The Salesforce Delivery Lifecycle Is Broken: New Research

‘State of Enterprise Systems’ Report Shows 80% of Systems Work Happens Before Any Change is Made — And AI is Making It Worse

NEW YORK, May 12, 2026 (GLOBE NEWSWIRE) -- Enterprise modernization is breaking before execution begins — in the gap between understanding and action — according to new research from Sweep. The report found that the vast majority of the work for a given Salesforce operator — 80% — is dedicated to reconstructing system context.

The analysis, drawn from a sample of more than 12,000 interactions, across +500 operators at over 200 organizations with Sweep’s AI agent, shows teams repeatedly rediscover how their systems work before they can act — turning every change into a multi-step investigation before implementation even starts.

In practice, enterprise systems work follows a three-stage lifecycle: discovery, design and build — but these stages are fragmented across tools, teams, and workflows, and often mired in deep complexity, layered through years of growth, turnover, and one-off projects.

For organizations under pressure to consolidate platforms, deploy AI, or update core systems, that burden carries a measurable cost. The report estimates administrators spend 620 to 1,040 hours per year reconstructing system context — $42,000 to $70,000 annually per admin, or up to $700,000 per year for a 10-person team.

“CIOs are fed up with modernization projects that drag on for years and cost millions,” said Ido Gaver, CEO and co-founder of Sweep. “AI changes that. What used to take 12 months can now be completed end-to-end in days. The real issue is complexity. It kills velocity. Traditional system integrators have built businesses around that inefficiency. AI, paired with deep system context, removes that friction and restores speed.”

Faster generation without full system context introduces a new failure mode.

Agentic tools that do not understand how everything is connected often introduce changes that break other parts of the system. These issues often aren’t caught right away, surfacing days or weeks later when the original context is already lost.

The result is a new form of technical debt: AI-generated metadata that accelerates change in the short term, but increases the time required to diagnose, unwind, and repair systems over time.

The Lifecycle is Fragmented

The research indicates that enterprise systems stall because every change begins with system forensics instead of immediate understanding: What exists? Where is it used? What depends on it? What breaks if it changes?

Across the dataset, those questions dominated. Among the most active users, most of the work happened in the discovery (80%) and design (19%) phases, with dependency tracing, automation discovery, and permissions analysis driving the majority of activity.

The report puts a number to a common failure mode that exists more broadly in the modernization lifecycle: system teams are often forced to treat each part of the journey as a separate phase across different tools, teams, and handoffs. Each project then restarts the same reconstruction effort. In Sweep, because those phases are unified, that effort takes minutes; without Sweep, discovery alone usually requires days or weeks.

AI is Accelerating the Problem

AI is accelerating systems growth, mostly by making it easier to change the system — but notably, it’s not accelerating system understanding.

New tools can generate flows, fields, automations, agents, and code faster than ever. Salesforce's Headless 360, announced at TDX 2026, reflects this shift toward more programmable, agent-accessible systems. But faster generation without structured understanding creates more dependencies for teams to untangle later.

Sweep's research shows this pattern emerging in Agentforce deployments: early work skews toward planning and implementation, but investigation rates climb sharply as systems mature.

The Velocity Tax

The research introduces the concept of a "Velocity Tax" to describe the cost of system work that happens before execution — work that rarely appears on roadmaps or sprint metrics. The human cost shows up in the data. Planning activity more than doubled after 9 p.m., rising from 7.2% during the day to 15.7% at night. And 7.1% of all interactions referenced legacy labels like "DEPRECATED," "DO NOT MODIFY," or "DO NOT DELETE" — informal governance that emerges when systems become too difficult to reason through directly.

The tax is not the work itself. It’s the lack of a system that connects discovery, design and build into a single, compounding process.

The full report, State of Enterprise Systems: Salesforce Edition, includes the complete dataset analysis, the Velocity Tax cost model, early Agentforce findings, and a breakdown of where investigative effort concentrates across metadata types. It is available here.

About Sweep

Sweep is the agentic layer for enterprise systems, giving AI agents the context they need to understand, plan, and govern changes across platforms like Salesforce, Snowflake, and ServiceNow. By connecting discovery, design, and build into one continuous workflow, Sweep helps teams ship projects in days instead of months. Founded in 2021, Sweep is trusted by enterprises including Brex, Wix, LG Electronics, SailPoint, and Coastal. Learn more at www.sweep.io.

Media Contact: Carolyn Adams: sweep@bluerunpr.com

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