{"resourceId":"maryland-business-ai-benchmark-innovation-team-20261001","versions":[{"version":"external-94c0f8dedb598a59dd72e84fb1c6764beefb271336b51e96c13e638f7ea53f79","resource":{"id":"maryland-business-ai-benchmark-innovation-team-20261001","title":"Maryland State Innovation Team (Oct 1): Business AI Benchmark of 276 leaders finds 91% use AI but 58% stay at basic use and productivity gains are mostly slight","organization":"Maryland State Innovation Team / Office of Governor Wes Moore","sector":"State innovation office evidence-building for AI economic and workforce policy","geography":"Maryland statewide","publishedAt":"2026-10-01","publicationDate":"2026-10-01","eventDate":"2026-10-01","sourceName":"Office of Governor Wes Moore (governor.maryland.gov)","sourceLabel":"Governor Moore Convenes Maryland Innovation Summit, Releases New Maryland Business AI Benchmark, press release, Oct 1, 2026 (with Maryland Business AI Benchmark Report, Sept. 2026)","sourceUrl":"https://governor.maryland.gov/news/press-releases/governor-moore-convenes-maryland-innovation-summit-releases-new-maryland-business-ai-benchmark","evidenceClass":"government-evaluation","outcomeClass":"mixed","topics":["knowledge-work","accessibility-workforce","operating-model"],"finding":"At the Oct 1 Maryland Innovation Summit, the State Innovation Team released a Business AI Benchmark. It is a June-July 2026 survey of about 300 senior decision-makers; the report says 276 executive or senior leaders. 91% report using some AI, but 58% are at basic use. 92% of regular users report positive productivity impact, mostly slight (70%) rather than significant (21%). Two-thirds have a dedicated AI budget, 64% plan to have existing staff do more with AI, and only 4% expect headcount cuts. Businesses ask the state for capital, technical assistance, pilots, talent pipelines, training and affordable secure infrastructure. The report notes a likely sample skew toward AI-engaged firms. It finds Public Services and Utilities leaders the least confident in using AI. The release also cites Maryland Community Compass (18,500+ active users, $14M state funding).","sledRelevance":"Relevant to state government as an example of a state innovation office producing its own AI evidence base before designing programs, and as a check on productivity claims: gains are mostly slight. Its subject is businesses, not agency operations, so relevance to agency AI adoption is indirect. Freshness: released Oct 1 (page updated 19:28 EDT), a few hours before the Oct 1 run started. That run did not capture it, it is not archived, and it is the newest state-produced measurement in this window.","evidence":"Opened the Oct 1 press release and the 33-page report PDF on innovation.maryland.gov (PDF created Sep 28, cover 'September 2026'). Confirmed the headline percentages, the 276-respondent base, fieldwork dates, the AI-engaged sample-skew caveat, the comparison caveat against an NBER firm sample, and the low confidence of the Public Services and Utilities segment. Community Compass figures are from the release only.","architectureImplications":"Businesses cite uneven data readiness and infrastructure bottlenecks, such as internet reliability and storage costs. That signals state programs may need shared secure infrastructure, not just training.","governanceImplications":"Shows a governance practice worth copying: measure locally before setting policy. Self-reported, non-random results should not be used as statewide prevalence figures.","securityPrivacyImplications":"Data security concerns rank among the top barriers to business AI adoption. State-provided secure infrastructure was a stated request; no security outcomes are measured.","caveats":"Voluntary survey of AI-engaged organizations; self-reported productivity; categorical revenue estimates; not representative of all Maryland employers. Business-focused, not an evaluation of state agency AI. The press release is promotional in tone.","streamIds":["state-government"],"roles":{"sales":"Use this as a calibration point, not a growth story: Maryland's own survey finds AI use is broad but shallow and productivity gains mostly slight. Discovery should ask whether the prospect state measures its own AI baseline before funding programs, and what evidence its innovation or commerce office has. A bounded measurement-design engagement fits. This evidence cannot support claims of large productivity gains, statewide prevalence or results for agency operations.","engineering":"Fit is survey and data design for state AI evidence programs: instrument design, sampling, segment reporting