Editorial
As organizations rush to implement generative AI, they are learning an important lesson: technology without a proper foundation yields diminishing returns.
While vendors and consultants paint pictures of AI revolutionizing every business process, the reality is more nuanced. Success in genAI implementation isn't about having the most advanced models. It's about having the right data, governance and a customer understanding in place first.
In a 2024 IDC report authored by Sudhir Rajagopal, 35% of CX executives agreed that capabilities such as generative AI will have the biggest impact on their organization's future CX strategy. Leading CX organizations (only 11% globally) demonstrate improved year-over-year performance on metrics such as customer lifetime value (18%), customer satisfaction (18%) and repeat purchases per customer (16%). The report emphasizes that to differentiate and capture value from intelligent experiences, enterprises must first shore up trusted customer data infrastructure and industrialize a system of connected insights.
If the company's push is to forge ahead quickly, let’s dig into it!
The Foundation: Governance and Data Quality First
Before diving into sophisticated AI implementations, organizations must establish solid data governance frameworks and ensure good data quality. The reality is that many companies don’t. This isn't just about AI compliance; it's about creating a sustainable foundation for AI success.
The 4 Core Barriers to Entry
- Lack of Data Quality: Many organizations have data that is untrustworthy, incomplete and disparate. AI is worthless to anyone who doesn't have their data right.
- Data Governance: Setting standards and definitions to establish the foundation for AI success requires clear governance structures and processes.
- Experimentation Framework: Identifying key customers (Ideal Customer Profiles) and acting on these profiles to continue learning requires methodical experimentation.
- Human Capital: Implementing a change management strategy is what will bring it all together. The talent shortage is a reality. Any currently available tool/agent will not replace the need for investing in critical thinking individuals with industry expertise who can provide meaningful context and feedback to execute a good AI performance strategy.
Related Article: Collaborative Governance is the Path to Globally Inclusive and Ethical AI
Understanding Ideal Customer Profiles
Many leaders think they have an ICP but, typically, they don't. If you truly do, congratulations! ICPs are critical components for go-to-market strategies, retention, etc. and influence both marketing and sales. Being clear about who you are serving ensures the team leverages insights in moving this iterative process forward.
ICPs vs. Buyer Personas
Don't confuse buyer personas and ICPs. They are two different things:
Buyer Personas: Fictional summaries based on some research about the ideal person or scenarios tied to an individual that you want to reach.
Ideal Customer Profiles: Actual live and available information AI gathered on specific decision makers with specific information about your product/service. ICPs also include problems, underserved areas and emotional connections, allowing for greater specificity.
Creating an Effective Ideal Customer Profile
To develop a meaningful ICP that can drive AI success, ensure your team follows these steps:
- Gather and analyze your customer data
- Review your best customers (scoring high, medium and low value) and identify shared traits (customer lifetime value is particularly important)
- Build a dynamic customer profile, requesting the model to summarize the highest value customers or buying groups (decision makers, influencers, etc.)
- When feeding information into AI, include emotional drivers and learnings from customer conversations in your prompts (building upon each prompt as you move along the process)
- Develop an experimentation program and act upon the results for improved efficiencies and revenue growth. Ensure you go beyond just automating lower productivity level tasks.
At times, corporations underestimate the power of speaking to individuals in their ICP. Their feedback can inform the specificity needed and allow creative flows as you brainstorm content ideas for solving pain points and personalization.
Connecting ICPs to GenAI Implementation
If your company is fortunate enough to have a solid ICP, it's time to unearth its value. There are common areas where more mature companies (and not many exist) begin their AI strategy to affect sales, marketing and support for long-term value:
The Model Training/Coaching Approach
Begin with an initial ICP, start small and review results, then expand through experimentation. This approach starts with the ICP Best Practices Manifesto (communication and "how to" guidelines) and then moves to showcasing or leveraging marketing audiences with consistent messaging.
This develops into an experimentation plan as a proof of concept to analyze differences between:
- Ideal customer profiles
- Previously developed audiences or personas
- Underperforming audiences
Your model will be on an iterative learning cycle. Because you're leveraging real data, you're developing ongoing value.
