2025 marked the year when organizations began to adopt AI broadly. 2026 will be the year they confront a new reality that using AI and benefiting from it are not the same thing.<\/p>\n
In partnership with Opinium Research, we recently surveyed 2,000 IT, HR, and CX decision-makers (manager level and above) from the US and UK, representing small and mid-size businesses (SMBs) and enterprise organizations across retail, technology, healthcare, legal, and financial services.<\/p>\n
Our soon-to-be-released RingCentral Agentic AI Trends 2026 reveals that, across nearly every industry, AI is present in dozens of tools and workflows; yet, few organizations have successfully integrated those systems into a coherent whole. (Of decision-makers surveyed, 86% say they have an AI strategy, but only 39% have integrated AI company-wide, and only 16% have deployed AI at scale.)<\/p>\n
The result is duplicative work, inconsistent customer experiences, and growing friction for employees asked to collaborate with intelligent tools that don\u2019t collaborate with themselves.<\/p>\n
That fragmentation has set the stage for what\u2019s next in agentic AI: moving from AI features scattered across applications to orchestrated AI agents capable of carrying context and taking action across channels and systems.<\/p>\n
Here are RingCentral\u2019s top predictions for how AI (and the organizations deploying it) will evolve in 2026.<\/p>\n
Software has been structured around applications for two decades. What we\u2019ll start to see next is that work organizing around agents instead.<\/p>\n
AI agents, referred to as \u201cdigital workers\u201d in our study, are emerging as the first operational layer capable of performing end-to-end work, moving tasks forward across platforms, workflows, and communication channels. Our research shows:<\/p>\n
The change is both conceptual and technical as organizations evolve their perspective on AI from \u201ctask automation\u201d to \u201cworkflow orchestration.\u201d<\/p>\n
\u201cIn 2026, the real shift will come from making AI truly operational. That means integrated systems, governed data, and intelligence that can understand human context at scale,\u201d says Kira Makagon, RingCentral\u2019s President and Chief Operating Officer.<\/p>\n
We\u2019re entering a moment when autonomous, context-carrying agents (and Agentic Voice AI) become the connective tissue of modern business operations.<\/p>\n
Right now, AI strategy ownership is split across functions, with 23% held by IT leadership, 23% by dedicated innovation teams, and 21% shared between business and technical leaders. Another 14% is owned by operations or CX leadership, and in 9% of organizations, no one owns it at all.<\/p>\n
These function-specific ownership models may have worked in the past when AI lived in isolated pilots and automation projects, but they break down once AI starts impacting revenue, customer experience, risk, hiring, data architecture, and internal culture.<\/p>\n
Companies are realizing that AI cannot be confined to a single department and must operate with clear, organization-wide rules. A more formal and coordinated approach is replacing the ad-hoc ownership model with:<\/p>\n
\u201cWhile AI adoption in enterprises seems inevitable, this research provides a more nuanced view of the realities. On one hand, it\u2019s validating to see that CX leaders are seeing real ROI, and in less time than might be expected,\u201d says Jon Arnold, Principal Analyst, J Arnold & Associates. \u201cThe data also shows a very high level of optimism towards AI, but a closer look counters some of that. Most deployments are more standalone for specific use, rather than being more fully integrated into workflows. For AI to deliver on its lofty promises, the latter will have to become the norm, where deployments have an impact at scale, not just across the organization, but with both customers and employees.\u201d<\/p>\n
A shared model turns governance into a stabilizer that eliminates rework, lowers project failure rates, and gives teams confidence to scale. Once decision rights and rules are clear, progress is steadier and less dependent on individual champions.<\/p>\n
One of the most overlooked aspects of agentic AI is the friction that comes from learning to work alongside it. Teams are still figuring out what AI can actually do, where it fits, and how it changes the work they already know.<\/p>\n
Our study shows that concerns about job impact haven\u2019t completely vanished, and nearly 40% of organizations have paused or cancelled an AI project, mostly because expectations, workflows, or training weren\u2019t aligned from the start. However, many (53%) now say they would prefer managing a digital agent.<\/p>\n
This mix of reluctance and growing comfort suggests that people aren\u2019t rejecting AI in general, but rather pushing back against AI that\u2019s confusing, inconsistent, or bolted onto a workflow that wasn\u2019t designed for it.<\/p>\n
Most of this friction is practical. Take, for example, the frustration that results when an AI system behaves differently in chat and on the phone, fails to hand off work with gaps in context, or adds steps instead of removing them. Those are moments people remember and that shape opinions about whether AI is helping or getting in the way.<\/p>\n
When AI starts behaving predictably with the same rules, logic, and expectations, tension decreases. Team members stop second-guessing the system and start focusing on their actual work. Then, the most significant productivity lift happens as AI lowers the coordination overhead that slows people down (like the follow-ups an AI agent handles automatically or the context it organizes before a call) and is a steady presence that\u2019s deeply felt in the everyday flow of business.<\/p>\n
Customer experience (CX) is where disconnected systems cause the most pain, and the benefits of orchestration are most evident.<\/p>\n
