Perly Consulting │ Beck Eco

The State of Play

A living index of AI adoption across industries — where established practice meets the bleeding edge
UPDATED DAILY

The AI landscape doesn't move in one direction — it lurches. Some techniques leap from experiment to table stakes in a single quarter; others stall against regulatory walls, technical ceilings, or organisational inertia that no amount of hype can dislodge. Knowing which is which is the hard part. The State of Play cuts through the noise with a rigorously maintained index of AI techniques across every major business domain — classified by maturity, evidenced by real-world adoption, and updated daily so you always know where you stand relative to the field. Stop guessing. Start knowing.

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AI Maturity by Domain

Each dot marks the weighted maturity of practices within a domain — hover for a brief summary, click for more detail

DOMAIN
BLEEDING EDGEESTABLISHED

Spreadsheet & data task automation

BLEEDING EDGE

TRAJECTORY

Stalled

AI that automates spreadsheet tasks including formula creation, data analysis, pivot tables, and formatting from natural language. Includes Excel/Sheets AI assistants and formula generation; distinct from natural language to SQL which queries databases rather than manipulating spreadsheets.

OVERVIEW

AI-driven spreadsheet automation works in narrow, structured workflows -- and struggles nearly everywhere else. That split defines the practice's stalled position at bleeding-edge. Accounting and finance teams have extracted real value: 60% adoption rates, measurable time savings, and fast payback cycles. But these wins have not generalised. Gemini in Sheets achieves 70.48% accuracy on complex real-world tasks, nearing human baseline; independent testing of Copilot in Excel shows formula generation succeeds 7/10 times on first attempt. Yet these capability gains mask a widening governance crisis: CSA survey (418 security professionals) finds 82% of organizations discovered ungoverned shadow agents, 65% experienced security incidents, 61% reported data exposure. Finance ROI remains trapped in a measurement gap: Deloitte survey of 1,300+ finance leaders shows 63% deployed automation but only 21% report clear, measurable ROI. Formula injection attacks (Ramp Labs vulnerability) and permission-drift risks demonstrate the automation is outpacing governance capability. Until shadow-agent visibility, lifecycle management, and formula-level security are resolved, adoption will remain confined to teams with well-defined, repetitive data workflows in compliance-light domains.

CURRENT LANDSCAPE

May 2026 announcements confirm vendor feature velocity but reveal critical governance and security gaps replacing feature limitations as the central barrier. OpenAI shipped ChatGPT for Excel/Sheets sidebar add-in GA (May 8) with manifest XML deployment option for regulated enterprise environments blocked from app stores. Google's Workspace Intelligence and Fill with Gemini (April 22) continue expanding automation across Sheets, enabling conversational dashboard creation and data entry at 9x manual speed. Microsoft's "Edit with Copilot" agentic feature (GA March 2026) enables multi-step Excel edits across Python, OpenAI, and Anthropic Claude models. Yet independent testing reveals performance gaps: Copilot in Excel achieves 70% formula generation success rate and 12-second latency on 8,000-row datasets but requires mandatory verification. Security and governance have become disqualifying: CSA survey of 418 security professionals found 82% of organizations discovered ungoverned shadow automation agents, 65% experienced security incidents, 61% reported data exposure from AI automation. Ramp Labs' Sheets AI suffered a critical vulnerability (May 2026) where prompt injection via hidden spreadsheet text allowed agents to exfiltrate financial data through formulas without user consent.

