The promise of artificial intelligence (AI) in customer care is compelling: streamlined operations, personalized customer experiences, proactive issue resolution, and significant improvements in satisfaction and retention. However, turning this promise into reality can be challenging. Many enterprises discover that adopting AI at scale in customer care involves navigating technical, operational, and cultural hurdles that can slow or even derail transformation efforts.

With over two decades leading global technology support teams, I’ve seen firsthand both the promise and the pitfalls of AI adoption. At TeKnowledge, our collaboration with Genesys enables organizations to overcome these challenges, turning potential barriers into strategic advantages. Below, I share common pitfalls and best practices enterprises should consider as they scale AI effectively in customer service environments.

Pitfall #1: Underestimating the Complexity of Integration

Common Barrier:
AI isn’t a plug-and-play solution. Enterprises often underestimate the complexity involved in integrating AI with legacy systems, multiple data sources, and existing customer service platforms. Poorly executed integration can result in fragmented customer experiences, lower efficiency, and frustrated agents.

Best Practice:
Successful integration starts with careful planning and leveraging expert managed services. Consider partnering with a provider experienced in complex integrations—like TeKnowledge—that can facilitate a structured adoption process, ensuring seamless connections between AI-driven solutions, CRM systems, contact centers, and other business-critical platforms. Properly integrated, AI becomes a force multiplier, delivering unified, consistent customer experiences across all channels.

Pitfall #2: Insufficient Quality of Data

Common Barrier:
AI thrives on data. Yet many enterprises struggle with siloed, fragmented, or poor-quality data. According to recent surveys, 54% of companies identify fragmented data as the biggest barrier to successful AI implementation. AI trained on incomplete or inconsistent data can deliver inaccurate predictions and ineffective customer interactions.

Best Practice:
Begin by ensuring data cleanliness and consistency. Investing in data governance and unification strategies—breaking down silos and creating a single, comprehensive view of the customer—is essential. Organizations should employ robust data quality processes before deploying AI. At TeKnowledge, we emphasize the importance of data alignment early in the implementation process, setting the stage for AI to deliver meaningful insights and accurate predictions consistently.

Pitfall #3: Overlooking the Human Element

Common Barrier:
AI implementation is not purely technical—it significantly impacts your workforce. Resistance to AI often comes from employees who fear automation may replace their roles. Additionally, poorly executed AI deployments can inadvertently increase workloads if not carefully integrated into workflows.

Best Practice:
The most effective AI deployments complement and empower human agents rather than replace them. Enterprises should prioritize robust change management programs, clearly communicating the role of AI as a support tool, not a replacement. Involving support teams early in the planning process, offering comprehensive training programs, and demonstrating how AI will improve their workflows can reduce resistance and increase adoption. When employees see AI as an ally, adoption accelerates, and employee satisfaction improves—leading to better customer experiences.

Pitfall #4: Difficulty Defining Clear ROI

Common Barrier:
Many organizations struggle to articulate clear, measurable outcomes from AI investments in customer care. Without clearly defined ROI, enterprises can hesitate, stall, or abandon AI projects prematurely.

Best Practice:
Clearly define metrics of success from the outset. Organizations should identify specific KPIs—such as customer satisfaction scores (CSAT), net promoter scores (NPS), resolution times, and operational efficiency—and baseline these metrics before AI implementation. Regular measurement and communication of these outcomes build confidence in AI initiatives. TeKnowledge consistently emphasizes measurable impact and continuous improvement through structured adoption and managed services, ensuring tangible results and clear ROI from AI investments.

Pitfall #5: Ignoring Security and Compliance Risks

Common Barrier:
Implementing AI solutions—especially in cloud environments—raises valid concerns around data security, privacy, and compliance (GDPR, HIPAA, PCI, etc.). Many enterprises underestimate the complexity and rigor required to maintain compliance, leading to delays or incomplete implementations.

Best Practice:
From the earliest planning stages, businesses must integrate security and compliance requirements into AI deployments. Choosing an AI solution provider experienced in enterprise-grade cybersecurity—such as our team at TeKnowledge—can significantly mitigate these risks. Ensure thorough security audits, establish robust governance policies, and incorporate compliance checks throughout the AI lifecycle. Doing so ensures your AI-driven customer support aligns with industry standards and provides peace of mind for stakeholders.

Turning Barriers into Bridges with AI

At TeKnowledge, our partnership with Genesys uniquely positions us to help enterprises overcome these common barriers. Our combination of deep operational expertise, comprehensive managed services, and leading-edge AI technology creates an environment where AI adoption is secure, effective, and transformative.

The journey to scaling AI in customer care is complex—but with careful planning, thoughtful integration, proactive workforce engagement, clear metrics for success, and rigorous security practices, organizations can confidently navigate this journey.

By avoiding these pitfalls and adopting these best practices, your organization will not just successfully implement AI—you’ll unlock its full potential, delivering extraordinary customer experiences, empowered employees, measurable business impact, and sustained competitive advantage.