AI transforms retail pricing with real-time discounts, says BCG

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Retailers are now using artificial intelligence (AI) to implement real-time pricing strategies, thereby, dynamically adjust discounts based on data analytics, experts said. This is of particular significance as pricing has become more fluid than ever with the rise of e-commerce giants and quick-commerce platforms.

"Retailers have mountains of data compared to other industries," said Kiran Pudi, Partner and Director, APAC Head-Pricing Practice, BCG, told Moneycontrol. "Promotions have always been data-driven, but now they’ve become a lot more dynamic as well," Pudi added.

With AI-driven analytics, businesses can swiftly respond to market demand, competitor pricing, and customer behaviour. Unlike traditional promotional strategies that were planned months in advance, AI enables real-time adjustments. "Decisions that used to be made over months are now happening on the fly," the expert further said.

“Promotions have actually become a lot more sophisticated, a lot more targeted, and they've always been data-driven. Now, they become a lot more dynamic as well," Pudi said.

Price Sensitivity

This level of agility is particularly crucial in India, where price sensitivity among consumers varies widely across regions and demographics.

“Price sensitivity drops depending on the value delivered so thinking that it's a generic statement that Indian customers are or consumers are super price sensitive is a myth. In a high inflationary market or relatively high inflation market regularly thinking and evaluating our pricing strategy… is something which should be an ongoing effort,” Pudi added.

This is particularly relevant in the Indian retail market, where purchasing behaviour differs across urban and rural segments. While some consumers prioritise low prices, others focus on overall value

Understanding these differences helps retailers design targeted promotional strategies that drive sales without unnecessary discounting.

AI Pricing Cycle

Nonetheless, the pricing dynamics of AI models follow a predictable cycle: as algorithms improve and hardware costs decrease, prices drop.

However, when new models are introduced, prices rise again before gradually declining over time. This cycle repeats every few months, with each version bringing a higher initial price point before stabilising.

"Every three months, six months, nine months, every player is gonna have their prices go down, then a new model comes in… It’s gonna get to a higher price point, then they will also go down," Jean-Manuel Izaret, Managing Director and Global Leader, Marketing, Sales & Pricing Practice, BCG.

While foundational AI models follow this pricing trend, companies like Microsoft take a different approach, "pricing per user" and progressively granting access to more advanced models as costs decrease.

This evolving structure highlights the balance between technological advancements and pricing strategies in AI-driven industries.