Roy Atkinson
CEO, Writer, Industry Analyst & MentorBridging AI, Customer Experience, and Employee Engagement
With AI, every contact can be scored against the organization’s QA criteria, thus elevating overall quality and helping to ensure a consistent customer experience.
We recently connected with Roy Atkinson, a familiar and trusted voice in the world of customer service and support to explore the evolving relationship between AI, customer experience (CX), and employee experience (EX).
With his deep understanding of how people, processes, and technology intersect, Roy brings thoughtful perspective to some of the most pressing questions in the support space today.
Our conversation circled around a shared interest: How can AI support—not replace—the humans at the center of customer interactions? And what does it mean to create experiences that feel both efficient and empathetic?
Roy walked us through a range of ideas, from how AI can help reduce repetitive tasks for support teams, to how it can elevate consistency, accuracy, and even morale. These themes resonated with us at SearchUnify, especially as we continue to build solutions that put people and knowledge at the core of AI-powered support.
His responses are thoughtful and real. And alongside them, we’ve added a few notes from our side—small reflections on how we see these insights come to life through our work.
Let’s get into it.
Q & A
In your article "Good EX Leads to Good CX: Employees Think So Too," you discuss the correlation between employee and customer experiences. How can AI tools be leveraged to enhance employee satisfaction and productivity, thereby positively influencing customer interactions?
Roy’s Answer
There are many ways AI can work to assist employees. For example:
1) In a contact center, AI’s summarization capability saves agents time and effort during every interaction, increasing productivity. Instead of having agents spend 3-5 minutes after every contact adding notes to a customer record, an AI- powered system can automatically produce better notes; this not only makes work better for that individual agent but for other agents who may later be looking for knowledge about solutions. Case notes are more uniform and complete, improving the knowledge base for all.
2) AI-powered “agent assistance” capability can provide input to keep an agent on track when a customer is upset, help find detailed answers to product questions, observe compliance regulations, and remind agents about special offers or rewards available to the customer.
3) With AI-powered chatbots available to handle routine customer interactions, tedious and repetitive work can be reduced, improving employee morale.
4) Without AI, only a small portion of contacts are measured for quality assurance. With AI, every contact can be scored against the organization’s QA criteria, thus elevating overall quality and helping to ensure a consistent customer experience.
SearchUnify Lens
We’ve seen firsthand how auto-summarization and contextual agent assistance can reduce post-call work and knowledge search fatigue. Solutions like Agent Helper & Knowbler do exactly what Roy highlights—turning every agent interaction into a reusable, high-quality knowledge asset while keeping agents focused on what matters most: the customer.
As AI becomes more integrated into customer interactions, what ethical considerations should organizations keep in mind to ensure transparency, fairness, and trustworthiness in their AI-driven initiatives?
Roy’s Answer
We should always remember that AI runs on data. As we have seen over the last couple of years, people and organizations are rightly concerned about data “leakage,” that is, the unintentional sharing of data that is then absorbed into the large language model (LLM) that underlies the AI and might be reshared. It is important, then, for organizations to obtain explicit consent for the collection and use of customer data and to use proper data security measures like encryption to safeguard the data both at rest and in transit.
In all cases, there should be human oversight to ensure that empathy and other human qualities are included in responses and actions affecting customers. Technology has a role to play here as well; the use of bias detection tools should also be part of any AI- powered system. Customers should be aware of when they are dealing with AI, and should be given the alternative of opting out of the interaction if they have concerns. Transparency matters.
SearchUnify Lens
Roy’s emphasis on transparency and consent is spot-on. SearchUnify’s Cognitive Search platform is designed with robust security measures, including encryption and access controls, ensuring that customer data is handled responsibly. Moreover, our solutions prioritize transparency, clearly indicating AI-generated responses and allowing seamless escalation to human agents when preferred.
The best customer experiences often feel effortless and invisible—users don’t even realize AI is at work. But as AI takes over more interactions, do you think there’s a risk of over-automation that alienates customers rather than engaging them? How should businesses design AI experiences that feel natural, not mechanical?
