Generic recommendations are dying. The “customers who bought this also bought that” era is ending, replaced by AI that knows not just what you bought, but when you bought it, why you needed it, and what else was happening in your life at the time.
My prediction for 2026 is that most companies will either personalize or lose customers to those that do.
Marketing Moves Beyond Mad Libs
McKinsey’s research shows 75% of consumers reject content that doesn’t feel relevant to them. The old approach of filling in blanks with a customer’s name and purchase history no longer cuts it.
AI in 2026 will create genuinely tailored content. If you’re training for a marathon in the spring, online retailers will automatically suggest shoes for longer distances, not ones you’ve bought before.
The shift is accelerating across industries, particularly in environments where personalization directly impacts conversion and retention. According to Deloitte, companies moving to hyper-personalization generated returns 8x higher on their marketing spend.
AI can also analyze browsing patterns and seasonal behavior for thousands of customers, something no human marketing team could handle. For example, Accenture’s 2025 Technology Vision found that 79% of executives expect conversational AI to know more than just customer age and shopping history.
Beyond Shopping Carts
Finance will personalize in ways that matter. Your banking app won’t just track spending, but will notice that your rent is due, and suggest moving money before overdraft fees hit.
Education platforms will adapt lesson pacing to how quickly someone grasps concepts, not how quickly the average student does. Corporate training will deliver information when employees actually need it for their projects, not in scheduled quarterly sessions.
In sectors where workplace tools are becoming genuinely adaptive, Ivaylo Bozoukov has seen AI move from reactive support to anticipatory assistance. The AI doesn’t wait for someone to search for information. It surfaces relevant data when that person starts a task that will need it.
“The real shift with AI-driven personalization is that it stops reacting and starts anticipating,” says Ivo Bozukov. “When systems surface the right information or offer at the moment it’s actually needed, they stop feeling like software and start feeling like good service. That’s where retention and trust are really built.”
The Privacy Paradox
People want personalization, but don’t trust how companies get the required data. Qualtrics’ 2026 research found that 64% of consumers prefer personalized experiences, but only 39% think the benefits justify the privacy trade-off. The gap is even starker with AI, specifically with 53% citing data misuse as their biggest concern, but 71% expecting personalized interactions. Consumers want services that know them, but are wary when they seem to know too much.Â
Trust Through Transparency
The organizations succeeding with personalization are upfront about what customer information they collect and why. Salesforce research shows 92% of consumers trust brands more when they clearly explain data usage. The winning approach is being transparent about collection and giving users real control.
This dynamic is playing out across multiple sectors, particularly where organizations embedded privacy controls early. These organizations avoided the trust problems that plagued companies that added privacy features as an afterthought.
Deciding the Winners
Generic experiences will drive customers away in 2026. So will personalization that crosses privacy boundaries. The companies that deliver tailored experiences while earning user trust will define what good service looks like.