Agent-payable readiness is not evenly distributed. Some industries have rebuilt checkout for machines while others still assume every buyer is human. This report scores agent-payable readiness across major industries in 2026 and shows where the gaps are widest. We score each sector from 0 to 100 on three pillars: discoverability by agents, structured data quality, and a completable payment path. The composite ranges from 71 for consumer electronics down to 28 for regulated categories like pharmacy. The spread predicts which industries will capture the agentic GMV wave and which will cede it.
Readiness Scores by Industry
The composite score weights discoverability, data quality, and payment path equally. Higher is more ready.
| Industry | Composite score | Discoverability | Payment path |
|---|---|---|---|
| Consumer electronics | 71 | 78 | 69 |
| Apparel and accessories | 64 | 72 | 61 |
| Home and garden | 57 | 63 | 54 |
| Beauty and personal care | 53 | 61 | 48 |
| Grocery and CPG | 46 | 52 | 43 |
| Pharmacy and regulated | 28 | 34 | 21 |
Biggest Readiness Gaps by Pillar
Most industries are stronger on discoverability than on the completable payment path, which is the harder pillar to fix.
| Industry | Data quality | Payment path | Gap (data minus payment) |
|---|---|---|---|
| Consumer electronics | 74 | 69 | 5 |
| Apparel and accessories | 68 | 61 | 7 |
| Home and garden | 59 | 54 | 5 |
| Beauty and personal care | 57 | 48 | 9 |
| Grocery and CPG | 51 | 43 | 8 |
| Pharmacy and regulated | 36 | 21 | 15 |
Key Findings
- Electronics leads, regulated lags. Consumer electronics scores 71 on composite readiness while pharmacy and regulated categories sit at 28, a 43-point spread that will shape who captures agent GMV.
- Payment is the universal weak pillar. Every industry scores lower on the completable payment path than on discoverability, confirming that being found is solved faster than being paid.
- Regulated categories face the widest gap. Pharmacy shows a 15-point gap between data quality and payment path, reflecting verification and compliance steps that block automated checkout.
Methodology
Data is compiled from the Presenc AI monitoring platform plus public sources, with Presenc AI estimates used where authoritative figures are unavailable. Readiness scores are modeled from observed agent sessions, public commerce signals, and vendor-reported benchmarks. Projections use compound growth modeling. Findings are reviewed quarterly. Last update June 2026.
How Presenc AI Helps
Knowing your industry's average is useful, knowing your own score is decisive. Presenc AI benchmarks your brand against the readiness pillars in this study and shows whether discoverability or payment path is your binding constraint. Track which AI agents hit your site and get your agent-payable readiness score to see exactly where you sit relative to your sector.