Beyond Personalization: How AI is Revolutionizing Customer Experience Forever

Turning Proactive, Predictive Customer Experiences into Value Creation

Conventional wisdom has long positioned personalization as the holy grail in customer service. Now, however, the rapid rise of AI is ushering in a new chapter in which personalization is a prerequisite, but is far from sufficient.

This shift from personalization—tailoring products, messages, and services to meet individual preferences—to experience transformation goes far beyond a further fine-tuning of messaging and delivery strategies. Instead, it depends on fundamentally reimagining how humans and technology work together to co-create experiences that feel alive, authentic, and adaptive.

By 2029, 80% of customer service interactions will be AI-mediated in real time, a fourfold increase from 2023, according to research from Gartner. Even more significantly, it’s predicted that 50% of those interactions will be initiated proactively by AI by 2030.

Harnessing the potential of this anticipatory engagement, where AI agents orchestrate ongoing conversations between the customer and the computer, will be key to building brand loyalty and trust in a new era of customer experience. And it will depend in large part on leadership’s ability to shift their understanding of value creation, change management, and, ultimately, the entire experience transformation.

Redesigning Value Creation

Leaders across industries are coalescing around this new approach to customer engagement, where personalization is becoming table stakes: In fact, 70% of executives surveyed think customer expectations around experience are outpacing their organization’s ability to adapt.

We’re rapidly approaching a reality where customers interact with the same persistent AI persona across all touchpoints over years, building familiarity and trust. And advances in multimodal AI (text, voice, image, sensor data) will allow systems to interpret complex customer contexts—location, mood, device usage—and tailor outreach accordingly.

Anticipatory customer engagement is poised for tremendous growth, as 72% of global brands report they’re investing in “experience orchestration platforms” for real-time journeys, according to Forrester. As companies gain richer, deeply contextual knowledge about customers, the challenge will be how to respond and engage in a way that drives ROI.

The value that's delivered through AI is fluid, and creating value requires a long-term vision and strategy. A road map that allows organizations to remain flexible in the face of ever-evolving technology is preferable to a fixed three-to-five-year road map.

The companies that embrace a “brand down” and “infrastructure up” approach will be well-positioned for success. A unified data infrastructure that supports real-time decisioning and complex insights, and addresses technical debt and siloed data, forms the foundation for an organization to transform on behalf of the customer. But that’s only half the battle, because even the most advanced AI models are only as valuable as the proprietary data they can access and learn from.

The “brand down” component involves integrating intelligent systems as the arbiters of experience, and managing multiple new inputs that impact brand narrative in unexpected ways. Companies will need to build on the infrastructure foundation by designing experiences that generate new, high-quality data in return.

After all, the experience a consumer has with a brand can’t be separated from their perception of that brand, and in an agentic world, that experience is becoming more difficult for companies to control. Whereas personalization is built on a structured paradigm of controlled ecosystems, experience transformation fundamentally changes the way that a brand interacts with a customer, going from reactive and self-contained to proactive and all-encompassing.

Mindset Matters: Preventing Pilot Purgatory

Why do 90 to 95% of AI pilot programs fail? In part, we can attribute it to both a misunderstanding of what adoption really looks like, and an underestimation of the depth and breadth of change required to achieve it.

The 2025 Kyndryl Readiness Report—which assesses how prepared businesses are for future risks and technology transformation—found that 62% of respondents are still in the experimentation phase and 72% said they've started more pilots than they can realistically scale.

There’s no single cause of “pilot purgatory”—companies struggle to move from proof of concept to production scale for a wide range of reasons, but often what’s missing is the right approach from leadership. It’s essential for leadership to serve as stewards and evangelists of AI, but transformations succeed and fail based on buy-in from across the organization.

Change management isn’t a supporting factor; it’s the linchpin, the primary determinant of success for AI transformation programs. From KPIs, to team structures, to operational models, to incentive structures — all have to be redesigned around this kind of autonomous way of working going forward.

According to research from the 2025 Kyndryl Readiness Report, 29% of executives say the lack of internal talent is one of their main barriers to success. When it comes to talent, mindset will matter more than years of experience or a list of skills on a resume. That starts with a person's ability to be flexible, to have an always-on learning mentality, and to understand that jobs are going to shift in the next three to five years more than they ever have in the past. And it also requires a recognition that going forward, managing people will also have to include managing teams that have agents on them and human-to-agent interaction will be a core skill.

Change management will need to shift from a one-and-done mindset into something that's always on and governed, because while AI can strip away repetitive, low-value tasks, human expertise, empathy, and lived experience remain irreplaceable, especially in the final refinement that determines quality.

Experience Transformation in Action

Businesses can mitigate the risk of falling into the pilot trap by taking a dual-transformation approach to AI implementation. In this model, a transformation core tests new AI-driven experiences, unencumbered by organizational or technical constraints, while an operational core scales successful innovations across the enterprise.

Transformation core:

• Operates outside of legacy processes and business constraints
• Offers an experimental environment to explore, test, and validate ideas
• Finds the breakthroughs

Operational core:

• Designed around horizontal change areas rather than vertical departments
• Integrates innovations into day-to-day, core business operations
• Delivers the value at scale

In short: the transformation core is the equivalent of a pharmaceutical research lab that discovers a new breakthrough drug, and the operational core delivers that drug to a population at scale. Transformation core finds the breakthroughs; operational core delivers the value.

The Next Technology Revolution

Consumers are becoming increasingly comfortable letting AI agents act on their behalf, a true turning point in how customers interact not only with a single brand but across different channels with multiple brands. Rather than doing everything themselves, people will increasingly hand over intent, authority, and even decision-making to digital agents. This is the next technology revolution, and is an even more dramatic shift than the invention of mobile applications and how that changed our relationship with devices and ecosystems.

Businesses will need to give AI the ability to learn and unlearn quickly, so it can adapt to new situations as they arise and move beyond simple automation to becoming a co-creator of the experience. That means the relationship between customer and company will shift from “I click, you deliver” to consent-based collaboration, and designing these “moments of choice” so they’re unbiased, easy to understand, and reversible will be key to building trust.

Companies that engage customers proactively see 29% higher customer satisfaction scores compared to reactive-only approaches, but that requires having the systems in place to continually give customers what they desire from a personalization standpoint, from an experience standpoint, and from a privacy standpoint.

The onus is on companies to deliver frictionless but data-compliant experiences, and progressive disclosure allows you to deliver value with minimal data at first, then enhance experiences as the customer profile builds — always giving customers the ability to change their minds. This transparent value exchange means showing customers exactly what the data they give is enabling in terms of experience improvements.

The real opportunity will be designing journeys that feel seamless from start to finish, with AI quietly enhancing the experience rather than getting in the way.

The Customer Is (Still) Always Right

Leaders inherently grasp the old adage that “the customer is always right,” and why it still matters for customer service. They understand how that mindset should manifest across organizations and customer interactions. But most leaders likely have not considered how that translates to their agentic AI systems.

We posed the question to ChatGPT directly: “Do AI agents know that the customer is always right?” It replied, “AI agents don’t ‘know’ anything in the human sense, but they can be programmed or trained to act in ways that align with the principle if that’s what the business wants.”

Therein lies the challenge. Companies are generating more output than ever before, but output doesn’t equal value. Realizing a return on investment depends on leveraging this newfound productivity in service of collective change. As the shift from personalization to experience transformation upends how brands engage with customers, success going forward will depend less on a broad metric of overall AI implementation and more on the specific ways a company harnesses it to provide experiences that are holistic, adaptive and unique to a company’s brand. That’s how AI lives up to its potential as a game-changing, differentiated superpower for a company.