As artificial intelligence (AI) moves deeper into contact center operations, leaders face a difficult balancing act. On one hand, AI tools have begun to have an impact on agent efficiency, response times, and service consistency. On the other, an uncertain regulatory landscape is making it harder to confidently deploy AI solutions, especially when critical metrics like customer experience, employee trust, and brand reputation are on the line.
Opportunities presented by AI are real, but so are risks. At this moment, the decisions contact center leaders make about AI implementation, in the context of whatever regulatory framework is eventually put in place, will shape operational efficiency and long-term business resilience.
Customer service is one of the last frontiers of enterprise innovation. That's not because it lacks importance. On the contrary, it's because the stakes are so high. Contact centers deal with sensitive personal data, and agents handle high-stress conversations and operate under intense scrutiny. The wrong AI deployment could do more than just frustrate a customer; it could violate a regulation, spark a lawsuit, or even go viral for all the wrong reasons.
In many ways, the regulatory landscape hasn't caught up to the technology. Federal policy on AI in the United States is still unsettled. Meanwhile, states have started writing their own AI rules. California and other states are leading the charge, each with slightly different expectations around data protection, fairness, and transparency. For businesses operating across state lines, this creates confusion and also increases the likelihood of costly mistakes.
From a leadership perspective, this ambiguity is stressful. Some customer service leaders have trialed several agent-facing AI tools without success, mostly due to poorly managed data or incomplete knowledge bases. In some cases, these leaders weren't even sure what constituted AI under their legal obligations. What's needed now isn't fear or avoidance; it's structure.
Too often, compliance efforts are treated as behind-the-scenes functions managed by a small internal team or a third-party vendor. That can't be the case with AI. These tools touch the core of the customer experience and the employee experience.
Lack of clarity breeds suspicion. To build confidence and minimize the fear that often grows out of uncertainty, leaders must prioritize transparent communication. Employees need to understand exactly how AI tools are being used, where they fit into daily workflows, and what guardrails exist to protect their roles. Open conversations about what AI isand what it is notcan go a long way toward de-escalating internal tension.
Externally, customers also deserve to know how AI is being incorporated into the operations of the organizations with which they deal. If AI is routing their calls, handling their queries, or assessing their sentiment, they should be informed. Contact center leaders have a responsibility to communicate honestly about AI's role in service delivery. When done right, this transparency strengthens the customer relationship and builds trust in the brand.
Operational Agility Matters
The quick pace of regulatory and technological change means that rigid, top-down implementations won&'t work. To navigate this environment, customer service centers must prioritize agility and ensure their ability to pivot quickly, adopt best practices from adjacent industries, and course-correct when something doesn't go as planned.
That means avoiding two common traps. First, don't wait for perfection before acting. Of course, data needs to be structured and clean, but analysis paralysis will stall innovation. Second, don't rush forward without a governance framework. An act-first-and-beg-forgiveness-later- strategy might buy short-term wins, but it could also expose the business to brand damage and legal risk.
Agility, in this context, means piloting tools with clear success criteria. It means having escalation paths to solve problems when AI gets something wrong. And it means recognizing that even with compliance measures in place, reputational risk will never disappear completely. The contact center is a high-touch environment. Trust must be earned and protected every day.
Just like traffic lanes and stoplights, regulation gives us the structure to move faster, not slower. But that only works when everyone understands the rules and agrees to follow them.
To execute a balanced AI strategy, companies must empower teams charged with incorporating AI into their technology environments. AI governance will be full-time work, but the people responsible for AI implementation will typically already have full-time jobs within the company. Larger organizations will need to create new positions, such as chief data officers or chief information security officers, to manage the transition. Mid-sized organizations will also need dedicated staff focused solely on AI readiness. That person or team should be responsible for the following:
- Monitoring new and pending legislation;
- Vetting vendors and their claims;
- Overseeing data quality and AI model performance;
- Communicating changes to executive and frontline teams; and
- Responding quickly when something breaks.
And most importantly, leaders need training. It's not enough to understand the technology; they must also be able to explain it in plain language to agents, managers, customers, and regulators. As AI continues to evolve, this bridge between technical execution and business communication will only grow in importance.
There's no question that AI will continue to shape the future of customer service. The bigger question is whether customer service leaders will be able to harness its potential responsibly and sustainably.
That requires structure. It requires communication. It requires internal accountability and external transparency. And perhaps most of all, it requires humility. We're all still learning what AI can and can't do. Mistakes will happen. But if we stay grounded in empathy, honesty, and operational flexibility, we'll be able to avoid most of the pitfalls and lead our organizations into a smarter, stronger, and more human-centered future.
At a time when customer trust is as valuable as operational efficiency, AI is not just a technology decision, it's also a leadership decision.
Jennifer Lee has 20 years experience in the contact center industry, with more than 15 years as a people leader. Throughout her career, she has served in a variety of roles in the contact center space, including operations, quality, workforce management, and client services. Prior to becoming president and co-CEO at Intradiem, she served as chief operating officer, chief strategy officer, and head of the Customer Success organization.