State of AI services 2026.

Source and scope of this report: Based on Trustgent's directory of 101 AI-implementation providers, as of June 2026. This is a snapshot of the listed-provider landscape, not yet outcome-verified data. All 101 providers in this reading are at verification level L0 (Listed from public record). Verified-outcome analysis grows as the L4 corpus is populated and outcome attestations are gathered. No figure below is estimated, extrapolated, or drawn from a survey; every number is computed directly from the directory.

What this report does (and does not) claim

This is a directory-composition landscape. It tells you what the supply side looks like from public record: where providers are headquartered, what capability areas they claim, what firm sizes are represented, which industries they serve, and how long they have been operating.

It does not tell you who delivers well. That requires L3-L5 verification data (customer ratings, AI-analyzed projects, and outcome-verified closes) which are actively being gathered but do not yet exist at scale. A directory that quoted delivery rates or quality rankings from L0 data would be fabricating them. We will publish outcome-layer findings in future revisions as evidence accrues.

Capability mix, what the index claims to build

Computed from the capability tags on 101 provider profiles. Providers self-select into capability areas; inclusion is a claim, not a verified outcome.

• Generative AI & RAG: 88 of 101 providers (87%). The dominant stated capability across the index.
• MLOps & Evaluation: 68 of 101 (67%). More than two-thirds of providers list the tooling and evaluation discipline that production AI requires.
• AI Agents & Automation: 65 of 101 (64%). Workflow agents are now a majority-stated capability, up from a niche in prior years.
• Data Engineering for AI: 60 of 101 (59%). More than half list the pipeline and data foundation work that underpins any AI build.
• Computer Vision: 32 of 101 (32%). Remains a meaningful but minority capability, reflects both specialist demand and greater build complexity.
• AI Governance & Compliance: 22 of 101 (22%). One in five providers lists compliance and governance work, a number likely to grow under the EU AI Act.
• Document Understanding: 14 of 101 (14%). Relatively specialised; concentrated in providers serving legal, financial, and healthcare sectors.
• Voice & Conversational AI: 13 of 101 (13%). The smallest capability cluster, still a specialist area, not a commodity.

The average provider in the index claims 3.6 capability areas. Nineteen providers list five or more, suggesting full-stack positioning; 46 list three or fewer, suggesting specialisation.

Geographic distribution, where providers are headquartered

Headquarter country is drawn from public record. It reflects the firm's legal or primary office location, not where delivery teams are based (which is frequently different, and unverifiable at L0).

The 101 providers span 32 countries. The distribution is concentrated but genuinely global:

• United States: 31 providers (31%)
• India: 11 providers (11%)
• United Kingdom: 7 providers (7%)
• Poland, Germany, Canada: 4 providers each (4% each)
• Spain, Brazil, Belgium: 3 providers each (3% each)
• Australia, Netherlands, France, Switzerland, Japan, Indonesia, Saudi Arabia, Israel, Ukraine: 2 providers each (2% each)
• Remaining 15 countries: 1 provider each

The US and India together account for 42 percent of the supply. European providers (counting UK, Poland, Germany, Spain, Belgium, Netherlands, France, Switzerland, Finland, Portugal, Austria, Czech Republic, Denmark, Sweden, Estonia) account for 34 providers (34%). The remaining 24% are in Asia-Pacific, the Middle East, Latin America, and Africa.

This is a more distributed supply than the market narrative (which focuses heavily on US-headquartered firms) would suggest.

Firm-size profile

Team size is not consistently disclosed publicly; 50 of 101 providers (50%) have no verifiable team-size figure in our sources. The figures below cover the 51 providers for whom a size band could be confirmed.

• 11-50 employees: 9 providers, specialist boutiques
• 51-200 employees: 21 providers, the largest single band among those reporting
• 201-500 employees: 4 providers
• 501-1,000 employees: 8 providers
• 1,001-5,000 employees: 7 providers
• 5,001-10,000 employees: 2 providers, large-scale AI services divisions

Among those reporting, the 51-200 band dominates. This is consistent with a supply side that is structurally fragmented, a large number of mid-size specialist firms rather than a handful of giants. The 50% non-disclosure rate makes firm-size inference across the full directory unreliable; we report it only where we have it.

Industry focus

Industries are drawn from publicly stated specialisations and sector-specific case study pages. A provider listed under an industry has publicly associated itself with that sector; it does not mean a verified delivery in that sector.

• Financial services: 64 of 101 providers (63%), the most commonly stated sector
• Healthcare: 46 of 101 (46%)
• Manufacturing: 33 of 101 (33%)
• Logistics: 13 of 101 (13%)
• Legal and SaaS: 2 providers each, smaller stated clusters

Financial services appears in nearly two-thirds of provider profiles. Healthcare is second by a meaningful margin. Both reflect sectors with large, structured-data assets and strong build budgets, conditions that have historically driven early AI adoption.

Founding-year cohorts

Founding year is publicly verifiable for 76 of 101 providers (25 not in public record).

• Founded before 2018: 59 providers (78% of those with a known year), these are established analytics and software firms that have expanded into AI implementation as the market has grown.
• Founded 2018 or later: 17 providers (22%), born in the generative AI or modern ML era, often with an AI-first positioning from inception.

The skew toward established firms reflects the composition of the current index. It does not necessarily reflect the broader market, which includes many newer entrants not yet in the directory.

What happens next

This report will be updated as the index grows and as verification data accumulates. The next meaningful upgrade is the outcome layer: when L3-L5 records exist at scale, it becomes possible to compare what providers claim against what they can demonstrate. Until then, this composition snapshot is what the evidence honestly supports.

The methodology for what counts as a verified outcome is published at trustgent.com/how-we-verify. The L4 analysis methodology is at trustgent.com/how-we-analyze.