Skip to main content

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

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.

Hot Topics

The Latest

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

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

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.

Hot Topics

The Latest

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...