AI will alter news media industry’s competition, strategy

By Greg Piechota


Oxford, United Kingdom


AI will redefine how companies compete, claim MIT and Harvard fellows in a new book. AI can help companies to reduce costs, charge more, or both thanks to scaled personalisation.

Strategy explains how a company, faced with competition, creates superior profits. In 1980, Harvard scholar Michael Porter described three main ways a company can achieve it:

  • Operate at a lower cost than rivals so it can offer lower prices to all consumers.
  • Command a premium price through product differentiation.
  • Focus on a narrow segment and differentiate by serving its needs for a premium price or at a lower cost.

Porter’s model applies to the news industry. For example, U.S.-based HuffPost uses blogging to reduce production costs and build an audience for advertisers. The New York Times offers in-depth journalism to stand out and charge consumers for subscriptions. TechCrunch concentrates on content and community for technology startups.

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

AI may significantly redefine Porter’s classic strategies, anticipate Aleksandra Przegalinska and Dariusz Jemielniak in a new book, Strategising AI in Business and Education, published in 2023 with Cambridge University Press.

Strategising AI

Professors Przegalinska and Jemielniak study the intersection of management and the Internet for Poland’s Kozminski University, Massachusetts Institute of Technology, and Harvard University. 

In the book, they analysed the impact of AI on Porter’s model:

  • Cost leadership: “[This approach] can be transformed through automation of tasks, optimisation of resources, and increase in effectiveness.”

  • Differentiation: “Starts to rely on personalised, or even hyper-personalised, services and products through machine learning-enabled customer segmentation and targeted marketing.”

  • Focus: “May become the dominant strategy that organises both cost leadership and differentiation approaches.”

They argue: “[AI techniques] allow for very refined analytics of people’s purchasing decisions and shopping preferences to the degree where new products and services become hyper-personalised. Such products can lean toward premium, but they can also be very affordable.” 

Redefining operations and sectors

Przegalinska and Jemielniak’s hypothesis challenges our understanding of competitive strategy trade-offs.

Porter believed: “Sometimes the firm can successfully pursue more than one approach as its primary target, though that is rarely possible.” This mirrors the 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. 

The devil is in operations — a successful implementation of the strategic position requires different resources, skills, organisation and management. 

  • For example, cost leadership-focused companies aim for the lowest production and distribution costs, which demands efficiency, scale, and tight operational control. 

  • Differentiation-focused companies strive to offer unique, high-quality products or services, requiring innovation, customer centricity, and a culture of creativity.

Companies that pioneer AI applications, observe Przegalinska and Jemielniak, 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. 

In the news media, AI pioneers, such as India’s Times Internet and Norway’s Schibsted, 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.

Porter warned in 1980: “The firm stuck in the middle [between generic strategies] is almost guaranteed low profitability.” 

In 2023, Przegalinska and Jemielniak expect that middle ground to be the new winner, as AI allows companies to serve multiple market segments at once and at scale: “The costs of running unsupervised machine-learning models are dropping.”

New strategy playbook

How can companies apply AI to pursue “focus-oriented cost leadership” or “focus-oriented differentiation”? The academics recommend:

  1. Identify the most valuable customers using data on your audiences’ behaviours and transactions for predictions. 

  2. Create a differentiated experience by applying predictive and generative AI to customise the product in ways that cannot be easily replicated by competitors.

  3. Improve effectiveness of your marketing and sales as different types of AI can tailor your campaigns to the target segments narrowly — down to individuals.

  4. Reduce costs by automating tasks with AI. This may improve speed and accuracy of decision-making, but also free up human workers’ time for creativity and innovation.

Looking for strategic insight on generative AI? Read a summary or watch this INMA Webinar with Professor Thomas Davenport, author of All in on AI

Greg’s Readers First newsletter is a public face of a revenue and media subscriptions initiative by INMA, outlined here. Subscribe here.

About Greg Piechota

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