AI Appreciation Day Feature: Agentic AI Poised to Handle 68% of Customer Service and Support Interactions by 2028

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Respondents predict that agentic AI will play an increasingly prominent role in their interactions with technology vendors over the coming years and are positive about the benefits it will bring, according to The Race to an Agentic Future: How Agentic AI Will Transform Customer Experience, a report from Cisco.  

88% report they feel confident that the agentic AI-led customer experience provided by technology partners will help their organization achieve its goals — for example, making their IT environments and operations more efficient, resilient and secure, accelerating their most important strategic IT projects, and maximizing value from their IT investments.

Respondents also expect the pivot to agentic AI-led customer experience (including technical support, customer success and professional services) to advance at a far greater velocity than the industry anticipated. They predict that 68% of their customer experience interactions with technology partners will be handled using agentic AI within the next three years. And, surprisingly, they expect more than half (56%) of interactions to be through agentic AI within the next 12 months, representing a significant increase and heaping pressure onto those vendors who are still only in the early stages of thinking about agentic.

In recent years, in response to growing IT complexity, technology businesses have introduced automation into their workflows and layered in AI to streamline support and services. This approach has still required human intervention to stitch processes together — to monitor, decide, act and adapt. Agentic AI negates the need for this level of human intervention. Agentic AI is a category of artificial intelligence that leverages AI Agents and a contextualized interconnection among them.

Agentic AI requires agency, meaning the AI Agents are capable of having memory, are task aware and possess the ability to independently take actions — or choose what actions to take or recommend — to achieve a particular outcome through the ability to learn from their environment and reason, with minimal human oversight.

This frees up customer experience professionals to focus on complex problem-solving, humans-on-the-loop feedback process for specific use-cases (where humans, for example, provide feedback to an AI system to improve its performance and focus on accurate and safe results), and building deeper, trusted relationships with customers.

Respondents are clear that they believe vendors who are left behind or fail to deploy agentic AI in an effective, secure and ethical manner, will suffer a deterioration in customer relationships, reputational damage and higher levels of customer churn. Meanwhile, the research highlights that respondents feel that vendors who embrace this transformation head-on, seamlessly and ethically deploying agentic AI across the technology lifecycle, will benefit from data-driven insights, improved scalability within their support and services, and loyalty at scale. Customer experience will become a strategic differentiator, with 81% of respondents predicting that vendors that successfully deliver agentic AI-led customer experience will gain a competitive edge.

Key findings include:

Accelerated demand for customer experience

As levels of IT complexity increase, organizations are leaning on technology vendors more than ever before. 92% of respondents state that the support and services provided by vendors are becoming more critical in the AI era.

Use cases across the technology lifecycle

More than 80% of respondents point to potential benefits of agentic AI-led customer experience at every stage of the technology lifecycle, with customer and technical support, technology strategy and planning, and operations viewed as the greatest opportunities.

Game-changing benefits

Customers expect agentic AI to drive improvements in IT productivity, time savings, and cost savings, as well as opportunities to improve data analytics, troubleshooting, and alignment of technology investment with digital transformation goals.

Human connection is irreplaceable

Customers want to retain human interaction when engaging with support and services, with 96% stating that human relationships are very important when interacting with B2B technology partners.

Robust governance is non-negotiable

99% of respondents state that it's important for technology partners to demonstrate robust governance arrangements to deliver ethical use of agentic AI, and 81% feel that vendors need to share their vision for AI-led customer experience to bring customers along on the journey.

Methodology: The report is based on a survey of 7,950 global business and technical decision-makers across 30 countries.

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AI Appreciation Day Feature: Agentic AI Poised to Handle 68% of Customer Service and Support Interactions by 2028

Learn more about Cisco

Respondents predict that agentic AI will play an increasingly prominent role in their interactions with technology vendors over the coming years and are positive about the benefits it will bring, according to The Race to an Agentic Future: How Agentic AI Will Transform Customer Experience, a report from Cisco.  

