Milestone 1 Inception Report
Research plan, methodology, source baseline, evidence framework and audience segmentation
| Field | Value |
|---|---|
| Project | CPC-26-0016 - Where the Story Holds: AI Commercial Positioning for Cardano |
| RFP | RFP 09 - AI Commercial Positioning |
| Prepared by | Intelligence Economy Institute (IEI), part of Tokenfrastructure (TKNFRA) |
| Project lead | Zakaryae Boudi |
| Scope | Core scope of 76,000 ADA only |
| Initial report date | 12 August 2026 |
| Revision date | 10 September 2026 |
| Status | Submitted for Milestone 1 review |
1. Purpose and scope
The study will assess whether AI can support a credible commercial positioning for Cardano, for which use cases and audiences, and under which technical, adoption and evidence conditions. It will test the proposed institutional-grade agent integrity, accountability and settlement position as a hypothesis rather than assume it as a conclusion.
This inception baseline covers the 76,000 ADA core scope. It is designed to produce evidence-based findings on demand, technical credibility, current Cardano activity, competitive position, adoption pathways and the resulting strategic recommendation.
Core research questions
- Which AI-related problems and use cases present credible demand from identifiable buyers or adopters?
- Which Cardano technical properties are relevant to those problems, and what evidence supports the associated claims?
- What AI-related activity and capability currently exist within the Cardano ecosystem?
- How does Cardano compare with specialised AI networks, relevant protocols and non-chain alternatives for the shortlisted use cases?
- What positioning and adoption pathway, if any, is supported by the evidence?
Scope boundary
- Included: the research and decision outputs within the 76,000 ADA core scope.
- Excluded optional add-ons: the extended institutional interview base, deep verification of one named deployment and six-month follow-on tracking of recommendation conditions.
- Also excluded: AI product or protocol development, pilot execution, implementation work and technical-roadmap authorship.
Milestone 1 establishes the research design and baselines. Populated evidence, completed interviews, the interview log, competitive teardown, activity-evidence review and preliminary findings are Milestone 2 outputs and are not claimed as completed here.
2. Research plan and methodology
The project uses a mixed-method, evidence-first design. Desk research is combined with structured primary research and verification of material technical, market and ecosystem claims. The method separates documented fact, respondent-reported evidence, analytical inference and vendor judgment.
| Research component | Method | Output use |
|---|---|---|
| Demand and buyer evidence | Test problems, adoption conditions, decision criteria and credible use cases through public evidence and structured interviews. | Buyer/adopter map and demand assessment. |
| Cardano activity evidence | Examine inspectable project, transaction, usage and deployment evidence; separate activity from adoption. | Activity-evidence review. |
| Competitive position | Compare Cardano with specialised AI networks, relevant protocols and non-chain alternatives at use-case level. | Competitive teardown and positioning tests. |
| Technical credibility | Test material claims concerning execution predictability, assurance, identity, auditability, privacy and settlement. | Claim assessments with limitations and confidence. |
| Synthesis | Triangulate primary and secondary evidence and retain negative or contradictory results. | Go, conditional-go, monitor or no-go recommendation. |
Research sequence
- Establish the questions, claim register, source baseline, scoring rubric, ledger structure and stakeholder universe.
- Gather and code secondary evidence; recruit and conduct 15–25 structured interviews across the agreed segments.
- Compare shortlisted use cases and alternatives; test material claims and evidence gaps.
- Synthesize findings, validate the decision logic and produce the final recommendation and outputs.
Source baseline
The named research baseline is provided in the Milestone 1 Source Register. It contains 50 specific public documents, standards, repositories, dashboards, protocols and organisation sources across:
- agent interoperability, commerce and machine-payment protocols;
- independent standards, regulation, risk and security guidance;
- Cardano technical documentation, activity data and ecosystem implementations; and
- specialised AI, compute, agent and non-chain comparisons.
Inclusion in the register means that the source is in scope for consultation; it does not validate every claim made by that source. Provider and ecosystem claims require corroboration, and the register can be extended where a new source is needed to test a material claim.
