Is it Time to Put AI in Charge of Pricing Strategies? Most Firms Seem Hesitant to Take the Leap

Despite corporates enthusiasm for AI, its use in pricing strategies — using algorithms to determine optimal prices for goods and services — is yet to gain the approval of many.

More than half of those canvassed by data and technology consulting firm Valcon do not harness any form of AI for business purposes — and only 27 percent deploy AI-based pricing.

The study surveyed 1,500 European, Asian, and American SMEs and corporates; 40 percent had over 10,000 employees. It was found that 53 percent don’t believe their internal data is mature enough for AI-based pricing. That renders them unable to benefit from a practice that experts say can help maximise margins at a time when they are facing headwinds from inflation, volatile market conditions, and fluctuating customer loyalty.

In terms of the risks and barriers associated with AI-based pricing, respondents — who included CEOs, CFOs, CSOs and CPOs (chief pricing officers) — believed the loss of control or a lack of understanding was the key risk (34 percent), followed by a lack of internal acceptance (23 percent), high maintenance costs (13 percent) and compliance and regulatory issues (11 percent).

Key statistics from the AI-based pricing study:

• 76 percent of respondents consider AI-based pricing relevant or highly relevant
• 27 percent reported regular use of AI to optimise promotions
• 19 percent regularly review and optimise prices via Chat GPT, while eight percent use specific applications like dynamic pricing
• 53 percent say their internal data is not sufficiently robust for AI-based pricing
• 67 percent say their IT infrastructure is not mature enough.
• 46 percent use historical transactional data for pricing, 21 percent use internal cost data, and 11 percent use customer demographic data.

Study author Danilo Zatta said that while most respondents recognise the transformative potential, adoption rates are lagging. More than half of respondents reported an increase in profitability in 2022, despite inflation and market volatility.

As economic growth continues to stagnate, Zatta says the use of AI will become critical for corporates to drive top-line profitability. “It capitalises on machine learning and data analytics techniques to analyse large volumes of data, making pricing decisions that maximise profits, spur revenue growth or fulfil other objectives, such as increasing market share or customer satisfaction.”

Data quality and IT architecture are seen as the biggest inhibitors to AI-based pricing, and Zatta urges companies to start with small pilot projects. The perceived enormity of big data projects can put some organisations off. “It’s pricing and data evolution, not revolution,” he says. “But time is of the essence.”