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AI Has Changed Your Customer—Here’s How to Keep Up

Discover how AI is reshaping customer expectations and learn the critical steps leaders must take to adapt.
Insights

Jun 16, 2025

9 min read

Julia Sholtz

Julia Sholtz

Group Product Marketing Manager, Amplitude

A robot browsing through analytics charts, representing AI use

The sparkle of an AI icon means more than just a new feature—it means a new way of doing business.

As companies integrate AI deeper into customer interactions, customers are rapidly adjusting their standards. AI-powered chatbots and predictive support have led 90% of customers to expect immediate responses to their questions. Machine learning has accelerated the expectation of deeply personalized interactions and experiences. And with McKinsey research finding that 72% of organizations have already integrated AI into at least one of their core business functions, and the vast majority planning to increase their investments over the next three years, it’s clear that the AI customer evolution is only going to accelerate.

These changes present a huge opportunity to executives. McKinsey reports that companies prioritizing personalization generate 40% more revenue than ones that don’t, and innovating with AI-enhanced interaction can drive better retention across all age groups. Effectively implementing customer-centric AI does more than keep up with your peer companies—it lets you outpace any competition that doesn’t.

However, simply adding a new AI vendor to your company’s tech stack isn’t enough to capitalize on evolving customer expectations—your organization has to be ready. We’ve identified five strategic steps for leading a successful AI adoption effort. Read on for how they can help you accelerate AI smartly and build a new backbone of customer-centric innovation.

1. Set the tone with a first-mover strategy

For your organization to follow you, you need to make a key decision about your AI adoption strategy up front: Will you aggressively pursue a first-mover advantage or take a wait-and-see, fast-follower approach?

The allure of waiting for best practices to emerge may seem prudent. Many companies hesitate due to all the unknowns in this new field—concerns about implementation costs, data security risks, timelines, or the lack of readily available AI talent.

However, hesitation also ignores the unique speed to AI technology evolution and the advantages that come with it. Adopting a first-mover strategy gives you:

  • Market leadership: Being first to market with innovative AI solutions establishes your brand as a leader. This drives customer acquisition and greater market share.
  • Learning and optimization data: Early adoption allows for rapid iteration and optimization. You gain invaluable insights from real-world data, refining your AI models and processes faster than competitors.
  • Control of customer expectations: By setting the standard, you can define what customers expect instead of having to react to the expectations set by your competitors.

Due to the risks of waiting and the benefits of acting, I advocate for the first-mover approach. When you make your choice, let it be a rallying cry for your organization to carry you through the adoption process.

2. Establish good data governance

Before you even start down the AI path, though, you need to make sure your data is ready.

As many as 62% of organizations identify data governance as the biggest obstacle to launching AI projects. Effective AI adoption requires good amounts of clean, reliable data—as the adage goes, “Trash in, trash out.” Without a solid data foundation, AI algorithms will produce inaccurate or biased results, undermining their effectiveness and potentially damaging your business.

Modern data governance practices are essential for ensuring that the data used to train your AI algorithms is accurate, consistent, and trustworthy. These practices encompass data quality as well as broader ethical considerations, including how data is collected, stored, and used. Respecting privacy rights and ensuring transparency are crucial to building customer trust and maintaining regulatory compliance.

Learn more about making data governance your competitive advantage with The Modern Guide to Data Governance.

3. Conduct an AI maturity assessment

After or alongside your data governance work, you’ll need to understand your organization's current AI maturity level.

Conducting an AI maturity assessment helps you understand your organization’s existing capabilities while identifying strengths, weaknesses, and areas for improvement. There are 5 stages in the AI maturity process:

  1. Aware: The company hasn’t implemented AI but is curious about its potential impact.
  2. Active: The company uses AI in specific areas like data science and analytics.
  3. Operational: The company is integrating AI tools more extensively and optimizing processes to get more efficient.
  4. Systematic: The company builds new business models and tools to capitalize on AI efficiency and innovation.
  5. Transformational: AI has become an integral part of the company’s DNA.

Knowing where you are at the present is essential for understanding the path to where you want to go.

AI maturity is built on a strong digital foundation, so it’s equally important to understand and evaluate your organization's overall digital maturity. Check out our Digital Maturity Checklist to help better develop your technological readiness.

4. Start with easy wins on AI investments

The best way to build transformative momentum is to rack up some quick wins.

Evaluate the different AI initiatives you might tackle based on their impact, risk, and how they align with your core business objectives or values. Impact could be potential to improve key metrics like customer retention, revenue growth, or operational efficiency. Risk may come in the form of technical feasibility, data availability, or team capacity.

For example, to enhance their product discovery and personalized shopping experience with AI, Amazon started with innovations that capitalized on their core strengths without being huge overhauls. AI-generated product listings made it easier for sellers to use their platform, and AI-summarized product reviews drew on their extensive review collection to bring insights to customers faster.

With a matrix of impact versus effort, you can identify your easiest initial AI wins. Low-risk, high-ROI use cases within AI-powered personalization, automation, and experimentation offer a great way to demonstrate the value of AI before scaling to more complex initiatives.

5. Usher in a cultural shift across your organization

Implementing technology and getting some wins are just the beginning—full adoption requires a fundamental cultural shift across the entire organization. Approach your AI initiatives not as isolated IT projects, but as transformative experiments that will impact every department in your organization.

The key areas of focus as you foster the AI culture shift are to:

  • Demystify AI through targeted education. Set up workshops and training sessions tailored to specific departments, showcasing AI's relevance to their daily workflows and addressing any concerns they might have.
  • Champion cross-functional collaboration. Establish cross-departmental AI task forces to break down silos and encourage open communication, ensuring all teams have a voice in AI implementation.
  • Highlight tangible AI success stories. Present real-world examples of how AI has improved processes and outcomes—especially from within your organization.
  • Empower employees through experimentation. Provide access to AI tools and encourage experimentation to create a sense of ownership and promote innovation.
  • Establish clear communication channels. Create a central location for all employees to learn about AI initiatives and provide feedback.

This cultural shift may be a longer-term process, but guiding your people through it will ensure that the gains from AI take deep roots in your organization and aren’t a flash in the pan.

The power to center the customer

AI is changing what customers expect from business interactions, but it’s also changing how you can center them. It’s enabling faster experimentation, more precise targeting, and deeper personalized product experiences at scale. Leaders who embrace AI now will be the ones shaping—not reacting to—customer expectations in the years to come.

This systematic approach will help jumpstart your organization’s AI acceleration.

To fully unlock the power of AI, it also helps to have the right tools. By partnering with Amplitude, you gain access to a platform that puts the power of AI to work for you—giving you data insights and automating key processes so you can create truly tailored experiences.

Get started with Amplitude for free today.

About the author
Julia Sholtz

Julia Sholtz

Group Product Marketing Manager, Amplitude

More from Julia

Julia is a product marketer at Amplitude, focusing on go-to-market solutions for enterprise customers.

More from Julia
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