BUSINESS INTELLIGENCE · 6GDT
What Comes After Generative AI?
Inferential Intelligence. Research on the transition from content generation toward inference, discovery and better human decision-making.
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RESEARCH FOCUS · BUSINESS INTELLIGENCE
Business Intelligence Beyond Prediction.
My research examines how Business Intelligence may evolve when AI moves beyond generation and prediction toward connecting evidence, questioning causality, forming hypotheses and supporting discovery.
Central research questionHow should Business Intelligence evolve when AI begins to reason across evidence, relationships and hypotheses?
Future of Business Intelligence
From dashboards and prediction toward reasoning layers that improve understanding, judgment and strategic decision-making.
Explore Business Intelligence →Inferential Intelligence
The ability to move from known evidence toward relationships, hypotheses, causal questions and deeper explanations.
Explore Inferential Intelligence →Sixth Generation of Digital Transformation (6GDT)
A proposed framework for the transition from generative systems toward inferential intelligence, Human–AI co-discovery and knowledge creation.
Explore 6GDT →NEW · GOVERNMENT · AI GOVERNANCE
Technology moves fast. Can government learn faster?
An independent 6GDT interpretation of The Economist’s visual premise on AI politics in Washington—and the institutional learning gap behind it.
Read the bilingual analysis →
SPORT · 6GDT
From prediction to causality: what changes when AI asks “why”?
A practical 6GDT sport framework connecting prediction, causal inference, counterfactual reasoning, human judgment and validation before action.
Explore the sport framework →
NEW · GOVERNMENT & ORGANIZATIONS · 6GDT
When does a government AI pilot become institutional intelligence?
Only when evidence and failure are validated, retained and carried into the next public decision.
Read the evidence-led analysis →
NEW · PROPOSED RESEARCH FRAMEWORK
The Seesaw Effect
Can extreme intelligence asymmetry pass a critical threshold—turning the leaders’ advantage into systemic fragility and rebound?
Explore the three-stage framework →NEW · MANAGEMENT RESEARCH QUESTIONS · No. 02
If the outcome is already decided before the process begins, what does the process actually select?
Part 02 examines the shift from selection to legitimation: when formal procedure, credible participants, and apparent competition may generate acceptance for a pre-shaped outcome.
Read Management Research Question No. 02 →
MANAGEMENT RESEARCH QUESTIONS · No. 01
How does management turn predetermined decisions into seemingly merit-based and accepted outcomes?
A research inquiry into manufactured legitimacy, selection processes, and the transfer of participants’ credibility to a predetermined outcome.
Read Management Research Question No. 01 →
PROPOSED HYPOTHESIS · 6GDT RESEARCH PATH
Inferential Liberation
What if AI’s greatest contribution is not answering for humanity, but releasing thoughts humanity could never fully express?
Read the Inferential Liberation Hypothesis →
Saeid Khorami, PhD
Business Intelligence Researcher · PhD in Information Technology Management
Research focus: 6GDT, Inferential Intelligence, Human–AI collaboration and strategic decision-making.
From Data to Inference. From Inference to Value.Decision Context Dashboard
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—INFERENCE SIGNAL
Inference Layer
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About
Business Intelligence, inference and the next stage of digital transformation.
I am a Business Intelligence researcher with a PhD in Information Technology Management. My current work explores how AI may move from generation toward inference — and what that shift means for organizational intelligence, strategic decisions and digital transformation.
Research profile
My research explores how organizations and societies move beyond digitization and content generation toward inference, judgment, and sustainable value creation. The central research trajectory connects 6GDT, the Age of Inference, Inferential Intelligence, and Neo-Inference Science.
6GDTSixth-generation digital transformation
NISNeo-Inference Science framework
AI & StrategyHuman-centered inferential systems
Sports LeadershipDiscipline, education, and performance
THEORETICAL DEVELOPMENT
Neo-Inference Science as a supporting research program.
NIS is developed as an underlying theoretical program for Human–AI co-discovery, recursive knowledge evolution and the study of inference. It supports the broader 6GDT research agenda rather than replacing it.
The conceptual architecture
Within this program, 6GDT is the primary transformation framework, Inferential Intelligence is the central capability, and Neo-Inference Science is an underlying theoretical development for Human–AI co-discovery.
The Age of Inference6GDTInferential IntelligenceInferential ArtInferential DesignInferential Society
Peer-Reviewed Publications
Two published research papers.
Peer-reviewed work by Saeid Khorami on digital transformation in higher education.
Identification and Validation of Factors Influencing Digital Transformation in Higher Education
Research identifying and validating technological, managerial and human factors shaping digital transformation in higher education.
View journal article →Presenting a Model for Digital Transformation in Higher Education
A meta-synthesis study presenting a structured model for digital transformation across universities and higher-education institutions.
Journal article · DOI 10.61838/dtai.2.3.3 →Contact
Research and professional correspondence
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