AI adoption has influenced how organizations use and measure customer experience technology stacks. As a result, organizations have had to shift from using metrics built for human-only workflows to more hybrid approaches.
Organizations need to work to understand the different parts of the CX ecosystem, including data infrastructures, governance, accessibility and security. They also need to maintain visibility over the AI tools employees are using, whether they are sanctioned or not.
Here are six articles that delve into how AI has impacted modern CX.
The rise of CX observability in service monitoring
AI adoption and cloud migration have increased the complexity of contact center technology stacks. Understanding how different parts of the customer experience ecosystem interact makes managing contact centers and agents easier.
There’s a revolution coming for the modern CX stack
Ensuring effective AI adoption requires effective data infrastructure, which are boosted by modern CX platforms. These platforms allow enterprises to access richer data models, implement data guardrails and governance, and integrate with data fabrics and architectures.
SingleCX channels in one place. Without it, customers can experience issues finding information from services or orders
Why traditional CX metrics fall short with hybrid CX
CX environments were originally built for human agents, but with increased AI adoption, those metrics are becoming outdated. Organizations who see CX success are considering what human-AI environments look like and customer outcomes.
CX teams built AI workflows. Now, leadership is catching up
Employees are using unsanctioned AI tools for repetitive, draining tasks. Leadership needs to standardize AI use to prevent governance and security concerns.
Microsoft’s new AI agents define new CX vision
Microsoft released new CX tools that change traditional systems, so they drive decisions and outcomes.