Primary-research baseline
The proposal calls for 15–25 structured interviews. The Prospective Interview Target Universe identifies 50 organisations as a recruitment and substitution pool, approximately twice the maximum intended sample to manage non-response. These are confirmed research targets, not confirmed participants. Individual identities, contact information, consent and outreach status are maintained in the controlled respondent log and are not published.
Interviews will begin with the respondent's problem, operating environment, current controls and decision criteria. Cardano will not be presented as the assumed answer. Platform characteristics will be tested only after the underlying need and alternatives are understood.
3. Initial claim register: hypotheses to test
The following claims are the initial analytical hypotheses. Their presence is not a finding, endorsement or completed assessment. Each will be populated with supporting and contradicting evidence in Milestone 2.
| ID | Initial hypothesis | Evidence that could weaken or reject it |
|---|---|---|
| H01 | There is identifiable buyer demand for selected AI-agent integrity, accountability or settlement capabilities. | No recurring problem, budget owner, procurement path or production demand is found. |
| H02 | Predictable transaction execution and cost can matter for some agent-mediated workflows. | Buyers do not value the property, or existing databases and payment rails meet the requirement better. |
| H03 | Cardano's formal-methods heritage can contribute to application-level assurance in defined cases. | The relevant properties are not inherited by applications, cannot be specified economically, or are not buyer-relevant. |
| H04 | Identity, delegated authority, auditability and selective privacy are material requirements in some institutional agent workflows. | Existing identity, workflow and payment controls are sufficient, or privacy and compliance constraints make a public ledger unsuitable. |
| H05 | Some current Cardano AI activity represents repeatable commercial adoption rather than experiments or incentive-driven activity. | Activity lacks users, repeat usage, revenue, deployment evidence or independent corroboration. |
| H06 | Cardano may hold a defensible position for selected agent-integrity, accountability or settlement use cases relative to specialised AI networks and non-chain alternatives. | Competitors deliver the same buyer outcome with stronger distribution, liquidity, performance, standards alignment or lower integration cost. |
| H07 | Credible delivery partners and an adoption pathway can be identified for any supported position. | No capable owner, buyer access, integration route, operating model or economic incentive is found. |
| H08 | Some plausible AI use cases should be classified as monitor or no-go because a blockchain is unnecessary or Cardano lacks a buyer-valued advantage. | The evidence instead demonstrates a necessary neutral shared layer and a distinctive, feasible Cardano contribution. |
4. Use-case assessment rubric
Shortlisted use cases will be scored on a repeatable 1–5 scale. Scores of 2 and 4 represent intermediate cases. Every score must include a rationale, evidence references, confidence level and unresolved gap.
| Dimension | Weight | Score 1 anchor | Score 3 anchor | Score 5 anchor |
|---|---|---|---|---|
| Buyer demand | 20% | No evidenced user, problem frequency or budget. | Defined pain and interested actors, but limited production evidence. | Recurring, paid or procurement-ready production demand. |
| Need for a neutral shared layer | 15% | A conventional database, workflow or payment rail is clearly superior. | A shared ledger helps under some trust conditions. | Multi-party control or settlement materially requires a neutral, shared record. |
| Cardano technical fit | 20% | No credible advantage or a material constraint. | Plausible fit with dependencies or untested assumptions. | A decisive, buyer-valued advantage supported by inspectable evidence. |
| Evidence quality | 15% | Conceptual or promotional evidence only. | Live prototype, vendor metrics or partly corroborated evidence. | Independent production and buyer evidence with clear denominators. |
| Buyer access and adoption path | 10% | No reachable decision maker, user or route to adoption. | Reachable experts or builders but an incomplete buying path. | Reachable budget owners/users and a credible procurement or distribution route. |
| Differentiation | 10% | Commodity position or weaker than alternatives. | Some defensible distinction for a defined segment. | Distinct outcome that relevant alternatives cannot readily match. |
| Delivery feasibility | 10% | Major missing infrastructure or unacceptable implementation risk. | Achievable with material partners or dependencies. | Usable production infrastructure and a credible delivery owner exist now. |
The weighted score is calculated as the sum of each 1–5 dimension score multiplied by its weight. It is a comparison aid, not an automatic recommendation. A use case can be marked no-go or monitor regardless of its numerical score if it fails a minimum screen: an evidenced problem and plausible buyer, a justified need for a neutral shared layer, legal and ethical viability, minimum production feasibility, and no unmitigated security or privacy blocker.