Finance sector deployment metrics show real ROI but masked by measurement gaps. AR automation demonstrates concrete adoption (40% payment acceleration, 90% error reduction, 91% success rate among mid-market firms). Mayo Clinic's RPA deployment (2.4M transactions automated, 84,000 staff hours saved annually) and City of Los Angeles' licensing automation (45 days to 6 days, 94% backlog reduction) provide case-study evidence of organizational payback. Yet Deloitte's 2026 Finance Trends survey (1,300+ leaders) reveals 63% deployed financial automation but only 21% report clear ROI—a measurement and benefit-realization gap where automation costs are visible but benefits are diffuse (labour freed to higher-value work) and difficult to track. The strongest third-party signal remains: GPT for Work leads ecosystem with 7M+ installations and 4.9★ rating. Outside finance, adoption continues to stall: only 3% of enterprises achieve meaningful AI transformation; 56% of CEOs report no AI ROI. The central obstacle: ungoverned shadow agents, formula accuracy failures under conditional formatting (83%), and data exposure risks now supersede licensing friction as the blocker to mainstream trust.

TIER HISTORY

ResearchJun-2023 → Jun-2023
Bleeding EdgeJun-2023 → present

EVIDENCE (89)

— ChatGPT Excel/Sheets sidebar add-in GA across all tiers with manifest XML deployment for enterprise environments bypassing app-store restrictions; addresses adoption friction for regulated enterprises.

— Ramp Labs Sheets AI vulnerability: prompt injection via hidden text allowed agents to exfiltrate financial data through formulas without consent. Demonstrates critical operational risk in formula-based automation.

— AR automation deployment metrics: 40% payment acceleration, 90% error reduction in reporting, 91% success rate among mid-sized businesses, 71% CFO prioritization. Finance-specific adoption and outcome data.

— Deloitte Finance Trends 2026 survey (1,300+ leaders): 63% deployed financial automation but only 21% report clear ROI; widespread deployment masked by measurement barriers and diffuse benefit tracking.

— CSA survey (418 security professionals): 82% discovered ungoverned shadow agents; 65% experienced security incidents; 61% reported data exposure. Spreadsheet automation agents lack foundational visibility and lifecycle control.

— Named deployments (Mayo Clinic: 84,000 staff hours saved annually, 18:1 ROI; City of Los Angeles: 45 to 6 days processing, 94% backlog eliminated) showing measured transition from spreadsheets to automation workflows.

— Independent testing of Excel Copilot on 8,000-row datasets: data analysis queries return results in 12 seconds; formula generation succeeds 7/10 times. Documents both capability and limitations (large datasets slow performance; verification mandatory).

— Major Google feature release adding end-to-end spreadsheet creation, side-by-side editing, and workspace intelligence for complex optimization problems.

