Research purpose
MTF Institute studies a narrow but consequential question: how should managers redesign decisions, work systems and controls when technology changes what an organization can observe or automate? The 2026-2027 agenda avoids prediction theatre. It separates public evidence, management inference and testable research questions.
2026-2027 technology portfolio
| Research domain | Management question | Current research page |
|---|---|---|
| Generative AI and artificial intelligence | How can organizations evaluate value and error under accountable human oversight? | Enterprise AI and data systems |
| Machine learning, data science and big data | Which data, evaluation and operating practices make models useful after a pilot? | Enterprise AI and data systems |
| Fintech, blockchain, Web3 and cryptocurrency | Where does tokenisation reduce friction, and where does it relocate risk? | Tokenised finance and blockchain |
| IoT, e-commerce and digital transformation | How do connected data rights and digital channels change operations and measurement? | Connected operations and digital commerce |
| Metaverse, spatial computing and digital twins | Which immersive use cases improve measurable work, simulation or learning outcomes? | Spatial computing and virtual worlds |
Registered research activity
MTF Institute's Portuguese company activity includes “Consultoria científica e investigação, desenvolvimento das ciências físicas e naturais.” The registered activity code is 72190-R3 — Outras atividades de investigação científica e desenvolvimento (I&D) em ciências físicas e naturais: other research and experimental development in physical and natural sciences.
This statement identifies the registered activity under which the company may conduct research and development. It does not turn an editorial review into academic peer review, confer university status, or imply government endorsement of a publication.
Shared methodology
The horizon scan uses public primary sources published by standards bodies, regulators, intergovernmental organizations and research institutions. Each evidence item is recorded with its domain, source, date, signal, proposed management question and limitation. The analysis then applies four stages:
- Evidence classification: distinguish a law, standard, observed dataset, institutional project and forecast.
- Decision translation: state which management decision the evidence could affect.
- Research formulation: express a question that can be investigated rather than a predetermined conclusion.
- Boundary review: identify missing data, sector limits, jurisdiction and possible alternative explanations.
Download the open CSV evidence matrix and the methodology report in PDF.
Five applied practice hubs
- Commercial Leadership and CCO
- Chief of Staff and Executive Operations
- Administrative Professional and CAP
- General Management
- AI Transformation and Platform Strategy
Research integrity
These publications are structured research agendas and evidence reviews. They do not report experiments that have not been performed. Sources are linked, limitations are visible and updates receive a new review date. Readers are invited to reproduce, challenge or extend the evidence matrix with attribution to the canonical MTF Institute page.