How have customer experiences evolved?

For years, automated or interactive voice systems have set the bar painfully low, and as a result, customers have been conditioned to expect very little from these interactions. Just take any interaction with a call center; long hold times, clunky IVRs, and endlessly being passed from pillar to post have trained many of us to simply give up before we even get started. 

But that’s changing fast. AI is now the dominant force in tech, and service operations are one of its hottest use cases. The newest chapter is “agentic AI” – intelligent systems that don’t just answer questions but pursue goals and get work done.

Customer-first cultures are in decline by 11.1% in 2025; only 31.7% of organizations prioritize the customer at the center of decision-making. As more companies become sales-led, customer frustration risks increasing, unless diffused by new technologies. 

What is agentic AI? 

Agentic AI is artificial intelligence that can infer goals, plan tasks, and take autonomous action. It doesn’t just respond to prompts or analyze data, but rather, it connects actions across systems to achieve outcomes on behalf of users. 

That’s what sets it apart from earlier AI approaches — and it’s why enterprise demand is accelerating fast. 

In fact, Juniper Research projects that global revenue from conversational AI will rise from $14.6 billion in 2025 to over $23 billion by 2027, fueled largely by agentic AI's ability to automate tasks and reduce reliance on human labor.

Here’s what the tech giants at IBM define it as: 

“Agentic AI takes autonomous capabilities to the next level by using a digital ecosystem of large language models (LLMs), machine learning (ML), and natural language processing (NLP) to perform autonomous tasks on behalf of the user or another system.”

Cisco breaks this down into three essential capabilities: memory, task-awareness, and independent action. These allow an agent to actively "choose what actions to take to achieve an outcome" rather than simply responding to whatever prompt it receives.

The State of Customer Success Report reveals that 70.7% of Customer Success Managers (CSMs) manage more than 10 accounts 1:1, and only 15.9% use automated adoption nudges. It’s clear that traditional methods simply can’t scale. Agentic AI closes this gap by autonomously executing repetitive tasks, not just suggesting next steps, but taking them.

To understand why this technology is so transformative, it's important to clarify how agentic AI differs from the generative AI systems most people are familiar with.

Agentic AI vs. generative AI

So, while generative AI creates new content like text or images, agentic AI is action-oriented. 

That said, AI doesn’t “understand” things like humans do. Instead, it learns from patterns, pulling value from columns in data and surfacing insights based on frequency, sentiment, or severity. But in high-volume, repetitive environments like contact centers, that’s exactly what’s needed.

Here's how this can play out in practice: Let’s say a customer calls in with a complaint regarding a bill discrepancy. A more traditional system would route the call, put them on hold, and eventually connect them to a customer support manager who would need to investigate the issue manually. 

Agentic AI recognizes the common billing problem from the off, validates their account details, initiates a refund, and emails confirmation – all well before the customer finishes explaining the issue.

This action-oriented capability translates into three fundamental ways that agentic AI is reshaping every touchpoint of the customer experience.

How are AI-powered agents transforming the customer journey?

The technological leap that is agentic AI is reshaping the entire customer journey in three key ways, each building on the foundation of the previous advancement.

24/7 availability

Sure, there are pros and cons of AI, like there are with human-led customer service, but one of the most – if not the most – attractive reasons for AI is this: voice agents never sleep. Whether 1,000 or 10,000 customers call at once, an AI can be like a concierge, greeting every single one instantly. This is an absolute lifesaver for companies during peak season or system outages.

But availability alone isn't enough if the experience remains frustrating. That's where the next advancement becomes crucial.

Seamless, natural conversations

It’s time to say goodbye to stilted, artificial-sounding voices and say “hello” to regional accents, natural pacing, and lightning-fast understanding that creates a “Wait… that was a bot?” moment. 

We’ll admit, it initially does feel a little dystopian to think there’s no telling between a human voice and an artificial one. However, the benefits are undeniable: more personalized customer care and better, more tailored experiences for each individual caller. Plus, it’s what customers expect, as according to Zendesk, “56% of customers believe bots will be able to have natural conversations by 2026.

While 65.9% of CS teams still rely on human-led check-ins for adoption, agentic AI offers an upgrade, instantly delivering intelligent follow-ups, nudges, or resources based on customer behavior, without waiting for a CSM to manually intervene.

Pro tip: Should customers ask, be up-front that your support agent is an automated assistant, but don’t make a meal out of it. The smoother the reveal, the higher the adoption. 

Once customers are comfortable conversing naturally with AI, the next breakthrough becomes connecting those conversations across every channel they use.

