It probably comes as no surprise that a recent study by PwC revealed that more than 60% of employees say they experienced more changes at work in the last year than the one prior. And now the rise of agentic AI is ushering in yet another wave of change for CX teams.
Unlike first-generation AI, agentic AI holds the potential to revolutionize the customer experience, enhancing agent efficiency, building customer trust and loyalty, and driving critical business outcomes. However, along with the promise of groundbreaking improvements in customer experience, integrating agentic AI into CX also presents significant change management challenges.
Whether you’re looking to upgrade an existing chatbot solution or implement an AI agent for the first time, adoption isn’t just about technology. It’s about people. The success of any agentic AI initiative depends on CX leaders’ ability to help their teams and all other stakeholders understand what’s at stake, why they should care, and what they can expect — both good and bad.
This guide explores common AI change management challenges and best practices to help set everyone in your CX organization up for agentic AI success. But first…
What is AI change management?
AI change management is the structured process of integrating AI-driven solutions into business operations while ensuring employees, customers, and other stakeholders are aligned and supported throughout the transition.
The goal? Minimize disruption while maximizing value.
Prioritizing people-related AI change management prior to choosing a vendor makes every other step of the AI change management process significantly less stressful (and more successful). Organizations can strengthen customer trust, upskill their workforce, and innovate more quickly than their competitors — all without disrupting stakeholder morale, satisfaction, or alignment.
Why AI change management is critical for business success
It’s been reported that as many as 80% of companies worldwide now use AI-powered chat on their websites. However, the majority of these instances are “chatbots” that leverage first-generation AI, rather than AI agents that harness the latest large language models (LLMs) and generative AI (GenAI) capabilities to give AI agency — AKA agentic AI.
Here at Quiq, we define agentic AI as a type of AI designed to exhibit autonomous reasoning, proactive and goal-directed behavior, and a sense of self or agency, rather than simply following pre-programmed instructions or reacting to external stimuli. Agentic AI systems can interact with humans in a way that is similar to human-human interaction, such as through natural language processing (NLP) or other forms of communication.
Agentic AI clearly represents a major opportunity for CX leaders to finally deliver unprecedented customer experiences that previous generations of AI have been promising to power for years — one that improves agent productivity, enriches customer relationships, and delivers real results.
But implementing agentic AI without proper preparation can quickly lead to bottlenecks, resistance, and, ultimately, failure. Poor planning and misaligned strategies can lead to process disruption, human agent churn, broken customer trust, and negative ROI. In contrast, structured AI change management ensures smoother transitions. It anticipates risks, proactively addresses employee concerns about AI’s impact on their roles, and establishes clear expectations and goals.
The impact of agentic AI on business and the workforce
The role of AI in CX transformation
There are myriad ways to apply AI across the customer journey. For example, AI agents offer 24/7/365 multilingual support. This improves performance metrics and customer satisfaction while showcasing commitment to delivering personalized experiences — something that AI agents can provide by drawing on customer data from various enterprise systems.
GenAI can also automate content generation, saving time by crafting product information, summaries, and even articles. This not only reduces workloads, but also allows customer service teams to tackle more complex or sensitive tasks.
Successful AI change management in action
An established furniture brand was grappling with customer experience friction and missed sales opportunities in a fiercely competitive industry. To curb these challenges, the company partnered with Quiq to introduce a custom AI agent capable of transforming customer interactions across platforms. The successful implementation and integration of this AI agent enabled the company to drastically reduce customer support escalations to human agents by 33%. It also facilitated proactive customer engagement, leveraging a product recommendation engine that contributed to the largest sales day in the company’s history.
Similarly, a leading national office supply retailer utilized Quiq to build an AI-driven assistant for store associates in just 6 weeks. The ability to rapidly generate accurate information to help answer in-store customer queries has increased associate efficiency by 35%. The AI initiative simplified the store associate’s experience, streamlined access to information, improved customer service efficiency, and significantly boosted job satisfaction and productivity. Results include a self-service resolution rate of 68% and an associate AI satisfaction rating of 4.82 out of 5!
Roles usually involved in AI change management
Successfully integrating agentic AI into your customer experience requires AI change management across a number of key stakeholders, including:
- Service and support agents: Your frontline service agents are the backbone of your CX strategy — and often the group most concerned about AI integration. Their core question? “Will this replace me?”
- Marketers: Marketing teams are the storytellers of your brand. They are concerned about creating a singular brand voice and crafting messages that resonate with your audience at every touch point — especially touch points involving AI.
- Sales representatives: Sales professionals rely on meaningful connections with prospects and customers. Their personal approach has always been a differentiator — which means change invites skepticism.
- IT: From ensuring data privacy and security to integrating enterprise-grade solutions, IT must handle the back-end complexity of AI platforms. They’ll want assurance of reliability and room to customize configurations for ongoing scalability.
- Executives: C-suite leaders are key decision-makers driving AI adoption from the top down. They see the bigger picture, but often want to know one thing upfront: “What’s the ROI?”
