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Does more AI always mean a better experience?
Over the past year, automation rates have risen, virtual agents have expanded and real-time assist tools have become standard.
And yet in many organizations, something subtle is happening beneath the surface. Containment improves - but CSAT doesn’t move. Agents override AI suggestions more than expected. This is what we call AI Fatigue.
In 2026, the challenge will not be whether to use AI but how to orchestrate it in a way that sustains trust, performance, and operational clarity.
In this issue, we look at AI Fatigue from three perspectives: what it is, why it matters more in 2026, and how organizations can avoid it.
Enjoy the read,
Prof. Dr. Levent Arslan , SESTEK CEO
“Why does AI struggle to deliver in real operations?"
AI Fatigue isn’t about too much technology- it’s about poorly orchestrated AI interactions.
We see it in:
Instead of simplifying experiences and delivering convenience, AI begins to introduce friction and frustration.
Trust erodes, experience plateaus, and adoption slows — despite increased investment. The problem is rarely the technology; it’s the absence of intentional design around how that technology is experienced.
👉 Request a Strategic AI Roadmap Session with SESTEK
By 2026, AI will be embedded in most interactions. Three forces are making quality the defining battleground.
• Customer expectations have evolved beyond speed: Interactions now have to be relevant, empathetic, and oriented around real outcomes. AI that answers quickly but misses the point is more frustrating than a slower human who gets it right.
• Employees are navigating growing complexity: Agents supervise, correct, and collaborate with multiple AI systems, often without a unified experience layer. Tools designed to reduce cognitive load can increase it.
• Differentiation is shifting from volume to quality: As AI becomes standard, competitive advantage will come from experience quality. Without a clear experience strategy, AI can quickly shift from a value creator to background noise.
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Preventing AI Fatigue is not about reducing AI. It’s about designing AI experiences with intention. Each principle below includes reflective questions to help surface where fatigue may already be taking hold.
Every interaction should start with a clear purpose: What should this actually resolve?
Some moments require efficiency, others require empathy, clarity, or a smooth transition to a human. Designing backward from the desired outcome — rather than forward from the available technology - is what separates AI that helps from AI that frustrates.
Ask your team:
► What was the customer trying to achieve - and did our AI help them get there?
► Did the automation create more steps, not fewer, in the customer journey?
► When did you last override the AI’s suggestion, and why?
AI should simplify the agent’s experience with real-time guidance, contextual insights, and seamless handoffs. The measure of good collaboration is not how often AI steps in, but how well-prepared agents are when it does.
Ask your team:
► Does the AI give you full context before a call?
► Which AI prompts or alerts do you find yourself ignoring - and why?
► When the AI hands off to you, do you feel set up to succeed?
Customers expect AI to remember and adapt. Consistent context across voice and digital channels is no longer optional - it’s the foundation of effortless experiences. When customers repeat themselves after switching channels, trust erodes. Continuity is the new courtesy.
Ask your team:
► How often do customers repeat information already provided to the virtual agent?
► Can you see the customer’s full interaction history before picking up?
► Does the AI treat each customer as an individual, or apply the same script to everyone?
Containment or deflection measure AI activity, not AI value. Track resolution quality, customer effort, trust and sentiment shifts, and agent experience.
Ask your team:
► After a resolved call, was the customer satisfied?
► Is there a metric you’re measured on that doesn’t reflect the quality of your work?
► What would improve your experience with AI tools better than what no dashboard currently captures?
Agentic AI - autonomous agents that can plan, reason, and take independent action – is increasingly part of real business conversations.
The opportunity is significant. Agentic AI has the potential to streamline operations, automate complex multi-step workflows, and elevate experiences. However, the gap between what Agentic AI can do and what organizations are ready to absorb remains substantial.
Governance frameworks, workflow design, change management, and employee readiness are evolving more slowly than the technology itself. Bridging this gap is not a technology problem; it is a design and orchestration challenge. – Tülin Ebcioğlu, SESTEK Professional Services Manager
Questions worth asking before scaling agentic AI:
QNB Türkiye moved from sample-based quality evaluation to comprehensive, real-time insight across all collection calls and unlocked measurable gains in both efficiency and quality coverage:
Fibabanka moved to handle a significant share of collection calls autonomously, resulting in:
Both engagements share a common design principle: AI deployed to resolve, not merely to deflect.
According to Gartner’s 2025 Customer Experience Report, CX leaders now rank effort reduction and interaction relevance above speed as the primary drivers of customer loyalty. As AI adoption grows, the organizations that win will be those that minimize friction — not those that maximize automation.
As technology accelerates, customer expectations rise - time becomes the most constrained resource in customer experience.
In our next issue, we’ll choose the topic based on your votes in our LinkedIn poll.
Follow SESTEK on LinkedIn and cast your vote to help shape the next issue.
See you next month! 👋
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