Seamless, omnichannel experiences

Don't think for a second that tomorrow's customer experiences will stop at voice interactions. Text, images, and interactive content will flow together seamlessly, allowing customers to start on a phone call, continue via chat, and finish in a visual portal – all guided by the same AI that maintains context throughout the entire journey.

This integrated approach transforms fragmented customer service into a cohesive experience that follows customers wherever they prefer to engage.

Key benefits for CX and operational excellence

These technological improvements translate directly into measurable business outcomes that touch every aspect of customer service operations.

Enhanced customer experience

The customer-facing benefits of agentic AI are immediately apparent. Wait times can drop from an average of seven minutes to thirty seconds. First-contact resolution rates soar as AI systems can solve problems on the first try rather than requiring multiple transfers. Every caller receives "white glove" personalization, feeling like they have a private concierge dedicated to their needs.

And perhaps most importantly, these improvements happen fast enough to create pretty rapid loyalty gains. Economics academics Erik Brynjolfsson, Danielle Li and Lindsey Raymond show AI assistance brought about a 15% increase in issues resolved per hour across 5,172 agents.

All it takes is one single great interaction between an AI agent, and bam! You’ve flipped your brand perception overnight, turning frustrated customers into brand advocates. 

But a word of caution: While customers experience these improvements at the front end, the behind-the-scenes operational impact is equally transformative.

Operational excellence that scales

Behind the scenes, the operational benefits of it are equally compelling. Agentic AI serves as a crucial buffer against labor shortages, filling gaps when hiring lags behind demand. Companies using platforms have automated up to 90% of routine calls, freeing human agents to focus on complex, high-value interactions.

Most significantly, customer support and success transform from a cost center into a command center. 

Real-time insights come to business leaders’ attention immediately instead of vanishing into call logs that nobody bothers to review. This operational transformation creates the foundation for an even more strategic shift: reimagining the role of human agents.

In 2025, 35.4% of CS teams saw budget cuts, and 53% operated with fewer than five people. Agentic AI is uniquely positioned to address this crunch: it scales support without scaling headcount, helping overstretched teams deliver enterprise-grade service with start-up-sized resources. 

As AI takes over routine tasks and delivers these operational efficiencies, it fundamentally changes what human agents can accomplish."

The evolution of human customer experience agents

When AI handles routine inquiries and basic problem-solving, human agents don't become obsolete – they level up. They transform into knowledge workers who supervise AI decisions, tackle complex cases, and feed frontline insights back to the business. Job satisfaction increases because the work becomes genuinely interesting and strategic rather than repetitive and draining.

This evolution requires a thoughtful talent strategy. Organizations need to reskill teams in AI literacy, create new roles like conversation designers, and treat AI not as a replacement tool but as a collaborator that thinks and optimizes in real time.

The most successful companies are already making this transition, but getting there requires overcoming several predictable challenges. 

Overcoming adoption hurdles with strategic rollouts

Smart implementation follows a proven playbook: start small, learn fast, think big. Run a limited pilot program, prove measurable value within weeks, then scale systematically across the organization.

Success requires making AI adoption a joint mission. CX leaders frame the customer experience problems that need solving, while CIOs ensure the technology integrates safely and securely with existing systems. Focus relentlessly on outcomes rather than chasing AI for hype's sake – pursue measurable wins like improved first-call resolution rates or higher NPS.

For most organizations, the smartest approach is to buy before you build. Unless AI is your core business, partner with specialists who have already solved the hard problems and can help you iterate quickly.

Address customer skepticism head-on with friction-free first impressions and clean fallbacks to human agents when needed. Tackle integration challenges early by unifying data sources, capturing institutional knowledge, and building security into the system architecture from day one.

These foundational steps prepare organizations for the ultimate vision of agentic AI.

Personal AI concierges for every customer

The trajectory of agentic AI points toward something remarkable: every customer accompanied by a personal AI that knows their complete history, anticipates their needs, and coordinates seamlessly across sales, service, and marketing touchpoints.

Imagine calling for support and having the AI already know about your recent purchase, understand your usage patterns, and proactively suggest solutions before you finish describing the problem. Picture that same AI coordinating with marketing to ensure you receive relevant offers and with sales to identify upsell opportunities that genuinely benefit you.

That's where agentic AI is heading, and the pace of innovation means you're either leading that transformation or scrambling to catch up with competitors who moved first.

The bottom line

The question isn't whether agentic AI will transform customer experience – it's whether your organization will lead that transformation or be forced to follow it. The time to decide is now.