HISTORY

  • 2023-H1: M365 Copilot enters early access with Excel integration announced; initial user feedback reveals limitations in complex formula generation.
  • 2023-H2: Copilot reaches GA in October with formula suggestions and Python integration. Peer-reviewed research documents accuracy breakdown on complex problems. Practical deployments of ChatGPT+Sheets for data analysis appear. Feature availability gaps and access friction limit real-world rollout.
  • 2024-Q1: Google Sheets ecosystem solidifies as dominant platform with multiple AI integration approaches (native, third-party add-ons like SheetGen, app scripts). Third-party tool ecosystem expands (GptExcel, others). Copilot remains unavailable in desktop Excel despite GA claims; licensing/access issues persist. Research benchmarks confirm formula generation accuracy challenges via NL2Formula dataset.
  • 2024-Q2: Adoption metrics emerge: automated reporting platforms show 60%+ organizational adoption and 80% time savings. Real-world case studies of scale deployments (1,700+ response surveys with ChatGPT analysis). Institutional adoption programs launched (M365 Copilot training bootcamps). Desktop Excel access gaps persist despite training programs.
  • 2024-Q3: No significant new evidence of capability expansion or adoption barrier shifts captured during this window.
  • 2024-Q4: Google launches Gemini AI integration in Google Sheets and new =AI() function via Workspace Labs. Microsoft ships Copilot Lite in Microsoft 365 Family plans, expanding distribution. User feedback and peer-reviewed research document persistent reliability gaps: Copilot in Excel fails on common tasks (find-replace, pivot table analysis) despite GA claims. Formal trustworthiness framework published identifying hallucination risks in formula generation.
  • 2025-Q1: Google ships Gemini GA for chart generation and Python-driven insights in Sheets (January). Microsoft expands Copilot in Excel with Python-driven advanced analytics for forecasting and risk analysis (March). Meanwhile, SPREADSHEETBENCH benchmark reveals 75%+ of models score below 24% accuracy on real-world Excel forum queries. Alteryx analyst survey confirms adoption paradox: 70% say AI improves productivity, yet 76% still rely on spreadsheets and 45% spend 6+ hours weekly on data prep. Emerging third-party solutions (GRID) begin bridging AI-to-spreadsheet logic gaps. Capability expansion continues, but accuracy and logic interpretation barriers remain blocking broader tier advancement.
  • 2025-Q2: Ecosystem expansion: Sourcetable launches AI-powered spreadsheet platform with $4.3M seed funding (April), signaling continued venture interest. Production deployment issues emerge: NHS experiences Copilot outage blocking Excel file analysis in April (resolved November). Access friction persists: Copilot unavailable for Family/Personal tiers, causing user frustration documented across support forums. Vendor acknowledgment: Coherent publishes analysis arguing AI cannot reliably replace Excel for complex models, must remain complementary. Market adoption stalled: analyst productivity claims hold at 70%, but data prep time-sinks (6+ hours weekly, 45% of analysts) remain unaddressed. Core barriers unchanged: formula accuracy, access complexity, organizational rollout friction, trustworthiness concerns.
  • 2025-Q3: Vendor use-case contraction becomes visible: Microsoft ships =COPILOT formula but explicitly warns it unsuitable for accuracy-dependent work (financial, legal, calculations). Google ships incremental Gemini features for Sheets (table auto-formatting, =AI() text function). Paradigm AI and other third-party entrants launch with specialized agent ecosystems (5,000+ agents) as alternative to general-purpose tools. Landmark production deployment: UK government trial of M365 Copilot (1,000 licenses) finds no productivity gains and actual slowdown on complex analysis. Analyst adoption metrics frozen: 70% report productivity gains, 76% still rely on spreadsheets, 45% still spend 6+ hours on data prep. Market bifurcating into specialized text-focused and text-excluded use cases. Analyst skepticism deepens as vendor warnings narrow the applicable use case.
  • 2025-Q4: Google expands Gemini for multi-table analysis (October); Microsoft deprecates Copilot application skills in Excel (removal Feb 2026). Third-party ecosystem matures with 10+ distinct platforms (Julius, Equals, Arcwise, Rows, SheetGod, GPTExcel, SheetAI, Coefficient, Quadratic, others). Critical case studies emerge: companies with high-volume spreadsheet work (Lula Commerce, REVOLVE) abandon spreadsheets for dedicated BI platforms rather than adopt AI spreadsheet tools. Quadratic critiques Excel AI architecture as unsuitable for production data work. Feature expansion continues to mask use-case contraction and user exodus to non-spreadsheet platforms.
