INNOVAREModule 7 · AI in Marketing, Sales & Customer Experience

Case 6: Does the Reading Hold Up?

The required Kumar, Ashraf & Nadeem (2024) reading taught plainly — the theory, the six themes, the ethics finding — then weighed honestly, with the regulation the module omits.

July 2026 · Case 6 of 6
As you read — hold this question

The marketers in this paper rated ethics their #1 concern — so why does almost nothing in the set materials tell you what to actually do about it?

5.28/7
how highly the reading’s surveyed marketers rated ethics — the top theme of all.

The module rests its academic weight on one Opinion Paper. Taught plainly, it maps AI marketing onto dynamic capability theory, three capability groups, and six themes — with ethics rated highest. Weighed honestly, it is a modest survey resting on a descriptive theory — and the most examinable rule in the module (APP 1.7, 10 Dec 2026) appears nowhere in it.

The required reading, taught plainly
The textbook versionQuiz: Required reading

Kumar, Ashraf & Nadeem (2024) — the theory, on one page

The paper ties AI marketing to dynamic capability theory: advantage comes from a firm’s ability to sense change, seize it, and reconfigure around it. It sorts AI capabilities into three groups — analytical, technological, strategic efficiency — and draws out six research themes: customer insights, measuring performance, automated strategies, ethical implications, customer experience, and growth.

The finding to remember: when the authors surveyed marketers, ethics outranked every other theme — scoring highest at 5.28 / 7, above growth and personalisation.
How much can it carry?
The other side

Read the method, and the theory, before you cite the conclusion

Unpacking the #1 theme: ethics is not abstract
“Ethics” here means three concrete things — algorithmic bias, privacy/consent, and transparency. Real cases: US regulators found Facebook’s ad-delivery algorithm discriminated in housing ads (a 2022 DOJ settlement forced Meta to build a “Variance Reduction System”); and Australia’s privacy regulator found Bunnings’ facial recognition breached the Privacy Act across 60+ stores. The compliance lesson in one line: “the technology is permitted” is not the same as “your governance around it was adequate.”
The forward-look, and the local rule that’s coming
The other side

AR/XR, and the disclosure timeline the module omits

The paper points to immersive / AR / XR / metaverse marketing as the next surface (Theme 5) — which is exactly where the set case is silent, so it’s your opening on the 7.5 Q2. And disclosure is becoming law almost everywhere except, for now, Australia:

JurisdictionRuleFrom
ChinaAI-content labelling in forceSep 2025
EU + CaliforniaEU AI Act Art. 50 · SB 942 — label AI contentAug 2026
AustraliaPrivacy Act APP 1.7 — disclose automated decisions10 Dec 2026
AustraliaNo general AI-labelling law yet
Take this away

APP 1.7 (10 Dec 2026) is the most examinable local date in the module, and it appears nowhere in the set materials. Australia is the current outlier — and the commercial case for disclosure already runs ahead of the legal one.

Quick recall — without looking back

Test yourself on this case

Question 1 of 3

What theory does the required reading use, what are its three capability groups and six themes, and which theme ranked highest?

Dynamic capability theory (Teece, 1997). Three capability groups: analytical, technological, strategic efficiency. Six themes: customer insights, measuring performance, automated strategies, ethical implications, customer experience, growth. Ethics ranked highest, at 5.28/7.
Question 2 of 3

What are the methodological limits of the paper, and the better-evidenced alternative theory?

It’s an invited ‘Opinion Paper’ (not full peer-review bar) with n=40 self-selected AI-invested professionals — a modest claim, not proof. Dynamic capabilities is descriptive and hard to falsify; a better-evidenced alternative (not used by the paper) is absorptive capacity (Cohen & Levinthal, 1990).
Question 3 of 3

Give the AI-disclosure regulation timeline, and the most examinable Australian date.

China: AI-content labelling in force Sep 2025. EU (AI Act Art. 50) + California (SB 942): from Aug 2026. Australia: Privacy Act APP 1.7 (disclose automated decisions) from 10 Dec 2026 — the key local date — but no general AI-labelling law yet, making Australia the outlier.

Module 7 Video

Module 7 · Long Form · No Takesies Backsies

Sources

Required reading
Kumar, Ashraf & Nadeem (2024), “AI-powered marketing: what, where, and how?” International Journal of Information Management, Vol. 77 (Opinion Paper).
Theory provenance
Teece, Pisano & Shuen (1997); Arend & Bromiley (2009); Cohen & Levinthal (1990, absorptive capacity).
Ethics & regulation
US DOJ v Meta settlement (2022, Variance Reduction System); OAIC determination on Bunnings facial recognition (2024); EU AI Act Art. 50; California SB 942; Australian Privacy Act reform (APP 1.7).
Innovare Study
Long-form video: No Takesies Backsies. 2026. youtu.be/yV5R4JThoYQ