AI personalization isn’t simply a nice-to-have anymore; AI personalization has rapidly evolved into a necessity for brands looking to improve relevance, resonance, and ROI. Recent discussions at Cannes Lions hosted by McKinsey with Eli Stein (Partner, McKinsey & Company) and Loreal Lynch (CMO, Jasper) have shown us that marketing strategies focused on personalization at scale are critical to engaging with consumers in today’s world, and generative AI is the accelerant to make personalization at scale a reality.

While businesses continue to wrestle with broken customer journeys and content overload, what’s wonderful about AI-driven personalization is that it can automate the creation of micro-targeted, hyper-relevant content at scale across every digital touchpoint.

Why Brands Are Rushing Toward AI-Powered Personalization

Consumer expectations have accelerated faster than many marketing departments can keep up with.  Consumers expect content that speaks to them personally, not “dear customer,” but contextualized personally, socially, and even emotionally. 

As Eli Stein said, “All of this is great, but what is the secret sauce is relevance; relevance is not optional anymore. If you are in multilingual, multicultural markets like India, and you can’t personalize, then you don’t exist.” This is the reality for marketers today, especially for consumer tech, e-commerce, and media. 

Today, consumers don’t want generic messages. They expect any interaction they have with a brand, whether an advertisement, sending them an email, or landing on a product page, or they are getting a response from a bot, to all be personalized and relevant, as if it were curated for them.  AI has made it possible to have personalization at scale, as it learns the behaviors of users and can adaptively shape contextual content based on real-time signals.

How Leading Organizations are Successfully Scaling Personalization 

Scaling personalization is more than just distributing the odd automated campaign; it is transforming the marketing operating model to allow for replicable, quantifiable, and cross-functional personalization. 

The high-performing companies are doing this by: 

  • Integrating generative AI tools into their content supply chain 
  • Leveraging AI agents to auto-generate a first draft of elegalreviews or modular product descriptions 
  • Building cross-functional relationships between Chief Marketing Officers, Chief Information Officers, and product teams 
  • Designing a framework for A/B testing to optimize personalized messaging feedback loops at scale 

McKinsey estimates that organizations that successfully achieve personalization will see 10-15% faster revenue growth and 20% more customer satisfaction. These are not wishy-washy metrics; they are destiny disguised as business impact.

The Role of Generative AI in Personalization

Generative AI is taking personalization to a new level beyond simple automation. Beyond segmenting audiences, it is creating content at scale and in real-time for each niche segment.

Examples might include:

  • Multilingual, culturally contextual personalized product recommendations
  • Content variations based on user behavior, tone preferences, and purchase history
  • Not just personalizing what you say, but how you say it, when you say it, across all channels

As Loreal Lynch, of Jasper, mentioned at the Cannes discussion, “Generative AI is not just a productivity tool, it is a creativity multiplier. But only with the right bounds.”

She encouraged brands to have a robust AI governance model, inclusive of legal, ethical, and design checkpoints to reduce misuse and protect their brand.

Scaling Personalization Is Also a Leadership Challenge

When personalization initiatives succeed, McKinsey research finds that it is rooted in the partnership of the CMO, CPO, and CTO. This “alliance of three” supports agile decision-making, integrating technologies quickly, and working from a single view of the customer journey.

But it is not simply a CMO, CPO, and CTO affair.

  • In scaling personalization maturity for brands, considerations to undertake include:
  • Invest in training of AI and data literacy in all marketing teams
  • Define guardrails for responsible AI
  • Use zero-party and first-party data to feed personalization efforts while remaining trustworthy.
  • Ethical use of zero-party and first-party data for personalization, in line with frameworks from GDPR and CCPA. 

Scaling personalization is not only technological; it is about transforming how teams work together to deliver on business outcomes.

Evergreen Opportunity: Embedding Personalization into the Brand DNA

While this topic surfaced during a Lewes Lions panel in July 2025, it’s evergreen. AI personalisation is now a central part of long-term marketing plans.

Companies can leverage this as a long-term growth engine by:

  • Creating an AI Personalisation playbook for repeatability
  • Setting up feedback loops that improve personalisation models
  • Including generative AI in their emotion-aware marketing plan
  • Creating a personalised product onboarding experience rather than simply personalised advertisements.
  • Personalisation is no longer just pushing product—it’s creating lasting, relevant brand experiences across the lifecycle.

Recommended Best Practices To Optimize Personalization ROI

If you are keen to put these valuable learning lessons into action, I’d recommend that you start with a few best practice strategies:

  • Audit and review your current personalization strategy: Can you sustain personalization? Are they truly AI-enabled
  • Select a compelling high-impact use case (for example, a personalized email journey or localized landing page)
  • Develop a governance approach to using AI content
  • Train marketers on how to define creative prompts and explore the idea of experimentation
  • Align marketing, tech, and product KPI’s around customer relevance and business success. 

Organizations that are successfully investing in personalisation are the ones who are, ongoing, treating personalisation as a capability, not a campaign.

Conclusion

AI personalization is changing everything about marketing as it can now create relevance and scale. Marketers have the potential for measurable growth and incremental customer engagement, provided there is a process, workflow, and governance to support them. Generative AI is developing at an incredible rate, and the organizations that will lead the future of customer experience and digital brand loyalty will be those that embed personalization into their DNA.

FAQs

1. What is AI-powered personalization in marketing? 

AI-powered personalization in marketing is the systematic use of AI and machine learning to offer personalized content, offers, and customer experiences driven by real behaviors, preferences, and context, automatically at scale.

2. How does generative AI go one step further with personalization? 

Generative AI can not only automate personalization but also create personalized content – text, images, or experiences – in real-time through micro-segments based on emotional and physical context.

3. What are the main benefits of personalization at scale? 

Marketers can expect increased conversions, improved customer satisfaction, reduced acquisition costs, and, best of all, reduced time spent replicating content, offers, and experiences.

4. Which industries have the biggest capability for AI personalization? 

Retail, e-commerce, financial services, health care, and entertainment lead the pack as leaders driving growth or competitive advantage through AI personalization capability.

5. How can organizations govern AI-generated content? 

Organizations can govern content through internal policies, help with legal review, ensure brand safety, demonstrate that algorithmic bias is absent, and monitor AI to remain current and relevant.

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