88% report they feel confident that the agentic AI-led customer experience provided by technology partners will help their organization achieve its goals — for example, making their IT environments and operations more efficient, resilient and secure, accelerating their most important strategic IT projects, and maximizing value from their IT investments.

Respondents also expect the pivot to agentic AI-led customer experience (including technical support, customer success and professional services) to advance at a far greater velocity than the industry anticipated. They predict that 68% of their customer experience interactions with technology partners will be handled using agentic AI within the next three years. And, surprisingly, they expect more than half (56%) of interactions to be through agentic AI within the next 12 months, representing a significant increase and heaping pressure onto those vendors who are still only in the early stages of thinking about agentic.

In recent years, in response to growing IT complexity, technology businesses have introduced automation into their workflows and layered in AI to streamline support and services. This approach has still required human intervention to stitch processes together — to monitor, decide, act and adapt. Agentic AI negates the need for this level of human intervention. Agentic AI is a category of artificial intelligence that leverages AI Agents and a contextualized interconnection among them.

Agentic AI requires agency, meaning the AI Agents are capable of having memory, are task aware and possess the ability to independently take actions — or choose what actions to take or recommend — to achieve a particular outcome through the ability to learn from their environment and reason, with minimal human oversight.

This frees up customer experience professionals to focus on complex problem-solving, humans-on-the-loop feedback process for specific use-cases (where humans, for example, provide feedback to an AI system to improve its performance and focus on accurate and safe results), and building deeper, trusted relationships with customers.

Respondents are clear that they believe vendors who are left behind or fail to deploy agentic AI in an effective, secure and ethical manner, will suffer a deterioration in customer relationships, reputational damage and higher levels of customer churn. Meanwhile, the research highlights that respondents feel that vendors who embrace this transformation head-on, seamlessly and ethically deploying agentic AI across the technology lifecycle, will benefit from data-driven insights, improved scalability within their support and services, and loyalty at scale. Customer experience will become a strategic differentiator, with 81% of respondents predicting that vendors that successfully deliver agentic AI-led customer experience will gain a competitive edge.

Key findings include:

Accelerated demand for customer experience

As levels of IT complexity increase, organizations are leaning on technology vendors more than ever before. 92% of respondents state that the support and services provided by vendors are becoming more critical in the AI era.

Use cases across the technology lifecycle

More than 80% of respondents point to potential benefits of agentic AI-led customer experience at every stage of the technology lifecycle, with customer and technical support, technology strategy and planning, and operations viewed as the greatest opportunities.

Game-changing benefits

Customers expect agentic AI to drive improvements in IT productivity, time savings, and cost savings, as well as opportunities to improve data analytics, troubleshooting, and alignment of technology investment with digital transformation goals.

Human connection is irreplaceable

Customers want to retain human interaction when engaging with support and services, with 96% stating that human relationships are very important when interacting with B2B technology partners.

Robust governance is non-negotiable

99% of respondents state that it's important for technology partners to demonstrate robust governance arrangements to deliver ethical use of agentic AI, and 81% feel that vendors need to share their vision for AI-led customer experience to bring customers along on the journey.

Methodology: The report is based on a survey of 7,950 global business and technical decision-makers across 30 countries.

Related Links

Hot Topics

The Latest

Three Strikes and They're Gone: Why Proactive Operations is Now a Customer Retention Strategy

IT organizations have historically measured success by how quickly they can respond when something goes wrong. The entire discipline of Incident Management has been optimized around mean time to resolution, first-response SLAs and ticket closure rates. But new research suggests that even though this is a well-executed playbook, it's no longer enough to retain customers ...

When the Database Is the Problem, Is APM Enough?

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

From Cleanup to Prevention: The Future of Cloud-Native Cost Optimization

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

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Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

Beyond Buy vs. Build: The New Playbook for Data Pipelines

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

The Corporate Network Is Fading - Here's What Replaces It

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

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As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

Data Center Outages Are Decreasing but More Costly

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

Observability Has a Physical Layer Now: What AI Infrastructure Teaches IT Operations

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

TLS Certificate Expiration Is Becoming an Observability Problem

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...