{"id":581158,"date":"2025-07-07T18:11:37","date_gmt":"2025-07-08T01:11:37","guid":{"rendered":"https:\/\/www.genesys.com\/blog\/post\/laying-the-groundwork-for-agentic-ai-in-customer-experience"},"modified":"2025-07-07T18:12:36","modified_gmt":"2025-07-08T01:12:36","slug":"laying-the-groundwork-for-agentic-ai-in-customer-experience","status":"publish","type":"blog","link":"https:\/\/www.genesys.com\/en-sg\/blog\/post\/laying-the-groundwork-for-agentic-ai-in-customer-experience","title":{"rendered":"Laying the Groundwork for Agentic AI in Customer Experience"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>[vc_row][vc_column][vc_column_text css=&#8221;&#8221;]<span style=\"font-weight: 400;\"><a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/the-future-of-cx-how-ai-will-redefine-customer-experiences-in-2025\" target=\"_blank\" rel=\"noopener\">Customer experience (CX) is evolving<\/a> \u2014 driven not just by changing consumer expectations, but by operational limits. Most organisations are facing the same challenge: increasing service complexity without increasing resources. The maths doesn\u2019t work unless something fundamental changes in how work gets done.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Artificial intelligence (AI) is a key part of that shift. But not all AI delivers the same value or operates with the same degree of efficiency. Many existing systems remain tightly scripted, focused on static automation. They reduce manual tasks, but can fall short in dynamic environments.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For businesses looking to scale personalised service without scaling costs at the same rate, a new generation of <a href=\"https:\/\/www.genesys.com\/en-sg\/capabilities\/ai-and-automation\" target=\"_blank\" rel=\"noopener\">AI for CX<\/a> is emerging.<\/span><\/p>\n<p><a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/agentic-ai-the-difference-between-leading-and-lagging-in-cx\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Agentic AI<\/span><\/a><span style=\"font-weight: 400;\"> brings that <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/the-levels-of-experience-orchestration\" target=\"_blank\" rel=\"noopener\">next level of experience<\/a> within reach. It introduces systems that can pursue goals, make decisions in context and adapt to real-world conditions \u2014 all while remaining aligned to business intent. And while true autonomy is still rare in production environments, semi-autonomous use cases can <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/discovering-the-business-value-of-ai-a-new-model-for-growth\" target=\"_blank\" rel=\"noopener\">create measurable CX improvements<\/a>.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To capture that value, organisations need to understand what agentic AI enables, what it requires and how to start building toward it now.<\/span>[\/vc_column_text][vc_row_inner][vc_column_inner][vc_column_text css=&#8221;&#8221;]<\/p>\n<h3><span style=\"font-weight: 400;\">Understanding the Defining Traits of Agentic AI<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">In order for a system to be considered truly agentic AI, it must demonstrate five core traits:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Autonomy:<\/strong> It can act independently, without requiring explicit instructions for every scenario.<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Goal-orientation:<\/strong> It operates with a sense of purpose, pursuing defined outcomes like resolving an issue or completing a transaction.<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Adaptiveness:<\/strong> It adjusts to new information in real time, continuously optimising its responses.<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Memory:<\/strong> It learns from past interactions and applies that knowledge to current ones, maintaining context and continuity.<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Reasoning:<\/strong> It can evaluate options, make decisions and plan next steps in pursuit of its goals \u2014 especially in situations that aren\u2019t predefined.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Together, these capabilities allow AI to move beyond rote automation toward real agency. Where traditional bots rely on decision trees or fixed scripts, agentic systems can reason through problems, identify intent and determine the best next step \u2014 even when the interaction doesn\u2019t follow a predictable path.<br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400;\">However, most real-world applications of agentic AI operate with partial autonomy. A virtual agent might be responsible for resolving a post-purchase issue or diagnosing a mobile app error. It can move flexibly to achieve a defined task, but escalation paths and decision boundaries remain in place to help keep the AI agent in check. This hybrid approach \u2014 structured freedom within safe zones \u2014 enables businesses to realise near-term benefits of agentic AI without overextending their risk tolerance.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Why not let the <a href=\"https:\/\/www.genesys.com\/en-sg\/capabilities\/chatbots\" target=\"_blank\" rel=\"noopener\">virtual agents<\/a> run completely free? Well, granting an AI system full creative autonomy \u2014 even for seemingly simple tasks \u2014 could lead to unintended outcomes.