Lanai Releases 2026 AI Labor Report: Enterprises Are Using AI at Scale, But Can't Prove What It Produces

79% worry their AI budgets will be cut because the spend can't be tied clearly to revenue or profit

SAN FRANCISCO, June 9, 2026 /PRNewswire/ -- Lanai, the Enterprise AI Accountability Company, released its 2026 AI Labor Report, unveiling that while AI has become part of the workforce in large companies, executives lack visibility into business workflows and impact. Based on a survey of 200 U.S. technology executives at organizations with 1,000 or more employees, the report shows most organizations cannot say clearly what AI produced, what it cost per unit of work, or how to defend the budget that funds it.

The data shows that 92% of leaders say their organization tracks the financial and efficiency impact of AI-generated work. In practice, only 2% say more than half of that work is actually recorded as a business outcome. AI may be doing the work, but the ledgers do not reflect that.

Lanai's executive team describes this pattern as "AI labor orphaning" — AI systems perform work, but that work never formally enters financial systems, performance records, or systems of record. The output is real but the accounting for it is missing.

"Those aren't just quirky statistics; they raise basic questions about the numbers executives rely on," said Lexi Reese, co-founder and CEO of Lanai. "If AI is doing a meaningful slice of the work but never shows up in the ledgers, how confident can you be in your P&L, your headcount plan, or the org chart you use to run the place?"

Key findings from the 2026 AI Labor Report include:

• 90% of organizations lack a single, dedicated function responsible for tracking how AI delivers ROI. AI accountability is scattered across finance, IT, operations, and business units, leaving no one clearly responsible for proving whether AI is creating measurable value or simply adding another layer of cost.
• 87% of organizations credit AI-assisted output entirely to the human employee, sometimes or always. Performance reviews, promotion decisions, and bonus pools are effectively built on work where the machine contribution is invisible — not because anyone is hiding it, but because no system was built to record it any other way.
• 88% have no formal methodology for attributing business outcomes to AI. 43% assume that if AI was involved, it contributed. 38% rely on educated guesses about correlation. Only 12% have a defensible answer when the CFO asks.
• 100% of organizations still require human review after AI generates work. None report fully autonomous workflows. The dominant model is supervised machine labor: AI drafts, classifies, and flags; humans check, edit, and approve. The AI that vendors are selling is not the AI enterprises are running.
• 53% estimate that most automated work runs through unmonitored shadow applications. In many firms, the AI that finance and IT approved is not the AI doing most of the work.
• 79% are concerned AI budgets will be cut because spending cannot be tied clearly to revenue or profit. Ninety-six percent have already lost at least one ROI opportunity because they lacked visibility into how AI made decisions. This is not a future risk. It is happening in budget cycles right now.
• The 12% benchmark. The organizations pulling ahead treat AI execution cost as a labor line rather than a generic IT expense, build attribution methodology before the CFO asks for it, and record AI contributions in the financial systems executives actually use. They are the only ones who can answer the board with confidence.

"These are not just measurement gaps; they're cracks in how companies describe themselves on paper," Reese said. "If AI's share of the work never shows up in the accounts, then the P&L, unit costs, and even the organizational chart start to drift away from how the business actually operates. You can't plan hiring, investment, or restructuring on numbers that leave out an entire category of labor."

The report also challenges the idea that large enterprises are on the brink of fully autonomous operations. Every organization surveyed said that a human still needs to review or intervene after AI generates work. For most firms, AI is not a self-driving system; it is a set of tools that change who does which part of the job.

"Right now, the story inside big companies is not that the robots took over," Reese said. "It's that AI quietly took on pieces of the job — writing the first draft, sorting the queue, flagging the anomalies — while people stayed responsible for the final call. The accounting and governance systems just haven't caught up to that split."

The full 2026 AI Labor Report is available at withlanai.com/ai-labor-report.

Methodology
The Lanai Survey was conducted by Wakefield Research among 200 U.S. tech leaders and executives at organizations with 1,000+ employees, between March 20th and April 8th, 2026, using an email invitation and an online survey. Results of any sample are subject to sampling variation. The magnitude of the variation is measurable and is affected by the number of interviews and the level of the percentages expressing the results. For the interviews conducted in this particular study, the chances are 95 in 100 that a survey result does not vary, plus or minus, by more than 6.9 percentage points from the result that would be obtained if interviews had been conducted with all persons in the universe represented by the sample.

About Lanai
Lanai is an enterprise AI accountability company. Its AI @ Work Operating System helps organizations understand how AI is being used across the business by automatically discovering workflows powered by copilots, autonomous agents, and AI embedded within SaaS tools. Lanai measures the leverage AI creates, tracks adoption across teams, and connects usage to the business outcomes leaders are responsible for. The company is led by co-founder and CEO Lexi Reese, former COO of Gusto and a longtime Google leader, alongside CTO Rajesh Raman, formerly of Google, Meta, and Splunk, and CPO Mohit Mehta, formerly of SignalFx (Splunk) and Cumulus Networks (Nvidia). Lanai is backed by Lux Capital, Juxtapose, BAG Ventures, f7ventures, and BenchStrength.

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SOURCE Lanai