RE-ENGINEERING MARKETING PEDAGOGY IN INDIA: AN INTEGRATIVE FRAMEWORK FOR GENERATIVE AI AND DATA GOVERNANCE

Najassim Pasha; Dr. Harshita Kaushik; Sajita S Kori

doi:10.5281/zenodo.21429580

Abstract

India's marketing classrooms are caught between two tectonic shifts happening at the same time — and most of
them don't even know it. On one side, generative AI has quietly upended how marketing actually gets done:
campaigns that once took weeks are assembled in hours, customer-segment models that needed data scientists
now run on free-tier APIs, and content that once required a creative team is generated with a prompt. On the other
side, the Digital Personal Data Protection Act of 2023 — India's most consequential data law since independence
— means that virtually every AI-powered marketing activity now carries legal weight. Yet when we
systematically examined 52 published syllabi from MBA and BBA marketing programmes spanning the country's
institutional range, we found a picture that is, frankly, sobering.
This paper reports the results of that analysis. Using a six-dimensional content-coding scheme — covering
AI/GenAI coverage (D1), analytics depth (D2), DPDP compliance literacy (D3), India-specific context (D4),
practical tool exposure (D5), and curricular integration versus siloing (D6) — we applied one-way ANOVA and
Pearson correlation tests to ask whether meaningful differences exist across three institutional tiers: IIM/premier
institutions, private and online universities, and state/central affiliating universities. They do. The differences
aren't subtle; they're structural and, in most cases, statistically enormous.
Ninety-four per cent of state/central university syllabi contain no substantive AI or GenAI content whatsoever.
Data governance coverage — including any mention of the DPDP Act — is entirely absent from every private
and every state/central syllabus in the sample, appearing only at five of the six premier institutions we examined.
The curriculum integration dimension (D6) produces a Pearson r of 0.838, which is to say: curricular coherence
around AI is almost perfectly predicted by institutional prestige. These findings point to an equity problem, not
merely a quality gap, and their stakes have grown considerably since Section 8 of the DPDP Act came into force
for data fiduciaries.
Drawing on constructive alignment theory (Biggs, 1996), competency-based education frameworks, and the
National Education Policy 2020, we propose an Integrative AI-Governance Curriculum Model — seven reengineered courses with explicit DPDP mapping, a minimal-infrastructure pathway for resource-constrained
institutions, and competency-demonstration assessments that replace knowledge-recall examinations. The
implications for AICTE's mandatory model curriculum, state board revision cycles, and faculty development
priorities are discussed.

Keywords

Generative AI in marketing education; DPDP Act 2023; curriculum innovation; Indian management education; NEP 2020; marketing pedagogy; institutional equity

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