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Consider, for example, a major bank using agentic-AI voicebots to handle customer identity-verification checks. If the correct security word on file is \u201cBoston\u201d but the user says \u201cMassachusetts,\u201d an AI agent might mistakenly judge that as close enough \u2014 potentially allowing a malicious actor access to a customer account. And in case you think that means agentic AI isn\u2019t ready for real-world action, bear in mind that human customer service agents have constraints on their autonomy for the same reasons. Human agents are trained to know a password must match precisely and forbid access if it doesn\u2019t, no matter how \u201cclose enough\u201d (and even charming) a caller might be.<\/span>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner][vc_column_inner][vc_column_text css=&#8221;&#8221;]<\/p>\n<h3><span style=\"font-weight: 400;\">From Scripted Flows to Adaptive Interactions<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Traditional automation in CX was designed around efficiency: Contain simple issues, reduce handle time, deflect volume. But efficiency alone doesn\u2019t scale well when conversations become unpredictable. Customers revise their answers. They change topics. They need clarification or want to go back and update something they said earlier.<br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400;\">These are the moments where rules-based bots typically fail. When the input doesn\u2019t match what was expected, the experience can break down \u2014 and often escalates unnecessarily.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Agentic AI manages these interactions differently. It can take a correction midstream, reorient around the new information in a nonlinear fashion and continue moving toward resolution. This makes interactions more resilient and outcomes more reliable \u2014 without forcing a handoff to a human agent unless it\u2019s truly needed.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Again, this isn\u2019t about giving bots free rein \u2014 or overly restricting them. It\u2019s about enabling the right level of flexibility for the specific task at hand. And understanding that is critical if you hope to use the technology well.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Moving money between accounts or delivering a legal disclaimer may require strict, deterministic flows. But troubleshooting an account lockout or gathering contextual data for a service enquiry may benefit from a more autonomous, open-ended, agentic approach.<\/span>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner][vc_column_inner][vc_column_text css=&#8221;&#8221;]<\/p>\n<h3><span style=\"font-weight: 400;\">Why Agentic AI Is Emerging as a CX Enabler<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Agentic AI brings capabilities that address some of CX\u2019s biggest pain points today.<br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400;\">As service volumes grow and interactions become more fragmented across digital channels, businesses need systems that can adapt without disrupting flow. And agentic AI supports that in several key ways:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">It enables always-on, personalised service that adjusts to context without requiring customers to repeat themselves.<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">It supports proactive engagement, identifying issues or next steps before the customer reaches out.<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">It fosters loyalty and retention, not through scripted empathy, but through intelligent responsiveness.<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">It improves human-agent efficiency, taking on routine or moderately complex interactions so that skilled staff can focus where their capabilities matter most.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">These benefits aren\u2019t just nice to have \u2014 they\u2019re increasingly non-negotiable. Modern<\/span> <a href=\"https:\/\/www.genesys.com\/en-sg\/resources\/practical-guide-to-mastering-journey-management?ost_tool=blog&#038;ost_campaign=0-0-0-0-0-0-0-blog\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">customer journeys<\/span><\/a><span style=\"font-weight: 400;\"> rarely follow a straight line. They unfold across multiple channels, asynchronously across time, with consumer expectations for \u201cchannel-less\u201d continuity at every step. Meeting those demands requires systems that can handle nuance, shift with context and deliver seamless experiences at scale. That\u2019s the real promise of agentic AI.<\/span>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner][vc_column_inner][vc_column_text css=&#8221;&#8221;]<\/p>\n<h3><span style=\"font-weight: 400;\">Preparing the Way for Agentic AI<\/span><\/h3>\n<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/deliver-the-next-level-of-experience-with-genesys-cloud-ai-studio-and-ai-guides\" target=\"_blank\" rel=\"noopener\">Getting agentic AI to work in practice<\/a> isn\u2019t a matter of flipping a switch. It requires foundational shifts in how systems are designed, integrated and governed. Success depends on a connected ecosystem that gives AI the data, structure and oversight it needs to perform reliably and safely.<br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400;\">That starts with a robust data infrastructure. Agentic systems rely on real-time access to interaction history, behavioural signals and operational context. When data is fragmented across systems, the AI\u2019s ability to respond intelligently is compromised. Clean, unified data creates the conditions for continuity, context and relevance.