Photo credit: Clay Banks/Unsplash

This is the second entry in a series examining what key loyalty-program trends in 2026 – from AI-driven commerce to emerging coalitions – mean for brands and consumers. Read more in the series here. 

By Uwe Stueckmann

As loyalty programs evolve in an increasingly AI-driven commerce environment, scale is becoming a defining advantage.

The rise of agentic discovery and agentic commerce is accelerating a dangerous trend in the Canadian retail sector: The consolidation of market power among a handful of “hegemons.” Massive market presence, aggressive tech investment and global economies of scale make it increasingly difficult for smaller, specialized Canadian retailers to maintain a profitable market presence.

Retail’s middle-market players should take inspiration from Prime Minister Mark Carney’s appearance at Davos in January when he urged geopolitical “middle powers” to compete with the “hegemons.” To be long-term sustainable, a retail loyalty program must possess sufficient “gravity,” meaning the forces that keep a consumer within a program’s (and thereby a brand’s) orbit.

The concept is defined by these core components:

Frequency: How often does the consumer interact with the brand?

Wallet share: What percentage of the discretionary household budget is allocated here?

The dividend: The net “yield” or tangible value returned to the member.

Emotional resonance: The customer’s psychological engagement with the category (e.g., food vs. hardware).

Utility (low friction): The time saved or ease of use provided by the program.

The threat of agentic discovery

The emergence of large language models (LLMs) and autonomous AI shopping agents has fundamentally changed the discovery funnel.

AI agents prioritize retailers that offer structured, machine-readable data through APIs that allow them to compare pricing, availability and rewards in real time. If a middle-power retailer is not part of a major ecosystem, they are effectively invisible to the agent.

Agents are programmed to optimize value. When an agent searches for a product, it doesn’t just look at price, it calculates what can be considered the “loyal dividend” across the user’s known programs if that dividend is understood by the LLM.

In 2026, the most valuable customer will be the one whose AI agent has “pre-authorized” a specific program (like Amazon Prime, PC Optimum or Scene+) as the preferred source. A standalone specialty retailer cannot provide enough data or aggregate value to win this “default setting” in an AI’s logic.

Clarifying ‘the dividend’

In high-gravity programs, the dividend is more than just points – it represents the annual yield of participation.

This yield can take a few forms. There is the “financial yield,” which reflects tangible value such as cash-back or points earned as a percentage of spend, as seen in programs like PC Optimum, which offers a roughly 2% average return. There is also “utility yield,” which comes from time saved or friction removed in the customer experience; Starbucks’ Skip the Line is a good example. Finally, “access yield” captures the value of exclusivity, whether through limited-edition drops or member-only events.

For middle powers, the goal of an alliance is to aggregate these dividends. A 2% dividend on a $500 annual spend at a furniture store is negligible ($10). However, when that $10 is added to a pool of $500 earned from an alliance that also includes categories such as groceries and gas, it becomes a meaningful household asset.

Case studies in gravity

Programs with broad reach across multiple categories illustrate what a high-gravity loyalty ecosystem can look like.

PC Optimum, for example, spans everyday essentials such as food, health and fuel, alongside financial services. That breadth allows it to capture up to 50% of discretionary household spend and generate substantial value for members over time, creating potential to turn the program into something closer to a financial utility than a traditional marketing tool. It also creates a rich, continuous stream of customer data.

Most specialty retailers operate at the other end of the spectrum. An apparel or hardware store may only see a customer a handful of times each year, limiting both the value generated through its loyalty program and the depth of data it can collect. On their own, these programs often lack the scale to substantially influence purchasing behaviour, especially when AI-driven tools prioritize frequency, value and visibility.

This is where coalition models begin to offer a potential path forward. Programs like Scene+ bring together partners across categories, allowing them to combine frequency, spend and emotional engagement and create enough mass to compete with the massive multi-national and domestic players. However, the history of coalition programs such as Air Miles underscores that scale alone is not enough, sustaining these ecosystems over the long term requires a carefully co-ordinated strategy that offers clear value for partners and a compelling experience for consumers.

The inflection point

If you are a specialty retailer operating a standalone program in a low-gravity market, you are currently at a crossroads and should be considering one of these paths.

Increase gravity through alliances: Look to partnerships or coalition models with “middle powers” to aggregate spend, increase engagement and strengthen overall value proposition.

Orderly shutdown: Reassess whether the program is delivering a meaningful return. If participation accounts for less than 50% of sales or engagement falls below roughly 30% of members, the option of discontinuing the program should be considered.

In a world of retail hegemons, there is no middle ground – only those with gravity, and those who drift away.

Uwe Stueckmann is a former EVP of customer experience and SVP of marketing and CRM at Loblaw and VP of marketing and CRM at Shoppers Drug Mart. He is also the co-founder of Innovate Marketing, a consultancy launched last fall that focuses on AI’s effects on commerce.