Methodology | Meridian Research Institute

Purpose of the Research

The Institute investigates how mid-market organizations are adopting AI tools within operational workflows. Existing data on this phenomenon is insufficient: vendor-sponsored research carries commercial bias, executive surveys capture aspiration rather than implementation, and case studies select for visible success while ignoring structural patterns.

Meridian Research Institute exists to reduce this epistemic uncertainty by collecting primary field data from operational environments, applying rigorous triangulation to distinguish reported strategy from observed practice, and publishing aggregate findings without vendor influence or consulting incentive.

Research Design Overview

All Institute research applies a Convergent Parallel Mixed-Methods design. This is an established research framework in which quantitative and qualitative data are collected independently, analyzed separately, and integrated only after internal validation.

Plain-language summary: What leadership reports is verified against what operational staff actually do. The two data streams are kept separate during collection and analysis. They are compared only after each has been evaluated on its own terms. Agreement strengthens findings; disagreement is documented as a finding in itself.

This structure is designed to surface discrepancies between stated practice and observed behavior—discrepancies that single-source research methods cannot detect.

Data Collection Protocols

The Institute collects two independent data streams concurrently:

Anchor Data

Structured interviews with organizational leaders capture strategic intent, adoption rationale, governance decisions, and leadership perception of AI integration status.

Interviews follow a standardized protocol to ensure comparability. Questions are non-leading; responses are recorded for systematic analysis.

Satellite Data

Anonymous surveys distributed to operational staff capture actual tool usage, workflow integration, documentation encounters, and perceived organizational support.

Staff responses are protected under the Vault Protocol. Individual responses are never attributed or shared with leadership.

Participant Selection

Organizations are selected based on relevance to the research domain, not commercial opportunity. Selection criteria include organizational type, employee count range, operational maturity, and AI adoption status. The Institute does not accept participation based on payment alone; research fit is the governing criterion.

Data Sources

Beyond interviews and surveys, the Institute may examine supporting artifacts where available: process documentation, tool inventories, usage policies, and governance materials. No single data source is treated as authoritative in isolation.

Triangulation and Verification

Findings are considered valid only when supported by convergent evidence from independent data streams.

Convergence Rule: A finding is recorded when anchor data (leadership) and satellite data (staff) point to the same pattern. Convergence increases confidence; it does not guarantee certainty.

Divergence Rule: When anchor and satellite data contradict, the divergence itself is documented as a structural finding. The Institute does not resolve contradictions by privileging one source over another.

Null Finding Rule: Where data is inconclusive, the result is reported as unresolved. The Institute does not force conclusions where evidence is insufficient.

This approach prioritizes accuracy over narrative clarity. Research outputs may include findings that are ambiguous or contradictory because operational reality is often ambiguous and contradictory.

Participant Protection

The Institute applies institutional-grade protection standards to all participant data.

Anonymization

Organization names and identifying details are stripped at data ingestion. No individual organization is identifiable in published findings. Staff members are never identified by name, role specificity, or any combination of attributes that would permit identification.

Aggregation Threshold

No finding is published unless supported by data from at least three organizations. This n≥3 rule prevents reverse attribution even when organization characteristics might otherwise narrow the field.

Staff Data Separation

Individual staff responses are never shared with organizational leadership. Staff data is aggregated before any analysis that could be shared externally. This protection exists to ensure candid reporting without career risk to respondents.

Data Vaulting

Raw data is secured under documented access controls. The Vault Protocol governs data storage, retention limits, and access permissions.

Review the Vault Protocol · Review Ethics & Data Protection

Research Independence

Meridian Research Institute operates independently of vendors, platforms, and consulting interests. The Institute does not accept funding that carries editorial influence. Participation in a study does not confer influence over findings or conclusions.

The Institute retains full editorial and analytical control over all published outputs. There is no work-for-hire arrangement; participants contribute data to a research program, not to a custom engagement.

The Institute does not provide consulting services, implementation support, or optimization recommendations. Research documents patterns; it does not prescribe solutions.

Epistemic Boundaries

The Institute is explicit about what its research does not claim:

No predictive certainty: Findings describe observed patterns within the studied population. They do not predict future outcomes or guarantee applicability to organizations outside the sample.
No universal applicability: Results are bounded by the research scope, time period, and participant characteristics. Extrapolation beyond these boundaries is the reader's responsibility, not a claim of the research.
No causal attribution beyond evidence: The Institute documents correlations and patterns. Causal claims require evidence that observational research cannot provide.
No prescriptive authority: Research outputs inform decision-making; they do not dictate it. The Institute does not advise what organizations should do, only what the data shows they are doing.

These boundaries are not limitations to be overcome but principles that distinguish rigorous research from advocacy or consulting.

Research Outputs

Institute research produces the following output types:

Aggregate benchmarks: Statistical summaries showing distribution of practices across the studied population
Pattern taxonomies: Classification systems for observed behaviors, structures, and approaches
Alignment indicators: Measures of convergence or divergence between strategic intent and operational execution
Failure mode documentation: Catalogued patterns of adoption obstacles, integration breakdowns, and governance gaps
Longitudinal comparisons: Where data permits, tracking of patterns across time periods

The Institute documents conditions and dynamics. It does not produce implementation roadmaps, vendor recommendations, or optimization playbooks.

Research design and analysis are conducted by the Principal Researcher at Meridian Research Institute.