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.
A daily newsletter distilling the past two weeks of movement in a domain or two — delivered to your inbox while the index updates in the background.
Each dot marks the weighted maturity of practices within a domain — hover for a brief summary, click for more detail
AI that autonomously scores contract risk, generates assessment reports, and recommends accept/reject/negotiate decisions. Includes automated risk scoring and recommendation generation; distinct from risk flagging which highlights issues for human assessment rather than making recommendations.
Autonomous contract assessment -- AI that scores risk, generates reports, and recommends accept/reject/negotiate decisions -- has moved from bleeding-edge experiment to leading-edge production standard in high-volume triage, yet the practice faces a hard tier ceiling beyond routine work. Global adoption has normalized rapidly: 92% of lawyers across 10 countries now use AI daily; 87% of general counsel employ AI; 52% of in-house teams actively use or evaluate contract review AI (quadrupled since 2024). Deployments deliver measurable ROI for high-volume screening -- 40-60% efficiency gains, 75%+ time savings, 300-450% reported ROI. Yet the same evidence base reveals binding constraints. Production systems show 17-34% real-world error rates despite 95%+ benchmark claims. Autonomous scoring tools exhibit documented algorithmic bias (corporate-favorable in negotiation scenarios). Hallucination incidents have spiked: 1,200+ documented cases globally, with $145K in court sanctions in Q1 2026 alone, including career-ending attorney discipline. Contractual data-access barriers and governance maturity gaps prevent 78% of agentic AI pilots from reaching production. The tier-defining tension is structural: the practice excels at high-volume first-pass screening where human review is downstream, but cannot advance to autonomous decision-making on complex or contested agreements without solving accuracy-on-edge-cases, fairness risk, and sanctionable failure modes.
Production deployments at scale demonstrate the economic momentum. Concord's engine processes 10k+ contracts monthly with 94% autonomous risk-spotting accuracy (vs 85% average for experienced lawyers), compressing review from 92 minutes to 26 seconds per contract and achieving 300-450% reported ROI. Inkvex's independent validation study on 327 real-world contracts confirms capability: 94% catch rate of high-severity flags (vs 85% baseline accuracy), 99% catch on auto-renewal clauses, 95% on liability caps, with only 6% false negatives. Orangetheory cut turnaround to 30 minutes per document (80% time savings); Agristo and ECS report 75% time reductions. Vendor ecosystem consolidation is deepening: Icertis serves 250+ Fortune 500 customers with $350M ARR and 30%+ Fortune 100 penetration (post-Dioptra acquisition); LinkSquares reports 1,300+ teams managing 13M contracts with 800k+ hours saved. Global adoption has normalized: Wolters Kluwer's 810-lawyer survey across 10 countries shows 92% use AI daily, 62% report 6-20% time savings, and 61% are confident in AI-driven workflows.
The advancement barriers, however, are hardening rather than softening. Brittney Ball's April 2026 research documents 1,200+ AI hallucination incidents in legal proceedings globally (roughly 10 per day), with $145K in court sanctions in Q1 2026 alone and indefinite attorney suspension for filing 57 defective AI-generated citations. Thomson Reuters analysis identifies the strategic risk: 80% of legal professionals see AI as transformational, yet only 38% expect near-term organizational change, and Gartner projects over 40% of agentic AI projects will be discontinued by 2027. Real-world deployment data shows 17-34% error rates in production despite 95%+ accuracy benchmarks; governance and infrastructure gaps prevent 78% of agentic pilots from reaching production. The bias vulnerability identified in January 2026 law review research persists: autonomous scoring tools systematically favor corporations over individuals in negotiation, creating direct liability exposure. Contractual data-access restrictions (NDAs and engagement letters from 2023-2024) force reliance on generic models rather than fine-tuned deployment. Autonomous decision-making on complex or disputed agreements remains out of scope for all but the most risk-tolerant teams.
— Global survey across 10 countries, 810 lawyers: 92% use AI daily, 62% report 6-20% time savings, 61% confident in AI-driven workflows. Demonstrates leading-edge maturity breadth and normalized adoption.
— Independent research on 327 real contracts (7 types) using California attorney baseline validation. Inkvex achieved 94% catch of high-severity flags, 6% false negatives, 99% on auto-renewal clauses, 95% on liability caps.
— Production deployment metrics: 94% autonomous risk spotting accuracy (vs 85% lawyers), 4 hrs/week savings per lawyer, 31% cost reduction, 300-450% ROI, processing 10k+ contracts monthly.
— Thomson Reuters survey data (53% seeing ROI) with customer outcomes: 75% time savings in contract review; named deployments (Agristo: 2hr to 15min, ECS: 8hr to minutes) demonstrate production autonomous assessment.
— HEC Paris researcher documents widespread AI failures: 1,200+ hallucination incidents, 10+ cases daily by March 2026, $145K Q1 sanctions, Greg Lake suspension for 57 fabricated citations—critical limitation on autonomous assessment without human review.
— Strategic analysis shows awareness-execution gap (80% see AI transformational, 38% expect near-term change). Gartner projection: 40%+ of agentic AI projects discontinued by 2027. Strategic adoption 3.9x more ROI than ad hoc.
— Large-scale Deloitte research (1,100+ respondents, 6 countries) quantifying agentic workflow benefits in AI CLM: 30% higher ROI, deployment benefits across legal and business teams.
— Practitioner framework for contract review/redline AI workflows. Documents control failure modes (clause omission), governance design for autonomous assessment, EU AI Act compliance requirements.