and repeatable measures over time. For agencies, the same method could baseline internal AI use. Constraints: voluntary, self-reported and skewed toward AI-engaged firms; not comparable to national samples. Proof of value would be a repeatable instrument with documented sampling limits and a second wave showing change, not one-off headline percentages.","delivery":"Delivery work would be a repeatable AI-adoption measurement program: define measures, recruit a broader sample, and publish methods and limits alongside results. The State Innovation Team or equivalent owns it, with commerce and labor departments as users. Acceptance criteria are proposals, such as a second wave with documented response rates. Risks include sample skew, promotional framing of modest results, and policy built on self-reported gains."},"roleDetails":{"sales":{"customerProblem":"State leaders design AI economic and workforce programs without local evidence on how far adoption has gone or what gains are real.","stakeholders":["State innovation office","Department of Commerce","Department of Labor","Governor's policy office","Department of Information Technology"],"discoveryQuestions":["Do you have a local baseline of AI adoption?","How do you validate self-reported productivity gains?","Which sectors or agencies show the least confidence?","Would you repeat a survey to track change?"],"valueHypothesis":"A repeatable measurement program could help states target AI support where adoption is shallow, with explicit limits on what results mean.","potentialEngagement":"Six-week measurement design and pilot wave for a state innovation or commerce office, including published methodology and limitations.","unsupportedClaims":["That AI raises Maryland productivity significantly","Statewide adoption prevalence","Any effect on state agency operations","Return on Community Compass funding"]},"engineering":{"fit":"Survey instrument, sampling and reporting design for state AI evidence-building.","architectureIntegration":"Store survey waves in a governed analytics environment with segment weights and publish dashboards with method notes.","prerequisites":["Partner channels for recruitment","Agreed adoption-level definitions","Privacy review of respondent data"],"constraints":["Voluntary and AI-engaged sample skew","Self-reported outcomes","Not comparable to national studies","Business focus, not agencies"],"security":"Protect respondent business data; aggregate segments to avoid re-identification of small firms.","proofOfValue":["Documented sampling frame and response rate","Second wave showing change on core measures","Segment results with confidence caveats"]},"delivery":{"work":"Stand up a repeatable AI-adoption survey with published methods and limits, and link findings to program design.","dependencies":["Recruitment partners such as chambers","Analyst capacity","Leadership agreement to publish limitations"],"ownership":"State Innovation Team, with commerce and labor departments as program owners.","skillsAdoption":"Analysts need survey methodology skills; program staff need training to interpret self-reported data cautiously.","governanceCheckpoints":["Instrument and privacy review","Methodology publication","Program decisions cite limitations"],"acceptanceCriteria":["Proposed: response rate and sampling frame published","Proposed: second wave within 12 months","Proposed: each headline figure carries a caveat"],"risks":["Sample skew overstates adoption","Promotional framing","Policy built on self-reports","Survey fatigue"]}},"retrievedAt":"2026-10-04T22:34:12-05:00","enrichedAt":"2026-10-04T22:37:03-05:00","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Employers expect workforce evolution over reduction (4% expect cuts) and want training programs, which supports state workforce-development roles in AI.","procurementImplications":"Limited direct procurement relevance; requests for affordable secure digital infrastructure could shape future state-sponsored shared services or grants.","operatingModelImplications":"A central state innovation team runs research, convenings and products (Community Compass), a hub model other states may compare against.","sourceVerification":{"responseId":"curl-mdbench-backfill-20261004","openedUrl":"https://governor.maryland.gov/news/press-releases/governor-moore-convenes-maryland-innovation-summit-releases-new-maryland-business-ai-benchmark","referenceExcerpt":"92% of regular AI users report a positive productivity impact, though most describe it as slight (70%) rather than significant (21%).","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}