Fragmentation is a common experience in CX, and everyone feels its impact. Customers repeat the same information across multiple channels and receive inconsistent answers across touchpoints. Cases bounce between employees with sluggish handoffs that don\u2019t provide the full details of the customer\u2019s original inquiry or concern. As a result, the endless cycle of repetition and frustration continues.<\/p>\n
\u201cIn CX, the gaps are impossible to hide. When information actually carries from one interaction to the next, whether it starts in voice, chat, or text, everything changes,\u201d says Carson Hostetter, RingCentral\u2019s EVP & GM of CX & AI. \u201cCustomers stop repeating themselves, agents get straight to the issue, and the whole experience becomes more streamlined. That\u2019s where AI agents make a real difference.\u201d<\/p>\n
Organizations utilizing AI agents report significant improvements in resolution speed, satisfaction, and consistency across all channels:<\/p>\n
These early gains likely stem from coordinated systems that are finally communicating with each other effectively, rather than requiring employees to manually bridge the gaps.<\/p>\n
CX will be the proving ground for agentic AI because the stakes are high and the potential payoffs are tremendous: shorter wait times, fewer escalations, consistent responses, cleaner handoffs, and customer experiences that don\u2019t differ by the channel used.<\/p>\n
SMBs have had a structural advantage in AI adoption. With fewer legacy systems and shorter decision cycles, they\u2019ve been able to move quickly from experimentation to deployment. Our research reflects this speed, with SMBs reporting that they see AI ROI slightly faster than large enterprises.<\/p>\n
Now, enterprises are positioned to catch up, supported by more robust architecture. When larger organizations adopt orchestrated systems (in which AI agents can pass context across workflows, applications, and teams), they\u2019ll unlock efficiencies previously buried by their own complexity.<\/p>\n
\u201cWhen you look at what\u2019s happening in the market, AI agents really are becoming the engine of growth,\u201d says Akshay Srivastava, RingCentral\u2019s EVP & GM of SME. \u201cSMBs will keep moving fast as they can spin up agents quickly and see results right away. For larger companies, the turning point is different. Once they connect their systems so context actually travels with the work, their scale becomes a real advantage.\u201d<\/p>\n
After a year of rapid experimentation, organizations are realizing that the biggest challenge presented by AI is finding alignment.<\/p>\n
Our research and predictions reinforce the same key takeaway: the advantage will shift to organizations that can effectively integrate AI as a cohesive system.<\/p>\n
To achieve true integration, companies will need an agentic AI architecture that enables agents to carry context, coordinate tasks, and support people across workflows instead of operating in isolation. That\u2019s when CX can become a real proving ground, SMBs and enterprises can unlock value through their respective AI paths, and governance can shift from a checkpoint to a growth function.<\/p>\n
Conversational data, including Agentic Voice AI (AI that analyzes intent, sentiment, and context from voice and activates the appropriate agentic workflows), serves as one of the richest signals for intent and context within that system.<\/p>\n
Our upcoming report goes deeper into these patterns, the data behind them, and where organizations are heading next. Sign up to get the report<\/a>.<\/p>\n AI agents (defined as \u201cdigital workers\u201d in our RingCentral 2026 Report on Agentic Voice AI Trends) are autonomous, software-based workers that can perform tasks, carry context, make decisions within guardrails, and coordinate work across systems, extending beyond generating outputs within an app.<\/p>\n Agentic AI refers to systems that take action. These systems can interpret intent, reason within context, and advance work across workflows, unlike traditional AI features that operate in isolation.<\/p>\n Agentic Voice AI leverages agentic intelligence to analyze conversational data, particularly in spoken interactions. Voice provides one of the richest signals in the enterprise: intent, sentiment, urgency, nuance, and context. Agentic Voice AI captures that signal and allows AI agents to carry it forward through a workflow, triggering the right actions across systems. It\u2019s not \u201cthe bridge\u201d between tools, but it is a powerful upstream input that makes orchestration smarter, faster, and more aligned with how people communicate.<\/p>\n Yes. RingCentral Agentic AI Trends 2026 <\/span> used the term \u201cdigital workers\u201d in the fielding survey, but across RingCentral, we use the term \u201cAI agents.\u201d<\/p>\n +++<\/p>\n Survey methodology note: RingCentral Agentic AI Trends 2026 <\/span> is based on a Q4 2025 survey conducted by Opinium Research among 2,000 IT, HR, and CX decision-makers (manager level and above) from the US and UK, representing SMB and enterprise organizations across retail, technology, healthcare, legal, and financial services. In the study, \u201cdigital workers\u201d refer to AI agents, defined as autonomous software-based workers capable of carrying out tasks and collaborating across workflows.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":" 2025 marked the year when organizations began to adopt AI broadly. 2026 will be the year they confront a new reality that using AI and benefiting from it are not the same thing. In partnership with Opinium Research, we recently surveyed 2,000 IT, HR, and CX decision-makers (manager level and above) from the US and …<\/p>\n","protected":false},"author":166,"featured_media":60543,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[43331,4],"tags":[],"class_list":["post-60542","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-innovation","category-customer-experience"],"acf":[],"yoast_head":"\n<\/a>FAQs<\/h2>\n
What is an AI agent?<\/h3>\n
What is Agentic AI?<\/h3>\n
What is Agentic Voice AI?<\/h3>\n
Are \u201cdigital workers\u201d and \u201cAI agents\u201d the same thing?<\/h3>\n