The Problem-Solving Approach
Get specific about your audience, solve specific problems and create segments leveraging available demographics, firmographics, advocacy scores and more.
- Focus on your dream customer list
- Look at industries and types of customers
- Remember that people are buying (B2B/B2C, these principles still apply)
- Add triggers (events happening within the people/company that cause a need)
Examples: new leadership, adopters, revenue potential, scaling sales team, new customer needs
It's also beneficial to include macro trends, broader AI world events impacting the customer. Typically, it takes eight touches to turn a lead into an opportunity. Companies that are open to different approaches and leverage human-centered design learn more about their customers and ultimately see the best returns.
Practical Use Cases
Use Case 1: Personalization & Predictive CX
Implement personalization and split testing with high-value customers and customers further down the customer journey. Leverage model scoring to determine predicted needs and/or next steps, then test if the drivers align with desired results (intent, repurchase/additional purchase).
Use Case 2: Sales Lead Optimization
Leverage your ICP to identify and prioritize sales leads that match your ideal profile. Companies that succeed see scalability because they mobilize their ICP effectively. They track motions and conduct backward analyses to understand patterns.
Use Case 3: A B2B Example
A B2B company identifies itself as superior to a competitor in an underserved market. By leveraging industry data and AI-driven experimentation, they pinpoint areas of high conversion and low performance. Mature AI-led organizations analyze win rates, revenue trends and churn metrics to refine ICP targeting and experiences. The ICP and AI adjust. Some sales divisions even adjust sales compensation structures based on ICP conversion rates, reinforcing AI-driven decision-making.
For Organizations Still Preparing for AI Leadership
When people insist on using AI to solve problems without considering whether it's the best solution for the bigger business question/problem and not just the “cool new tool,” it's time for discovery and consulting, as it might not be the best option.
- Conduct Brainstorming Exercises: Ask internal teams (and strategic vendors/partners) to provide a wish list with no limits. Ask "why?” and “so what?” and follow up with "how does this impact business growth?"
- Elevate the Thought Process: Move beyond the assumption that AI will just handle lower-level work. Discover what kind of intellectual design or partnering can truly expand knowledge and develop new ways of working. For example, how will velocity impact sales growth with improved efficiency in timing and personalization?
- Address People and Change Management: The most common underlying issue in AI implementation is the human element. Change management and upskilling needs to be addressed throughout the process of implementing your AI strategy. This will also lead to better adoption rates and cultural changes.
Related Article: AI Implementations, Enhanced Customer Loyalty: Today's Value-Driven Contact Centers
The Path Forward
Technological sophistication matters less than foundational excellence. By focusing first on governance, data quality, well-defined ICPs and human capability, organizations create the conditions where AI can deliver extraordinary value.
Webinar
Sep
25
CMS Briefing: A Live Look at What’s Next in AI-Driven Platforms
Learn how leading organizations are using AI‑driven tools to publish faster, personalize smarter and stay secure.
Register
Webinar
On demand
Ready or Not: How Data-First Organizations Are Unlocking Agentforce Potential
Learn how to cut through the noise, activate Agentforce and build a Salesforce AI strategy that actually delivers.
Watch Now
Webinar
On demand
AI in Customer Service: Faster Resolutions, Happier Customers
Don’t let rising demand burn out your team. See how to build a smarter, more resilient support org.
Watch Now
Webinar
On demand
From Hype to High-Impact CX Strategies That Actually Scale
Turn buzzworthy AI and outsourcing trends into measurable CX wins with fresh 2025 data.
Watch Now
Webinar
On demand
Insights to Action Rethinking the Contact Center for Real Business Impact
Join our exclusive webinar to hear CX executives share their innovative strategies for transforming service delivery.
Watch Now
Webinar
On demand
Accelerating Healthcare Ops with AI
Sign up to see how your peers are putting AI to work — and making it stick.
Watch Now
The question isn't whether genAI will transform marketing and customer engagement — it already has. The question is whether your organization has laid the foundation to capture that transformation's value.
For marketers and executives navigating this landscape, the path is clear: start with what you know about your best customers, build the foundation and let technology amplify that understanding rather than substitute for it.
Learn how you can join our contributor community.
