New AI study could lead media to 'golden' middle ground

Jul 26, 2023 at 05:57 pm by admin

A new book explains how AI may redefine application of Michael Porter’s classic rules on cost, differentiation and segmentation.

Strategising AI in Business and Education, by Aleksandra Przegalinska and Dariusz Jemielniak, is newly published by Cambridge University Press.

In an INMA blog, researcher-in-residence Greg Piechota says the MIT and Harvard fellows believe AI will redefine how companies compete, helping companies reduce costs or charge more – or both – thanks to scaled personalisation.

He quotes Harvard scholar Porter’s strategy for companies in a competitive market to thrive by lowering costs (and prices), differentiating to command a premium price, or focussing on a narrow segment in which it can charge more.

Piechota says empirical studies confirm both low cost and differentiation positioning drives performance, but differentiation leads to more sustained performance over time.

Przegalinska and Jemielniak study the intersection of management and the internet for Poland’s Kozminski university, Massachusetts Institute of Technology and Harvard university.

They say cost leadership can be transformed through automation of tasks, optimisation of resources and increase in effectiveness, while differentiation “starts to rely on personalised, or even hyper-personalised, services and products through machine learning-enabled customer segmentation and targeted marketing”.

However, focus may become the dominant strategy that organises both cost leadership and differentiation approaches. The use of AI allows for “very refined analytics of people’s purchasing decisions and shopping preferences to the degree where new products and services become hyper-personalised,” they say. “Such products can lean toward premium, but they can also be very affordable.”

Piechota says Przegalinska and Jemielniak’s hypothesis challenges our understanding of competitive strategy trade-offs. Porter’s belief that successfully pursuing more than one approach as its primary target was rarely possible, “mirrors concerns of news executives whether a company can successfully pursue both advertising and reader revenue models in digital or optimise for both volume of readers and their value at the same time”.

Przegalinska and Jemielniak say companies that pioneer AI applications are rapidly transforming “not only their operations but the whole sectors. For example, healthcare increasingly relies on AI to design and customise drugs and therapies”.

Piechota cites new media pioneers such as India’s Times Internet and Norway’s Schibsted, which view data and tech platforms as the backbone of their business. Collecting data, segmenting users, and targeting content, offers and ads based on predictions support both advertising and reader revenues.

“These are the cornerstones of news media transformation from product- to customer-centric.”

While Porter warned that firms “stuck in the middle” between generic strategies” were “almost guaranteed low profitability”, Przegalinska and Jemielniak expect that middle ground to be the new winner, he says, as AI allows companies to serve multiple market segments at once and at scale.

The authors recommend using data on audience behaviour and transactions to identify the most valuable customers; creating a differentiated experience by applying predictive and generative AI to customise the product in ways that cannot be easily replicated by competitors; and improving effectiveness of your marketing and sales as different types of AI can tailor your campaigns to the target segments narrowly, down to individuals.

Reducing costs by automating tasks with AI may improve speed and accuracy of decision-making, as well as freeing up human workers’ time for creativity and innovation.


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