  • 2026-Jan: Adoption bifurcation crystallizes: financial services teams deploy spreadsheet automation at scale (accounting sector 52% adoption, 250% ROI, 20-30% capacity gains) while mainstream adoption stalls (56% of CEOs report no AI ROI). Microsoft scales back Copilot integration due to user trust concerns and privacy friction, signaling vendor pivot from aggressive embedding to tactical deployment. Third-party ecosystem remains active but no major breakthroughs. Core barrier: structured domains see strong unit ROI while long-tail knowledge workers face trust, cost, and governance obstacles preventing mainstream scaling.
  • 2026-Feb: Vendor feature expansion continues: Microsoft releases Agent Mode availability in EU and local file querying with Copilot Chat; Google announces admin usage reports for Gemini and forecasting in Connected Sheets via BigQuery ML. However, structural adoption barriers intensify: Microsoft 365 Copilot security bug (CW1226324) bypasses Data Loss Prevention policies, exposing confidential data; technical analysis shows 83% of AI-generated formulas fail under conditional formatting; organizational surveys reveal only 3% of enterprises highly transformed with AI while 72% remain early-stage. Accounting case studies document strong sector adoption (60% of firms, 25-35% time savings, 90-day ROI), yet broader market stalled by compliance concerns, formula fragility, and skills readiness gaps (61% use AI daily but only one-third prepared to adapt).
  • 2026-Mar: Adoption bifurcation sharpens: Microsoft Copilot seats reach 15M with 160% YoY growth and 3x increase in large deployments (35k+ seats); 60% Fortune 500 now deployed with 20-40% measured productivity on Excel data analysis. Google launches Fill with Gemini for Sheets with real-time web data integration and pattern summarization. Yet critical barriers persist: Excel data analysis achieves only 20% adoption despite wide distribution; complex workbooks score worse than random guessing (82% best-case vs >50% human baseline); governance gaps cause 60% of AI projects to fail; and measured ROI remains elusive despite high engagement. Finance sector remains strongest signal (52% adoption, 250% ROI). Core tension unresolved: feature acceleration in vendors masks fundamental accuracy, governance, and trust gaps preventing mainstream tier advancement.
  • 2026-Apr: Trust fracture and market bifurcation deepen. Microsoft's own terms of service contradict marketing claims: Copilot labeled "entertainment only" in ToS while marketing emphasizes productivity gains, revealing 3.3% real market penetration. Microsoft restricts free Copilot Chat access in Excel effective April 15, requiring $30/month per user licensing, signaling major pricing barrier and adoption friction. Meanwhile, leading third-party tool GPT for Work reaches 7M+ installations (ranked #1 in Kinross 2026 report, 4.9★ rating) and Google Workspace reports 128 customer deployments with named-org metrics (Geotab 89% adoption, Docusign 80% positive, Pinnacol 96% time savings). Microsoft ships Work IQ context-aware Copilot, Claude Opus 4.6 model support, and Copilot Notebooks for Excel generation. Yet Gartner forecast warns >40% of agentic AI projects will be discontinued by 2027 due to unclear ROI, uncontrolled costs, and insufficient data. Practice remains at bleeding-edge: strong specialized adoption in accounting, but mainstream tier advancement blocked by trust gaps between vendor marketing and contractual disclaimers, persistent formula accuracy failures under conditional formatting (83%), and licensing/pricing barriers preventing organizational scale.
  • 2026-May: Governance crisis crystallizes as primary adoption barrier, superseding feature maturity concerns. OpenAI ships ChatGPT for Excel/Sheets sidebar GA (May 8) with enterprise deployment options, removing app-store friction. CSA survey (418 security professionals) reveals 82% of organizations discovered ungoverned shadow automation agents created without IT/security/governance knowledge; 65% experienced security incidents; 61% reported data exposure from AI agents. Ramp Labs Sheets AI vulnerability (detected May 7, patched March 16) demonstrated prompt injection exploits allowing agents to exfiltrate financial data via formula injection. Independent testing (Neuriflux, May 2026) documents Copilot in Excel achieving 7/10 formula generation success on first attempt with 12-second latency on 8K-row datasets. Finance sector shows bifurcated signal: AR automation metrics strong (40% payment acceleration, 90% error reduction, 91% mid-market success); but Deloitte survey of 1,300+ finance leaders shows 63% deployed financial automation yet only 21% report clear ROI—measurement gap masks benefit realization. Named case studies demonstrate payback: Mayo Clinic RPA deployment yielded 84,000 annual staff hours (18:1 ROI); City of Los Angeles licensing automation reduced processing from 45 to 6 days. Third-party ecosystem remains dominant (GPT for Work 7M+ installations). Core tension: deep governance gaps (shadow agents, data exposure, lifecycle control, permission drift) now block mainstream adoption more than feature maturity or pricing. Automation is outpacing governance capability. Practice remains stalled at bleeding-edge with strong accounting/finance niches but unresolved trust/control gaps preventing broader organizational scaling.

TOOLS