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

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Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

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For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

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Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

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