Feature
The Gist
- Maximizing AI with minimal spend. Organizations are stretching budgets by upskilling teams and unlocking existing AI features in their current martech stack.
- AI shows up in content and chatbots. Generative AI is proving most useful in marketing content creation and customer-facing self-service chatbots.
- Personalization success hinges on maturity. Winning organizations pair advanced DXPs with focused strategy and enterprise-wide AI adoption.
In the CMSWire's State of Digital Customer Experience (DCX) 2025 report, customer experience teams reveal both their enthusiasm for generative AI and their real-world struggles to operationalize customer data and personalization.
Sound familiar? Personalization struggles. Customer data struggles.
With struggles come opportunities, though.
In this Q&A with my collegaue Tim Harnett, senior manager of research and content at Simpler Media Group (publisher of CMSWire), shares deeper insights from the recently-released findings — including how budget-conscious organizations are prioritizing AI and personalization, and what separates DCX leaders from laggards.
Table of Contents
- Budget Constraints and Prioritization in Digital Customer Experience
- AI’s Role in Customer Experience
- Understanding Customer Behavior
- Personalization Trends: Efforts Ramp Up
- Regulatory and Ethical Considerations in AI
- Where to Find the CMSWire 2025 State of Digital Customer Experience Report
Budget Constraints and Prioritization in Digital Customer Experience
Nicastro: Given that limited budgets and resources are the top challenge for DCX teams, how do you see organizations balancing investments in AI, personalization and customer data platforms while facing financial constraints?
Harnett: I see organizations doing more with less and potentially looking inward a bit more if they can’t get the budget for new tools. One of the main ways they could do this is by leveraging the AI capabilities already embedded in their current martech stack before investing in new AI-powered tools.
This shouldn’t be too difficult — nearly all martech companies are adding AI-powered capabilities to their offerings, so the chances an organization already has some kind of AI capability is very high.
In addition to using the tools they currently have, organizations should prioritize upskilling existing teams to better utilize current tools rather than hiring new specialized AI/personalization talent. Training current teams on current tools will help move the needle forward on AI utilization without incurring new costs.
Related Article: Digital Experience Platforms (DXP): What to Know in 2025
AI’s Role in Customer Experience
Nicastro: The report highlights that 45% of DCX teams are using generative AI for more than half of their work. What specific AI-driven use cases have shown the most measurable impact on improving customer engagement and retention?
Harnett: Using AI for content creation and chatbots are two of the biggest use cases we’ve seen from the research. In the survey, 38% use AI for content creation and enhancement, with many respondents specifically calling out ChatGPT in the open comments.
The specific content they’re creating varies — anything from marketing emails to social media posts. The other application with major adoption is chatbots for customer self-service and conversational experiences, with 40% using AI for this purpose. AI-powered chatbots can provide 24/7 customer support, handle routine inquiries and offer personalized assistance, which leads to more satisfied customers.
Understanding Customer Behavior
Nicastro: The report reveals that 49% of organizations have tools to understand customer behavior but struggle to act on insights. What are the main barriers preventing teams from leveraging customer data effectively, and how can they overcome them?
Harnett: There are four main reasons organizations might struggle with effectively leveraging customer data:
- Rapidly changing customer behavior (31% cite this): The pace of change makes it difficult to keep up with evolving customer needs and preferences.
- Diverse and complex customer behavior (29%): Customers exhibit a wide range of behaviors that are challenging to model and predict.
- Lack of in-house expertise (29%): Many teams lack the skills and resources to properly analyze and act on customer data.
- Siloed, fragmented customer data (28%): Disparate data sources and systems prevent a unified view of the customer.
Upskilling current teams and breaking down silos between departments are low-cost ways organizations can overcome these barriers. If the organization isn’t experiencing budget issues, it might look into investing in a Customer Data Platform (CDP) or other martech tool that can gather all customer data in one place.
Main Barriers to Leveraging Customer Behavior Data
These are the top four challenges DCX teams face when trying to act on behavioral insights, based on CMSWire's State of DCX 2025 report.
| Barrier | % Citing This | Why It Matters |
|---|---|---|
| Rapidly changing customer behavior | 31% | Customer needs and preferences shift quickly, making it difficult to keep up with expectations. |
| Diverse and complex customer behavior | 29% | A wide range of behaviors makes modeling and prediction more difficult. |
| Lack of in-house expertise | 29% | Teams often lack the skills and training needed to analyze and act on data. |
| Siloed, fragmented customer data | 28% | Data scattered across systems prevents a unified view of the customer. |
Personalization Trends: Efforts Ramp Up
Nicastro: Personalization efforts have increased significantly, with 67% of organizations implementing some form of personalization. What differentiates organizations that successfully derive value from personalization versus those that are still in experimental stages.
Harnett: The key differentiator seems to be having the right combination of technology, data, talent and organizational focus to move beyond experimental personalization and realize tangible ROI. In the report, we compare organizations whose tools are working well to those whose tools need work, to uncover key insights in this area.
Here are some examples of how successful organizations differentiate themselves:
- They have more mature, enterprise-grade Digital Experience Platforms (DXPs): 57% of organizations with effective tools have a DXP, compared to only 33% of those with tools needing work.
- There’s a stronger focus on DCX as a top organizational priority: 62% of those with effective tools see DCX as extremely important, versus 34% of those with tools needing work.
- There’s more advanced use of AI and analytics to power personalization across the organization: 49% of those with effective tools have AI deployed in their DCX, versus only 2% of those with tools needing work.
- There’s a higher level of organizational maturity and expertise in implementing personalization: 46% of those with effective tools are already seeing benefits, compared to only 9% of those with tools needing work.
Related Article: Taking Hyper-Personalization to the Next Level
Regulatory and Ethical Considerations in AI
Nicastro: With 66% of organizations now having formal guidelines for AI usage, how are companies ensuring compliance with evolving AI regulations, and what best practices are emerging for responsible AI governance in customer experience?
Harnett: There’s no silver bullet here; only by taking a proactive, holistic approach to AI governance can organizations reap the benefits of AI-powered CX while maintaining customer trust and compliance. This includes doing some or all of the following:
- Establishing clear policies and processes for ethical AI development and deployment, covering areas like data privacy, algorithmic bias, transparency and human oversight.
- Implementing robust data management and security practices to protect customer information used in AI models.
- Providing employee training on responsible AI practices to ensure consistent application of guidelines across the organization.
- Engaging legal/compliance teams to stay up-to-date on evolving AI regulations and adapt policies accordingly.
- Conducting regular AI model audits and performance reviews to identify and mitigate potential risks or unintended consequences.
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Where to Find the CMSWire 2025 State of Digital Customer Experience Report
You can access an executive summary of the full report on the CMSWire 2025 State of Digital Customer Experience. Check out my conversation with another colleague, Sarah Kimmel, on the DCX report on the CMSWire TV Digital Experience series.
We also covered the CMSWire 2025 DXP Market Guide in a Q&A with Tim Harnett in March.
Stay tuned for a Q&A with Tim on the CMSWire 2025 State of the CMO report.
