Every week, a new headline promises that artificial intelligence can take over the contact center. Vendors talk about limitless automation. Boards ask why their competitors are moving faster. For customer experience leaders, the harder question isn’t whether automation can be done, but what to automate in CX first.
Opinions differ. A Gartner study found that 64% of customers would rather not deal with AI at all when the issue involves money or mistakes. At the same time, Verint reports that 86% of consumers now see AI as helpful in resolving everyday service problems, especially younger customers.
Obviously, CX automation can deliver incredible results when it’s implemented correctly. But the risks of automating too much too fast are becoming increasingly obvious. Just look at Air Canada, the company that lost a tribunal after its chatbot gave the wrong refund information.
So, how can CX leaders get the balance right?
Further reading:
- How AI Contact Centers Really Work
- What Can AI and Automation Really Do for Your Contact Center?
- How Enterprises Are Already Using AI and Automation in CX
Why is Task Selection So Important in a CX Automation Strategy?
Not every task belongs in the hands of an AI agent. Some are predictable and low-risk; others carry consequences too great to gamble on. The difference is where most automation projects succeed or fail. A useful way to think about it is through an Automation Fit Matrix:
- Low-risk, high-volume tasks: Ideal to automate now - password resets, refunds within policy, and delivery updates.
- Medium-risk, moderate-volume tasks: May be suitable to automate with escalation paths and guardrails. Examples include loyalty program updates or warranty claims.
- High-risk, sensitive tasks: Best left to people. Billing disputes, fraud investigations, or medical queries fall into this category.
What Should Companies Automate First In Customer Experience?
The distinction between what AI could do and what it should do is at the heart of customer trust. The industry is still reckoning with the gap between promise and performance; leaders want AI that works, not just more AI for its own sake. Customers expect AI to be practical, empathetic, and tuned to their situation. To deliver on that, CX automation needs a plan.
In most organizations, that plan begins with modest steps, focusing on safe wins and only widening the scope once confidence has been earned. These are the kinds of areas companies can target as they start their automation journey.
Automating Simple CX Tasks: Refunds, Resets, and Quick Wins
These are the jobs that consume huge amounts of agent time, even though they follow strict rules. Password resets, account unlocks, refunds within policy, and reshipments for lost or damaged items all fall into this category. They’re predictable, policy-driven, and reversible if needed, exactly the type of workflow that makes sense for automated CX.
Automating simple requests not only reduces cost but also clears queues quickly. For example, RCBC Bank partnered with Kore.ai to handle high-volume, rules-based service requests. The result: $22 million in annual savings and more than 600,000 cases deflected in the first year.
In retail and e-commerce, refunds and reshipments work the same way. Customers appreciate instant resolution, while brands benefit from consistent enforcement of policies.
From a contact center operations standpoint, these are also the safest places to test new automation vendors or platforms. Mistakes are easy to correct, and the ROI is visible within weeks. For many leaders, this is the “day one” use case that proves automation can deliver without undermining trust.
CX Self-Service Automation: How AI Handles Common Requests
The second priority is giving customers faster access to information they’d rather not wait on hold to get. A big share of calls are the easy ones: checking where an order is, tracking a delivery, confirming an appointment, or asking about a warranty. None of these usually needs judgment from an agent.
Hand them to automation, and customers get answers right away. Agents then have more time for the unusual cases that actually require their attention. A good example comes from Deutsche Telekom, which deployed Rasa CALM virtual agents to handle common service queries. The system resolved half of all incoming requests autonomously, cutting agent workload by 30%.
This category also includes knowledge base search. When automation can surface the right article or policy instantly, whether for the customer in self-service or for the agent in conversation, resolution times drop sharply. Many contact center leaders now see agent assist and knowledge retrieval as the most practical first steps in CX automation, because the impact appears instantly.
These are simple improvements, but they create a foundation for trust. Once customers experience automation that works reliably, they’re more open to broader adoption later in the journey.
Proactive CX Automation: Using AI to Prevent Customer Issues
One of the most effective uses of CX automation isn’t responding to issues but preventing them from becoming calls in the first place. Proactive notifications, whether it’s a flight delay, a service outage, or a suspicious transaction, reassure customers and cut inbound volume at the same time.
Airlines show the value clearly. Lufthansa uses Cognigy to send delay and rebooking alerts to millions of passengers. The updates go out before people even think of calling, which keeps contact center traffic from spiking and makes a stressful experience a little easier to handle.
This approach works across sectors. In telecom, customers can get instant notifications when outages are detected, along with estimated recovery times. In financial services, proactive fraud alerts build trust while preventing losses.
Learn how smarter automation really cuts costs here.
AI-Powered Agent Assist: Boosting Productivity and Accuracy
Not all automation has to face the customer. Some of the biggest early gains come from tools that support agents behind the scenes. Post-contact summarization, intelligent prompts, and automated quality checks all improve productivity without exposing customers to risk.
Heathrow Airport’s contact center shows how this works in practice. By automating call summaries, agents cut down on repetitive wrap-up work. The system achieved 95% accuracy, saving valuable minutes per interaction while capturing more consistent data. Multiply that across thousands of daily calls, and the efficiency gain is massive.
Agent assist tools are another safe starting point. By surfacing relevant customer history, policy details, or even suggested replies during live conversations, they shorten resolution times and reduce errors. Property platform Yopa implemented intelligent agent assist and saw productivity improve fourfold, giving teams more bandwidth without adding headcount.
Quality assurance can also benefit. Platforms like Scorebuddy are automating compliance checks, ensuring every interaction meets regulatory and service standards. This adds oversight while reducing the manual workload for supervisors.
Are Internal Workflows Safe to Automate in CX?
Automation doesn’t have to stop at the contact center. Some of the quickest wins come from applying the same principles internally. IT and HR functions are full of routine, policy-driven requests that absorb time but add little strategic value.
Inside the business, IT and HR teams deal with the same type of routine work. IT desks spend hours on password resets and access requests. HR staff answer the same questions on benefits, leave, or onboarding. Automating those jobs takes the load off, leaving specialists to work on tougher problems while employees get quicker responses.
By deploying Kore.ai agents across its global HR function, AMD automated thousands of employee queries, cutting wait times and reducing the need for additional headcount. The impact wasn’t just cost savings; it also improved employee experience by giving staff faster, more consistent answers.
