Customer service has always been a high-stakes balancing act. Do more with less. Offer faster support on more channels. Scale globally, but keep it personal.

And in the last year, that balancing act collapsed. Human agents were stretched too thin. AI solutions overpromised and underdelivered. Customer expectations skyrocketed anyway. 70% of customers now expect conversational experiences across touchpoints—and 60% will walk away after just one bad one.

Enter agentic AI. Gartner recently predicted that by 2029, 80% of common customer service issues will be resolved autonomously without human intervention. That figure raised eyebrows. Not because it’s implausible, but because for many, it still feels like a moonshot.

We disagree. In fact, we’d argue it’s already overdue. At Ada , we’ve been building toward this shift for years.

Agentic AI—the kind that can reason, act, and learn independently—isn’t five years away. It’s here. It’s working. And it's not replacing agents—it's reimagining what customer service teams can do when AI isn't just a tool, but a teammate .

At Ada, our customer’s AI agents are already resolving millions of inquiries without humans in the loop. But this isn’t a victory lap. It’s a wake-up call. Because the gap between companies experimenting with bots and those scaling autonomous CX is widening fast.

So let’s unpack the reality behind Gartner’s bold prediction—and what it’ll take to get to 80% before everyone else does.

from chatbot to colleague: the agentic AI evolution

Let’s get one thing straight: agentic AI isn’t a rebrand for smarter chatbots. It’s a fundamentally different approach to automation, in how machines interact with humans and how they deliver business outcomes.

Whereas traditional bots follow scripts, Agentic AI systems are defined by their autonomy —learning from context, adapting to user needs, and initiating actions to reach outcomes without step-by-step guidance. They’re goal-directed, context-aware, and capable of initiating actions without constant human instruction. Think resolving a billing dispute, escalating a fraud concern, or processing a refund—all without a ticket ever being filed.

In other words: they don’t just respond—they resolve. They don’t just follow scripts—they reason, act, and improve over time.

This shift mirrors broader trends in enterprise AI adoption. 40% of organizations are already using generative AI in some capacity, but only a fraction have successfully applied it beyond pilot programs. The majority are still stuck in the ‘digital assistant’ phase—automating greetings, not resolutions.

Agentic AI pushes beyond generative capabilities—it’s not just about understanding language, but about owning outcomes.

At Ada, we call this the AI agent . And we don’t just sell a platform to deploy them, we actually give people the tools to onboard, coach , and promote it, just like you would any other member of your team​. Backed by our Reasoning Engine, our platform enables our customers to isolate issues, retrieve knowledge, trigger backend actions, and deliver consistent outcomes across chat, email , and voice —automatically, intelligently, and relentlessly.

Because customers don’t care whether their answer is “retrieved” or “resolved.” They care that it’s done. And increasingly, they expect it to happen without waiting on hold.

resolution—not response—is the metric that matters

Most automation vendors still brag about response times, chat volumes, or containment. But here’s the reality: touching a ticket isn’t the same as closing one.

What matters now is Automated Resolution —how often your AI can fully solve a customer’s problem, end-to-end, with no human intervention. But resolution alone isn’t enough. It has to be delivered in a way that meets your brand standard and delivers an exceptional experience to reflect both business efficiency and customer satisfaction.

And while 72% of customers expect immediate service, immediacy doesn’t mean faster routing—it means faster resolution. Anything else feels like a delay.

Agentic AI thrives on accountability. At Ada, we measure it religiously, because these aren’t efficiency gains—they’re business transformations. They free up human agents to focus on complex edge cases, turn support from a cost center into a revenue driver, and scale CX without increasing headcount.

That’s what Gartner’s 80% looks like in practice, and the companies measuring the right things today are the ones most likely to hit that mark tomorrow.

you can’t automate excellence without ops

Here’s the uncomfortable truth: most companies aren’t failing at AI because the tech isn’t ready. They’re failing because their operating model isn’t.

Autonomy is earned. AI doesn’t become agentic by accident. It needs coaching, supervision, and strategic resourcing. Guidance, feedback loops, and cross-functional ownership. It needs product teams to connect APIs, ops teams to coach performance , and CX leaders to rethink how success is measured.

In other words, customer service teams need an AI Customer Experience (ACX) framework to follow—a blueprint for building a program that drives both resolution and ROI​. From team structure to integrations to company-wide engagement , following a framework that turns AI into a function—not just a feature—is going to see undeniable impact.

Ada customers who hit 75% Automated Resolution see up to 75% reductions in operating expenses. That’s not just support cost optimization—it’s a strategic moat. Others report savings in the millions. But none of that happens without investing in AI management: a team that measures, trains, and optimizes the AI just like a high-performing hire.

Bottom line? Agentic AI isn’t just a product, it’s an operating model.

omnichannel is the only path to 80%

Agentic AI doesn’t live in a silo. Customers toggle between email, voice, SMS, and social—often within a single interaction. And they expect consistency wherever they land.

That’s why the next wave of autonomy demands true omnichannel orchestration .

Traditional tools treat each channel like an island. AI built this way has to relearn context, repeat itself, or worse—drop the customer entirely. The result? Friction, fragmentation, and failed resolutions.

Agentic AI must be omnichannel by design. That means one brain powering every interaction. One source of truth. One system of action.

Ada’s AI Agent is already delivering on this. Whether a customer starts on Instagram and moves to voice, or asks a follow-up question by email three days later, they’re speaking to the same intelligent system—with full memory, history, and context.

Omnichannel isn’t just a CX flex—it’s a fundamental mindset shift. Everything you build, train, and deliver should be designed to work across every channel, by default.

don’t wait for 2029: the era of AI agents is already here

Gartner’s 2029 forecast is bold—but bold doesn’t mean far away. The technology exists. The playbooks are written. The benchmarks are real.

What’s missing for most companies isn’t capability—it’s commitment. Commitment to operationalizing AI, measuring the right outcomes, trusting intelligent systems with more than triage, and treating AI not as an assistant, but as a true agent.

The companies that win won’t be the ones who wait for perfect AI. They’ll be the ones who invest in it, manage it, and treat it like the game-changing employee it is. At Ada, we’ve seen firsthand how agentic AI redefines what customer service can and should be.

The window for experimenting is closing. The companies that treat agentic AI as a core competency—not a side project—will be the ones who dominate customer experience in the next decade.

Agentic AI has clocked in. The only thing left is whether it’s working for you—or your competitors.