page requests. If AI mediates content discovery, fewer end-user requests reach CDN-cached origin servers.	headwind	Long-term erosion of traditional web caching revenue as human page views decline relative to bot/agent queries.	Akamai (most exposed, hardware-intensive legacy CDN model)	FinancialContent
AI-driven content disengagement	Akamai observed agentic traffic declining post-Cyber Week 2025 because many sites lack the structured data agents need. Agents disengage from unoptimised sites, shifting traffic away from poorly-structured CDN customers.	headwind	CDN customers in retail/media face traffic shifts if they don't optimise for agent consumption, reducing effective CDN utilisation.	Akamai customers in retail & media	Akamai AI Pulse
Capital expenditure burden (Akamai-specific)	Akamai is investing heavily in physical GPU inference infrastructure (Akamai Inference Cloud). CapEx is projected at 23–26% of revenue in 2026, weighing on margins even as AI-adjacent revenue grows 45%.	mixed	AI agents drive new revenue but at the cost of high capital intensity for hardware-focused CDNs — software-defined competitors benefit more.	Akamai (headwind); Cloudflare (tailwind — software model)	FinancialContent
Agentic content monetisation standards	Akamai predicts that 'agentic commerce will scale only where trust and permission are clearly established.' Agent identity frameworks (Visa Trusted Agent Protocol, Skyfire KYA) will require CDN-level enforcement of who agents are and what they can access.	mixed	CDNs that build agent identity and permission infrastructure early win new platform revenue; laggards become 'dumb pipes'.	All three — early movers win higher-margin platform roles	Akamai AI Pulse

So even if some tailwinds exist, Claude Managed Agents threaten to transform some of those tailwinds into headwinds. 

The key headwind is that Anthropic runs Managed Agents on its own cloud infrastructure. Users simply describe the agent, and Anthropic handles sandboxing, authentication, and tool execution. 

This keeps substantial compute spend inside Anthropic's own stack rather than at CDN edge nodes.

 

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