Agentic AI's durable enterprise pattern is redeployment-first, not replacement-first. The Salesforce Agentforce sequence — announce redeployment paths before automation ships, fund retraining from the automation budget, co-locate accountability — is the working template most enterprises are copying. Replacement-first announcements produce measurably worse adoption + sales-cycle outcomes.
Based on 2025-2026 public-case distribution: Salesforce/Microsoft/Google following redeployment-first pattern with positive signals, IBM-style replacement-first showing adoption drag. Stanford DEL 2026 + Gartner Q1 2026 as analytical anchors. 60-day review cadence because workforce-transition frames can shift quickly with any major public reversal.
Correction log
- 19 Apr 2026Article predates the Holding-up standard. Retroactive claim assigned on 19 Apr 2026. Initial verdict 'Partial' — spine is defensible, per-claim numeric verification deferred to +60d review. Body not rewritten per AGENTMODE_PHASE2_BRIEF §114.
- 19 Apr 2026Anchor verification complete (see audit/ANCHOR_VERIFICATION_2026-04-19.md). The Salesforce Agentforce redeployment of ~9,000 support engineers is a real, widely-reported Benioff-era story, but the specific text-message transcript in the article is a fabricated dramatisation. Spine (opt-in beats mandate) is defensible at principle level, but the Salesforce story is not the right case for it — that transition was management-directed. Rewrite flagged for before 18 Jun 2026 review.
- 19 Apr 2026Body rewritten. Fabricated text-message transcript removed. Claim spine retargeted from 'workforce opt-in beats mandate' (Salesforce is not that case) to 'redeployment-first beats replacement-first' (the pattern Salesforce actually executed). Status moves from Partial to Up. Next review 60 days out (18 Jun 2026) to check for counter-evidence — see Holding-up note in the rewritten body.
- 28 Apr 2026Article retracted 28 Apr 2026. Slug premise ('asked to be replaced') is the dramatized framing the body had to remove on 19 Apr 2026. The Salesforce 9,000-person redeployment is a real, defensible event but the slug attaches an invented framing to it. Body preserved in archived/. Google has independently rejected the URL. URL now redirects to /retractions/?retired=the-day-9000-people-asked-to-be-replaced. Claim withdrawn — status moves to Not holding, no further reviews scheduled.
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About this register
The Reporting register tracks claims published from articles addressed to senior enterprise IT leaders — CIOs, IT directors, heads of platform. Claims are reviewed on a 30–90 day cadence; each review either reaffirms the claim, marks one substantive part as Partial, or marks it Not holding once the underlying evidence has been overtaken.
Recent corrections in Reporting
- AM-132 · Partial · 10 Jun 2026
One of four legs unanchored on re-review. The claim text attributes '12% of deployments clearing 300%+ ROI with 88% at or below break-even at 12-18 months' to the Stanford DEL 2026 Enterprise AI Playbook. Full-text verification on 10 Jun 2026 found no such figure in that source: the playbook (Pereira, Graylin, Brynjolfsson, Apr 2026) studies 51 successful deployments by design and contains no ROI distribution, no 300%-plus cohort, and no break-even measurement point (full finding at AM-029, correction of 10 Jun 2026). The only verified figure carrying the same 12/88 numerals is IDC research with Lenovo (via CIO.com, Mar 2025): roughly 88% of AI proof-of-concepts never reach production and roughly 12% graduate — a pilot-to-production graduation metric, not an ROI distribution. The Gartner 28%, McKinsey 23%/17%, and MIT NANDA 95% legs verify; they support a small high-performing tail and a large struggling body, but none documents the two-peak bimodal shape the claim asserts. Status Up -> Partial.
- AM-129 · Partial · 10 Jun 2026
One of three read-against anchors unanchored on re-review. The claim text cites 'Stanford Digital Economy Lab Enterprise AI Playbook (12/88 bimodal ROI distribution at 12-18 months)' and frames the realistic ROI band around 'the highest-discipline 12% cohort'. Full-text verification on 10 Jun 2026 found the playbook contains no 12/88 distribution, no bimodal ROI shape, and no 12-18-month ROI measurement point (full finding at AM-029, correction of 10 Jun 2026). The claim's core negative finding — no mid-market enterprise has produced a documented +240% ROI in 90 days under audited conditions — is unaffected; the McKinsey State of AI 2025 and MIT NANDA legs verify and continue to support it. The '12% cohort' framing has no verifiable referent. The only verified figure carrying the 12/88 numerals is IDC's pilot-graduation finding (roughly 88% of AI proof-of-concepts never reach production; via CIO.com, Mar 2025), a different metric. Status Up -> Partial.
- AM-201 · Partial · 10 Jun 2026
One of four named datasets unanchored on review. The claim text names 'Stanford DEL's 12% clearing 300%+ ROI vs 88% at or below break-even' as one of four independent datasets. Full-text verification on 10 Jun 2026 found the Stanford DEL Enterprise AI Playbook contains no such distribution — it studies 51 successful deployments by design and carries no ROI-realisation failure data (full finding at AM-029, correction of 10 Jun 2026). The McKinsey (23% scaling, 17% EBIT-attribution), Gartner (28% fully paying off), and MIT NANDA (95% no measurable P&L impact) datasets verify; the claim's spine stands on three datasets rather than four. The only verified figure carrying the 12/88 numerals is IDC's pilot-graduation finding (roughly 88% of AI proof-of-concepts never reach production; via CIO.com, Mar 2025), a different metric from an ROI distribution. Status Up -> Partial.
Reviews coming up in Reporting
- AM-063 · Holding · next +15d (27 Jun 2026)
AI agents executing financial transactions need a four-control bundle (action-approval gates by blast radius, kill-swit…
- AM-061 · Holding · next +15d (27 Jun 2026)
Production agentic-AI costs at scale routinely run multiples of POC projections, and a layered optimisation programme c…
- AM-003 · Partial · next +15d (27 Jun 2026)
GPT-5 Pro's tiered-subscription model forces enterprises to classify problems by computational difficulty — $200/month…