Roy’s Answer
For years, we have known that customers don’t like waiting on hold and don’t like repeating the same information. AI properly applied is being used to expedite contacts—reducing wait time—and provide transcripts of previous conversations and interactions to agents, reducing or eliminating the need to answer questions and repeat information. The right technology correctly used can help create seamless and effortless experiences for customers. It’s important for organizations to keep interactions human and intuitive through vigorous user acceptance testing and continual improvement.
SearchUnify Lens
Roy’s insights resonate with our approach to AI integration. SearchUnify’s Virtual Assistant (SUVA) is engineered to handle routine inquiries, allowing human agents to focus on complex issues. SUVA ensures that interactions remain fluid and human-like by leveraging advanced natural language processing and continuous learning, thereby enhancing customer engagement without the pitfalls of over-automation.
AI enables unprecedented levels of personalization in customer engagement. How can companies navigate the fine line between offering personalized experiences and respecting customer privacy, especially in light of evolving data protection regulations?
Roy’s Answer
Personalization can only come from customer data. In a 2023 study, Salesforce found that 92% of customers are more likely to trust companies that clearly explain how their data is used. Transparency, then, is key to building customer trust. Over time, an organization’s adherence to the principles of data regulation will increase or erode that trust. Safeguarding customers’ data should go beyond compliance; it should be a cornerstone of any customer experience efforts. Lack of trust will lessen the chances of customer retention. Beyond that, any misuse or mishandling of customer data could expose the organization to legal consequences. Neither customer churn nor compliance issues are desired outcomes, so efforts to protect and secure customer data must be taken. If organizations focus on doing right by the customer and use data for the stated purposes, they will be better off in every respect.
SearchUnify Lens
Roy emphasizes the necessity of transparency in data usage for personalization. At SearchUnify, our SearchUnifyGPT™ solution leverages generative AI to provide personalized, contextually relevant answers while strictly adhering to data protection regulations. We ensure that data usage policies are clearly communicated to users, fostering trust and compliance.
Traditional knowledge bases often become outdated, requiring constant manual updates. But what if AI could automatically refine, update, and even generate new knowledge based on real-time customer interactions and issue resolutions? Do you see a future where AI-driven knowledge bases become self-learning ecosystems that evolve alongside customer needs?
Roy’s Answer
Building and maintaining knowledge bases is certainly one of the capabilities of Generative AI. Summaries of customer interactions can be accurately captured in a desired format and quickly added to a knowledge base. Gen AI can also distill long, tedious documentation down to consumable bits so that agents and customers can get the information they need in a form they can understand.
The biggest issue with having a good knowledge base is maintenance. Finding and replacing obsolete or unused knowledge articles has always been time-consuming. AI can comb through the knowledge base at lightning speed and identify articles that no longer apply or that need revision.
When the effort of building and maintaining the knowledge base is reduced, it’s far more likely that it will be used by humans. It will also be more accurate when used by AI.
SearchUnify Lens
Roy hits on a core challenge we’ve long focused on at SearchUnify: keeping knowledge fresh, relevant, and effortlessly usable.
That’s exactly why we built Knowbler—an AI-powered knowledge creation and curation engine designed to do more than just manage articles. It listens, learns, and evolves in sync with your support ecosystem. By transforming resolved cases into structured knowledge, auto-flagging outdated content, and surfacing high-impact insights, Knowbler helps your knowledge base stay alive and aligned with real-time customer needs.
Looking Ahead: Bridging the Gaps, Thoughtfully
Our conversation with Roy Atkinson brought us back to the heart of what matters in support today: how AI can serve as the connective tissue between employee engagement and customer experience. When agents feel supported—with the right tools, timely information, and fewer repetitive tasks—they’re able to show up fully for customers. And when customers feel understood and taken care of, loyalty and satisfaction naturally follow. AI plays a key role in making this connection more seamless, but only when it’s designed with empathy, transparency, and intention. At SearchUnify, this belief guides everything we do. Whether it’s using Knowbler to turn interactions into knowledge, or enabling intelligent handoffs with SUVA, we’re building toward a future where AI helps bridge—not widen—the gap between great EX and great CX. Big thanks to Roy for joining this conversation and helping shape this perspective. If you’re thinking about how AI can help you create more connected, human-centered experiences, we’d love to continue the dialogue. Let’s keep building smarter support—together.
