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Raise The Bar with Machine Learning for Improved Customer Service

Holly Simmons

For today's executives, machine learning is the latest term to get hyped before slowly becoming a reality. And in fact, the majority of CIOs have now begun to take advantage of this transformational, labor-saving technology for customer service, IT, and other parts of the organization.

More than two-thirds of CIOs believe that decisions made by machines will be more accurate than human-made decisions

The Global CIO Point of View report compiled by ServiceNow notes that 89 percent of organizations are either in the planning stages or are already taking advantage of machine learning. Nearly 90 percent of the CIOs surveyed anticipate that increasing automation will increase the speed and accuracy of decisions, and more than two-thirds believe that decisions made by machines will be more accurate than human-made decisions.

With digital transformation being a top priority on many corporate agendas, IT and customer service are partnering to bring machine learning to real world use to improve the customer experience, to reduce manual work by customer service agents and field service technicians, and to improve the quality of service.

A new report from Accenture found that front-line customer support functions spend up to 12 percent of their time categorizing, prioritizing, and assigning tickets. And 27 percent are weighed down by having to choose from 100+ assignment groups.

Machine Learning Improves Customer and Agent Experiences

Most customers today prefer to help themselves via self-service ... Machine learning simplifies this process for the customer

Most customers today prefer to help themselves via self-service including filing a case or request online. Machine learning simplifies this process for the customer by reducing the number of categories from which to choose. Additionally, because requests are being automatically assigned, response times are faster and fewer calls are required.

For agents, eliminating manual work opens the door to focusing on more strategic work such as helping customers get more out of the products or services they purchased. Assignment errors are reduced thus eliminating unnecessary escalations and shortening the time to case closure. For companies, machine learning not only reduces costs, but also improves agent engagement and satisfaction.

Removing the Hurdles Democratizes Machine Learning

One of the obstacles CIOs face in bringing machine learning into their organization is the high cost of entry. Taking full advantage of machine learning in-house requires data scientists that are costly and in short supply. Only about one in four CIOs report having the staff to properly execute their machine learning strategy. This requires a rethink of the best way to implement machine learning. How can you take advantage of this technology without hiring an army of data scientists?

The good news is that third-party providers are now able to integrate machine learning models into their applications including customer service or CRM systems. Pre-built approaches enable rapid implementation and the ability to see results in less than a day without the need to staff up.

Something as simple as fewer categories and faster case assignment can have a noticeable impact on customer engagement, agent satisfaction, and the bottom line. IT working in harmony with customer service to take advantage of machine learning opens up a new world of possibilities. The hype is high, the rewards are real, and the time is right for organizations to embrace this technology and experience the benefits for themselves.

The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

Image
Broadcom

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...

Raise The Bar with Machine Learning for Improved Customer Service

Holly Simmons

For today's executives, machine learning is the latest term to get hyped before slowly becoming a reality. And in fact, the majority of CIOs have now begun to take advantage of this transformational, labor-saving technology for customer service, IT, and other parts of the organization.

More than two-thirds of CIOs believe that decisions made by machines will be more accurate than human-made decisions

The Global CIO Point of View report compiled by ServiceNow notes that 89 percent of organizations are either in the planning stages or are already taking advantage of machine learning. Nearly 90 percent of the CIOs surveyed anticipate that increasing automation will increase the speed and accuracy of decisions, and more than two-thirds believe that decisions made by machines will be more accurate than human-made decisions.

With digital transformation being a top priority on many corporate agendas, IT and customer service are partnering to bring machine learning to real world use to improve the customer experience, to reduce manual work by customer service agents and field service technicians, and to improve the quality of service.

A new report from Accenture found that front-line customer support functions spend up to 12 percent of their time categorizing, prioritizing, and assigning tickets. And 27 percent are weighed down by having to choose from 100+ assignment groups.

Machine Learning Improves Customer and Agent Experiences

Most customers today prefer to help themselves via self-service ... Machine learning simplifies this process for the customer

Most customers today prefer to help themselves via self-service including filing a case or request online. Machine learning simplifies this process for the customer by reducing the number of categories from which to choose. Additionally, because requests are being automatically assigned, response times are faster and fewer calls are required.

For agents, eliminating manual work opens the door to focusing on more strategic work such as helping customers get more out of the products or services they purchased. Assignment errors are reduced thus eliminating unnecessary escalations and shortening the time to case closure. For companies, machine learning not only reduces costs, but also improves agent engagement and satisfaction.

Removing the Hurdles Democratizes Machine Learning

One of the obstacles CIOs face in bringing machine learning into their organization is the high cost of entry. Taking full advantage of machine learning in-house requires data scientists that are costly and in short supply. Only about one in four CIOs report having the staff to properly execute their machine learning strategy. This requires a rethink of the best way to implement machine learning. How can you take advantage of this technology without hiring an army of data scientists?

The good news is that third-party providers are now able to integrate machine learning models into their applications including customer service or CRM systems. Pre-built approaches enable rapid implementation and the ability to see results in less than a day without the need to staff up.

Something as simple as fewer categories and faster case assignment can have a noticeable impact on customer engagement, agent satisfaction, and the bottom line. IT working in harmony with customer service to take advantage of machine learning opens up a new world of possibilities. The hype is high, the rewards are real, and the time is right for organizations to embrace this technology and experience the benefits for themselves.

The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

Image
Broadcom

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...