Common objections and challenges in AI change management
CX leaders encounter a number of challenges and objections when it comes to integrating and adopting agentic AI. Some of the most common that require immediate change management include:
“AI will take jobs away from human agents!”
The fear that AI will replace human agents is one of the most significant barriers to adoption. Employees may worry about their livelihoods, viewing AI as a competitor or threat, rather than a partner or resource.
“AI can’t deliver great customer service…”
Skepticism around AI often stems from previous experiences with underwhelming chatbots. Customers and team members alike may wonder if AI agents have the intelligence and nuance to handle real-world customer concerns.
“What about data privacy and security?”
AI systems require large volumes of data to function effectively, which can raise concerns about privacy, security, and compliance. Some teams may even push for custom solutions built in-house to maintain control.
“What if it damages our brand’s reputation?”
The potential for AI-related issues — misunderstood responses, hallucinations, or off-brand messaging — can trigger anxiety among stakeholders tasked with protecting the company’s public image and perception.
“AI will solve all our problems instantly!”
On the flip side, some stakeholders might naively believe AI to be a magic wand that will instantly resolve all inefficiencies and elevate CX metrics overnight. This unrealistic expectation can lead to disappointment when results are not immediate.
Best practices for AI change management
AI change management isn’t just about removing barriers — it’s about creating advocates. By understanding stakeholders’ concerns and aligning solutions with their priorities, you can demystify AI and build trust in its transformational potential.
AI isn’t a standalone fix; it’s part of a collaborative vision. Focus on education, transparency, and actionable results to align teams and embed confidence in AI’s role. Ultimately, a well-managed transition will enrich not just your CX strategy — but the experience of everyone involved.
Here are a few key best practices for getting folks on board before taking the plunge:
Highlight AI’s role in upskilling human agents
Your team needs clarity on how AI will enhance their roles, not erase them. AI is exceptionally good at automating repetitive, low-value tasks like data entry or providing scripted customer responses. AI also presents agents an opportunity to grow and develop new skills, like interpreting AI insights or managing tech-enabled workflows.
Plus, AI can make those same agents significantly more productive. How? With the automation of simple, routine tasks, combined with AI assistants helping your agents respond faster and more accurately to higher-value conversations.
Engage skeptics in the vendor selection process
Even within forward-thinking teams, some employees will approach AI with hesitation — or outright skepticism. Their reservations often stem from perceptions of over-hyped technology or negative past experiences (hello, ineffective chatbots). Turn skeptics into allies by giving them a seat at the table. Specifically, involve them in identifying and evaluating AI for CX use cases and solutions. This inclusion doesn’t just smooth over resistance, it also helps teams get excited about potential solutions.
Explore “buy-to-build” agentic AI solutions
If technical stakeholders show resistance to off-the-shelf platforms, offer a middle ground. Buy-to-build platforms offer technical teams the flexibility, visibility, and control they crave to build secure, custom experiences that satisfy business needs. At the same time, they save time, money, and resources by handling the maintenance, scalability, and ecosystem required for CX leaders to deliver impactful AI-powered customer interactions.
Invite brand experts to help build and test
Help teams understand that, contrary to popular belief, hallucinations are preventable using a combination of the latest AI technology, retrieval augmented generation (RAG), and sophisticated business logic that runs pre- and post-response generation checks. Then, involve them in the knowledge preparation and testing processes to reassure them that the AI agent is responding to customers in your unique brand voice.
Establish clearly defined objectives and KPIs
AI projects succeed (or fail) based on realistic and measurable outcomes. Clear, incremental goals ensure alignment at every level of the organization and prevent optimistic executives from expecting too much, too soon. Define objectives and KPIs, such as increased first-contact resolution (FCR) rates, improved CSAT or lower customer effort score (CES), that align with broader business goals, and establish timelines that make sense for hitting each one.
Trends in AI change management: Using AI to streamline adoption
Interestingly, AI itself can accelerate change management initiatives in several key ways. AI proves instrumental in making data-driven decisions that propel positive change, like analyzing in-depth employee surveys to identify patterns and trends that can then be proactively addressed. This allows businesses to effectively gauge employee sentiment toward change, helping to drive strategies that are tailored, engaging, and transformative.
AI platforms can sync various communication channels, automate reminders, and even draft communications based on contextual understanding. This creates a more open, transparent, and inclusive environment for all employees, making organizational change more scalable and effective. It also helps bridge any potential communication gaps, ensuring that stakeholders at all levels are aligned with the strategic vision and the change management process.
Preparing for AI-driven change
As Founder & Principal Analyst of esteemed customer experience research and advisory firm Metric Sherpa, Justin Robbins, recently said, “While AI adoption is surging, only a fraction of organizations report tangible success. Why? It’s not because the technology doesn’t work. It’s because too many organizations approach it with unrealistic expectations, incomplete strategies, or resistance rooted in fear.”
These are all issues that must be addressed before signing on the dotted line. Nobody said it was easy — we humans are complex creatures notoriously opposed to change. But there’s more that unites us than divides us, as the saying goes, which is why we were able to successfully classify your change-resistant colleagues into seven common personas.
