Over the past year there have been plenty of media reports discussing artificial intelligence failures and highlighting the negative aspects of it. I’m of the belief that AI will eventually be infused into every aspect of our lives and change the way we work, live and learn.
This is similar to the impact the internet had, although the scope and impact of AI will be much bigger than that technology transition. Like the internet, there will be stops and starts, failures and successes but make no mistake: AI is here to stay.
AI agents have arrived
A recent report from RingCentral Inc., 2026 Agentic AI Trends, found AI agents are indeed showing up in the workplace – not as features buried inside applications but rather as coordinated systems that help work move from one step to the next. According to the report, spoken and written interactions are becoming a key input for organizations as they implement AI agents.
A lot gets lost when conversations are boiled down to dashboards. Voice, video and chat carry context that can be missed, especially in live voice conversations where tone and intent matter. In fact, in the past I have referred to voice as “dark data,” and agentic voice AI can capture that input. By listening to live conversations, AI agents can ask questions and pass information along to other systems, so work doesn’t stall or lose context as it moves from one step to the next.
Generative AI has pushed these capabilities directly into everyday work, but most deployments are isolated. This is a good focus for RingCentral as gaining AI adoption is less about introducing new tools and more about connecting what’s already in place. This is an important industry shift as we move from AI vision to AI reality.
Customer sentiment for AI is high today
One of the more interesting data points from the survey was around adoption. Ninety-seven percent of those who participated in the report said they’re using at least one form of AI today. Unsurprisingly, generative AI is the most widely used at 77%, followed by predictive analytics (54%) and process automation (53%).
Early AI deployments tend to focus on tools that are easy to roll out. Sixty-nine percent of business decision-makers said their first initiative went live within a year. During that timeframe, 77% saw a return on investment, and 92% said they were satisfied with their AI initiatives overall. It’s interesting that this data counters the HBR report that came out last year that stated most AI projects fail. I do think the data points in the report were taken out of context, but the RingCentral study shows that AI is becoming more mature and value is being realized.
In January, I talked with Liesl Perez, co-founder and chief growth officer of Denver-based Axis Integrated Mental Health, which uses RingCentral’s AIR (AI Receptionist) product. The organization struggled to answer all the inbound calls and was leaving money on the table. In the time Axis has been running AIR, under a year) Perez told me, it has generated $1.7 million in additional revenue, which for a small organization is very meaningful.
AI can remove day-to-day tedium
Organizations described AI’s impact as largely operational. Fifty-two percent said they’re using it to improve productivity, and 90% stated it works best when applied to specific workflows. Among organizations using or testing agentic AI, 61% reported productivity gains and 58% said workflows move faster, with additional benefits cited around customer experience, operating costs, and customer satisfaction. Perez described the operational use cases for AI as being able to “remove the tedium” from work.
Many organizations are past the early stages with AI agents. Fifty-seven percent reported moving beyond exploration, 93% said they’re familiar with AI agents, and nearly everyone (96%) agreed that AI agents will be essential to staying competitive.
Execution challenges remain
However, there are plenty of organizations that experience execution challenges, and AI projects stall once they’re in motion. Forty percent of organizations have paused or canceled at least one AI project or initiative. Integration complexity is the most common reason (46%), followed by internal resistance or misalignment (33%), unclear or inconsistent ROI (3%), and poor employee user experience (26%).
Similar challenges show up when companies try to scale AI agents. Trust in outcomes (38%) is a major barrier for organizations already using agents. Other barriers include employee resistance, data integration issues and worries about cost and compliance.
This is why orchestration is necessary. RingCentral described it as the layer that connects AI agents, people and systems across an entire workflow. Orchestration allows data to move from one step to the next. Orchestrated systems rely less on rigid inputs like forms or tickets and more on conversational input. Agents interpret conversational input, handle incomplete information and respond to exceptions. They also work together, passing context instead of duplicating effort.
Voice rises as a preferred channel for agentic AI
Interaction preferences suggest where this is heading. RingCentral asked respondents to imagine interacting with an AI agent across customer-facing and employee contexts now and in the future. Forty-two percent said they prefer to interact with AI agents through chat today. However, in two years, that dropped to 25%. Meanwhile, preference for voice rose from 14% to 23% in two years, and video increased from 10% to 22%.
Respondents were also asked to give an AI agent some human traits. They prioritized correctness and clarity over emotion by ranking reliability first (28%). Creativity (24%) and common sense (16%) followed after that. Empathy, accountability, humor and patience were not as desirable.
RingCentral concluded the report with the prediction that the next phase of AI will be system-level, not tool-level. Most organizations already have the necessary building blocks, and the early value is clear. What continues to hold them back is fragmentation. According to RingCentral, the focus must shift to agents that can work together and use real conversations to understand what needs to happen across people and systems.
From a company perspective, the pivot to AI appears to be working for RingCentral. On its most recent earnings call, the company called out annual revenue run rate from customers using at least one monetized AI product as having more than doubled year over year. That’s approaching 10% of overall ARR, with new AI-led products alone reaching $100 million in ARR.
Final thoughts
Just as the internet once transitioned from an experiment to the foundational fabric of global commerce, AI is currently undergoing its own “connectivity” phase. We are moving past the era of the standalone chatbot and into the era of the orchestrated agent. The data in the report shows where the industry is today: Businesses aren’t looking for AI that can tell a joke or show empathy; they want reliability, clarity and the removal of “tedium.”
For organizations still on the sidelines, the key takeaway from the 2026 Agentic AI Trends report is urgency. AI isn’t just a feature to be added — it’s the new system-level architecture required to stay competitive.
Zeus Kerravala is a principal analyst at ZK Research, a division of Kerravala Consulting. He wrote this article for SiliconANGLE.
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