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Equally important is a composable, modular tech stack. Agentic AI must operate across systems \u2014 CRM solutions, billing, scheduling and more \u2014 and adapt as needs evolve. Flexibility in the architecture, including API-first design and workflow orchestration, enables new use cases to emerge without reengineering the entire ecosystem.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Agentic AI also depends on structured, accessible knowledge. Even the most sophisticated systems require a reliable source of truth. A curated, well-maintained knowledge base allows the AI to reason through tasks, maintain consistency and respond with accuracy across scenarios.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">And finally, governance must be embedded \u2014 not added later. <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/navigating-the-new-era-of-security-privacy-and-compliance\" target=\"_blank\" rel=\"noopener\">Security, privacy<\/a>, explainability and compliance need to be designed into the system from the start. Guardrails should define what the AI can and cannot do; when to escalate to a human; and how to align with organisational policies, brand voice and evolving regulations.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Taken together, these capabilities form the foundation for sustainable, scalable AI autonomy \u2014 the kind that can support business outcomes while maintaining trust.<\/span>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner][vc_column_inner][vc_column_text css=&#8221;&#8221;]<\/p>\n<h3><span style=\"font-weight: 400;\">Addressing the Challenges that Come with Autonomy<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Again, the more independent a system becomes, the more critical it is to maintain control. Guardrails aren\u2019t just a technical safeguard; they\u2019re a strategic one.<br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400;\">So, organisations deploying these tools need to define their boundaries: Where is agentic AI appropriate? Where must it defer to a human? How do we monitor its decisions? And how do we explain those decisions \u2014 to users, to regulators and to our own internal stakeholders?<\/span><\/p>\n<p><span style=\"font-weight: 400;\">AI<\/span> <a href=\"https:\/\/www.genesys.com\/en-sg\/definitions\/what-is-a-large-language-model-llm\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">LLM<\/span><\/a><span style=\"font-weight: 400;\"> models\u2019 tendency toward bias, too, remains an ongoing concern. Systems trained on real-world data risk reflecting real-world inequities. Continual testing, feedback processes and human-in-the-loop reviews are required to mitigate unintended consequences.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Integration is another point of potential complexity. Agentic AI can only act meaningfully if it\u2019s connected to the tools and systems that execute work \u2014 billing platforms, CRM systems, scheduling systems, logistics applications, etc. Without this integration, intelligence can stall at the surface level.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">These challenges aren\u2019t reasons to avoid agentic AI. They\u2019re reasons to approach it with an intention to really understand its limits and potential, so you can start benefiting from its power now and grow it over time.<\/span>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner][vc_column_inner][vc_column_text css=&#8221;&#8221;]<\/p>\n<h3><span style=\"font-weight: 400;\">How to Start Adopting Agentic AI Now<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Adopting agentic AI doesn\u2019t require a wholesale transformation. It starts with choosing the right use cases and building momentum through measurable progress. Four steps can help guide the process:<\/span><span style=\"font-weight: 400;\">\u00a0<\/span><\/p>\n<p><strong>1. Assess readiness and clarify goals: <\/strong><span style=\"font-weight: 400;\">Evaluate where your current systems fall short and where AI-driven adaptability could deliver better outcomes. Identify gaps in data access, workflow flexibility or governance.<\/span><span style=\"font-weight: 400;\">\u00a0<\/span><\/p>\n<p><strong>2. Select focused pilot use cases: <\/strong><span style=\"font-weight: 400;\">Choose scenarios that are low-risk but high-value. Examples might include post-purchase engagement, proactive outage communication or using a virtual agent to address non-urgent support issues.<\/span><\/p>\n<p><strong>3. Build feedback loops: <\/strong><span style=\"font-weight: 400;\">Be sure to choose a system that can learn from what happens. Track resolution rates, customer sentiment and any manual overrides or escalations. Use that data to refine the experience<\/span><\/p>\n<p><strong>4. Scale with purpose: <\/strong><span style=\"font-weight: 400;\">Expand where the model proves value. Don\u2019t aim for full autonomy everywhere. Instead, match the degree of agentic functionality to the nature of the task and the stakes involved.<\/span>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner][vc_column_inner][vc_column_text css=&#8221;&#8221;]<\/p>\n<h3><span style=\"font-weight: 400;\">A Measured Path Forward<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Agentic AI is not a single capability or a fixed endpoint; it\u2019s a direction \u2014 a way of designing CX systems to handle more complexity, deliver more value and operate more fluidly across channels and contexts. Getting there isn\u2019t about adopting the latest model. It\u2019s about laying the right groundwork so your AI can make smart decisions safely, consistently and at scale.