01Introduction

SECTION 01

1.1 Background

Organisations are embedding machine-learning models, autonomous agents and generative AI into lending, operations, customer service and fraud control. Decisions once made by people are now made, or shaped, by systems that learn from data and adapt on their own.

This shift moves the security perimeter. Beyond protecting networks, data and identities, the enterprise must now protect the integrity of machine decisions and the human judgement that depends on them — the domain this study calls cognitive security.

1.2 Research problem

Existing frameworks — NIST CSF 2.0, ISO/IEC 27001:2022, CMMI-style maturity models — were designed for conventional digital infrastructure. They offer limited guidance on adversarial manipulation, model drift, AI governance and human–AI trust , and no single instrument lets an executive measure, in one comparable score, how secure the enterprise's thinking systems are.

1.3 Significance

Theoretically, the study joins AI governance, cybersecurity strategy and resilience in one maturity construct. Practically, it gives boards and security leaders a measurable baseline and a staged path to improve it.

1.4 Research objectives

O1 · Examine how AI integration has transformed enterprise security requirements.

O2 · Identify emerging AI-driven threats: adversarial ML, automated phishing, deepfakes.

O3 · Evaluate the limits of existing frameworks for autonomous AI systems.

O4 · Design a unified cognitive security maturity framework.

O5 · Develop a practical assessment instrument for executive decision-making.

1.5 Research questions

RQ1 · What characterises AI-driven post-digital enterprises, and how do they change the security landscape?

RQ2 · Which cognitive threats pose the greatest risk to AI-integrated environments?

RQ3 · Where do existing frameworks and standards fall short for autonomous AI systems?

RQ4 · What components does a unified cognitive security maturity model require?

RQ5 · How can organisations assess and improve their cognitive security capability?

1.6 Scope

Medium and large organisations using AI in core operations, across sectors; organisational, governance and control layers — not individual algorithms.