5. Evidence framework and credibility ledger
Material claims will be recorded in a credibility ledger so that the basis, strength and limits of each conclusion remain visible. Evidence that cannot be independently inspected will be identified as such and weighted accordingly.
| Ledger field | Purpose |
|---|---|
| Claim or question | Proposition being tested and the research question it informs. |
| Source | Source reference, type, date and location. |
| Evidence status | Documented fact, respondent-reported evidence, analytical inference or vendor judgment. |
| Validation | Whether and how the evidence has been corroborated. |
| Independence | Cardano-connected, independent or mixed evidence. |
| Confidence | High, medium or low based on source quality and consistency. |
| Limitations | Known gaps, contradictions, access constraints or conditions. |
Credibility standards
- Material conclusions will be traceable to identified evidence or clearly labelled judgment.
- Technical capability will be distinguished from demonstrated deployment, recurring use and commercial adoption.
- Provider metrics will retain their denominator, period and provenance; transaction counts will not be treated as users or revenue.
- Contradictory evidence and material limitations will remain visible.
- Confidence will reflect source quality, independence, recency and corroboration.
- Respondent evidence will be attributed, anonymised or treated as confidential according to consent.
AI-use approach
AI tools may support source discovery, organisation, coding and drafting. They will not be treated as authoritative evidence. Material outputs will be reviewed by the project team, cited sources will be checked, and confidential or personal information will not be entered into unapproved tools. Material AI assistance will be disclosed where relevant.
6. Stakeholder and audience segmentation
| Segment | Research contribution | Recruitment focus |
|---|---|---|
| Institutional buyers and adopters | Demand, decision criteria, risk, procurement and evidence thresholds. | Product owners, operational users, payments, risk, compliance, procurement and enterprise AI functions. |
| AI-agent builders and platforms | Use-case requirements, integration conditions and current control patterns. | Agent product, engineering, safety, identity, governance and applied-agent functions. |
| Payments, commerce and delivery infrastructure | Authority, payment, fulfilment, disputes, interoperability and route-to-market. | Protocol, payments, merchant, wallet, fraud, identity and delivery functions. |
| Cardano ecosystem and technical contributors | Current activity, technical evidence, operational limits and ecosystem capability. | Protocol, infrastructure, application, privacy, adoption and operator functions. |
| Independent and non-Cardano comparisons | Competing architectures, neutral controls and counter-evidence. | Specialised AI/compute networks, alternative chains, workflow platforms and independent experts. |
| Standards, identity, security and assurance | Control baselines, interoperability, risk and evidence requirements. | Standards, digital identity, cybersecurity, assurance and formal-methods functions. |
| CPC and Intersect | Commissioner alignment, challenge and milestone review. | Steering and validation input; not treated as buyer evidence. |
The organisation-level recruitment baseline is the Prospective Interview Target Universe. The realised Milestone 2 sample will seek cross-segment balance, keep Cardano-connected evidence from dominating the sample and corroborate material vendor claims with independent evidence.
7. Success criteria and Milestone 1 confirmation
- The research questions can be answered through a proportionate mix of primary and secondary evidence.
- Material findings can be traced through the credibility ledger to supporting evidence and limitations.
- The analysis distinguishes technical capability, demonstrated activity, commercial demand and strategic inference.
- The source register provides a specific, reviewable secondary-evidence baseline.
- The target universe and segmentation provide an actionable recruitment baseline for 15–25 interviews without claiming participation before consent.
- The rubric supports repeatable use-case comparison while preserving no-go conclusions.
- The final recommendation can distinguish go, conditional-go, monitor and no-go outcomes.
This report consolidates the contractual Milestone 1 elements: the inception report, research plan and methodology, source baseline, evidence framework and credibility-ledger structure, stakeholder and audience segmentation, initial claim list and scoring rubric. The methodology may be refined following CPC and Intersect review without expanding the core scope.