<br \/>\n<\/span><br \/>\n<span style=\"font-weight: 400;\">That\u2019s why timing matters. The systems being designed now will shape how experience is delivered over the next decade. Starting with focused, responsible deployments will allow organisations like yours to gain advantage early \u2014 while balancing safety, compliance and trust.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">At Genesys, we\u2019re helping organisations build that future on a solid foundation. With orchestration, guardrails and modular design at the core of our platform, our agentic-AI capabilities can evolve with your needs. Whether you\u2019re exploring the concept or already scaling pilot use cases, we\u2019re here to help you move forward with clarity and control.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The shift from automation to agency is underway. Laying the right foundation now means you won\u2019t just keep up \u2014 you can stay ahead.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">See how you can take your customer experience to the next level and build what\u2019s next with<\/span><a href=\"https:\/\/www.genesys.com\/en-sg\/resources\/genesys-cloud-ai-studio-and-genesys-cloud-ai-guides-product-overview?ost_tool=blog&#038;ost_campaign=0-0-0-0-0-0-0-blog\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\"> Genesys Cloud AI Studio and AI Guides<\/span><\/a><span style=\"font-weight: 400;\">.<\/span>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner][vc_column_inner][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column][vc_column_text css=&#8221;&#8221;]Customer experience (CX) is evolving \u2014 driven not just by changing consumer expectations, but by operational limits. Most organisations are facing the same challenge: increasing service complexity without increasing resources. The maths doesn\u2019t work unless something fundamental changes in how work gets done. Artificial intelligence (AI) is a key part of that shift. But [&hellip;]<\/p>\n","protected":false},"author":954,"featured_media":579769,"template":"","tax_priority":[54],"tax_blogtype":[17756],"tax_blogcategory":[15928,18426],"tax_contenttheme":[14904],"tax_bundle":[15268],"tax_contenttheme2":[16139],"tax_capability_sitewide":[16201],"tax_products_programs":[16477,17548],"tax_buying_job":[16651],"tax_buyer_persona":[16887,16919],"tax_sector":[],"tax_segment":[17079,17104,17125],"class_list":["post-581158","blog","type-blog","status-publish","has-post-thumbnail","hentry","tax_priority-54","tax_blogtype-genesys-en-sg","tax_blogcategory-ai-and-machine-learning-en-sg","tax_blogcategory-experience-orchestration-en-sg","tax_contenttheme-level-up-your-technology-en-sg","tax_bundle-genesys-ai-en-sg","tax_contenttheme2-improve-customer-experience-en-sg","tax_capability_sitewide-ai-and-automation-en-sg","tax_products_programs-genesys-ai-en-sg","tax_products_programs-genesys-cloud-cx-en-sg","tax_buying_job-job-2-solution-exploration-en-sg","tax_buyer_persona-business-en-sg","tax_buyer_persona-technical-en-sg","tax_segment-enterprise-en-sg","tax_segment-midsized-en-sg","tax_segment-smb-en-sg","tax_content_type-blog-en-sg"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/blog\/581158","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/blog"}],"about":[{"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/types\/blog"}],"author":[{"embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/users\/954"}],"version-history":[{"count":3,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/blog\/581158\/revisions"}],"predecessor-version":[{"id":581161,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/blog\/581158\/revisions\/581161"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/media\/579769"}],"wp:attachment":[{"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/media?parent=581158"}],"wp:term":[{"taxonomy":"tax_priority","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_priority?post=581158"},{"taxonomy":"tax_blogtype","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_blogtype?post=581158"},{"taxonomy":"tax_blogcategory","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_blogcategory?post=581158"},{"taxonomy":"tax_contenttheme","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_contenttheme?post=581158"},{"taxonomy":"tax_bundle","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_bundle?post=581158"},{"taxonomy":"tax_contenttheme2","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_contenttheme2?post=581158"},{"taxonomy":"tax_capability_sitewide","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_capability_sitewide?post=581158"},{"taxonomy":"tax_products_programs","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_products_programs?post=581158"},{"taxonomy":"tax_buying_job","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_buying_job?post=581158"},{"taxonomy":"tax_buyer_persona","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_buyer_persona?post=581158"},{"taxonomy":"tax_sector","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_sector?post=581158"},{"taxonomy":"tax_segment","embeddable":true,"href":"https:\/\/www.genesys.com\/en-sg\/wp-json\/wp\/v2\/tax_segment?post=581158"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}