Industry executives and experts share their predictions for 2025. Read them in this 17th annual VMblog.com series exclusive. By Frank Kelly, VP and Chief Technology
Officer, Hughes Network Systems
Organizations spanning many industries have
spent recent years launching programs to investigate what AI technology can do.
Managed service providers (MSPs) have given special attention to pilot projects
that can improve the customer experience while optimizing internal workflows. Test-driving
all the latest tools hasn't delivered as much real business value as some
enterprises hoped, despite devoting significant time and financial resources to
deploying AI across numerous operational areas. Many programs, such as anomaly
detection and auto-remediation of simpler scenarios, have indeed proven immensely
useful, while others missed the mark, leaving them short on results as we find
the right blend of AI capabilities and real-world use cases.
Moving into 2025, MSPs will have more
options to find a productive path forward by leveraging AI in ways that demonstrate
tangible value in practical applications.
GenAI will enable greater use of unstructured
data to tackle more nuanced business needs
GenAI will enable businesses to take
unstructured data and make it more relational in terms of having a
multi-dimensional model to generate complex relational models. That will empower
MSP help desks to use AI to automatically identify characteristics of customer
calls based on words used and the tone of the voice through the journey of the
call. AI can leverage clustering and relationships to generate patterns that
indicate why some calls are long and sometimes do not result in positive
resolutions whereas others are short and a solution is clear. How can we reduce
those long calls and potentially use other tools like self-service or other
automated options to eliminate short calls? Customer calls generally break down
into initial problem definition and information gathering phases. Then there is
a correction phase, followed by the crucial validation phase to confirm the
problem was fixed. Companies can look forward to dealing with customer service
calls through new, innovative methods driven by GenAI to quickly identify and
analyze the journey, the actions taken, and the information needed. That can be
partnered with agentic AI to drive the resolution journey without burdening the
customer with decision-making, using machine-learned processes to quickly and
accurately identify the root cause and drive corrective actions to resolve the
issue.
Customers will trust AI more as it demonstrates
consistent value in MSPs' processes
MSPs have already implemented AI to help
identify the causes of problems. The industry is also using AI to deploy fixes
after getting the go-ahead from the customer. In 2025, we expect to move
further along that spectrum to the point where customers will say, "Every time
you bothered me with that issue in the past, you fixed it without causing
problems. So now just go fix it for me, don't even ask." Many MSP customers want
AI because it can save time and result in higher network resilience, but the
early days were a little rocky, and it's taken a while to earn people's trust. MSPs
have worked hard to build that trust through consistent execution and through
customers seeing the success of that execution.
Outbound chatbots will deliver more
proactive value from AI
Historically, MSPs have waited for users to
call in if they need something or if something has gone wrong. Today, chatbots
often field those incoming user calls, asking questions and trying to provide
answers. MSPs will be developing outbound chatbots, flipping that around and
functioning proactively. From a customer service standpoint, that's already what
many people think of when envisioning agentic AI-a system that reaches out to
alert customers to a problem before they even know something is wrong and seeks
approval to implement a fix. MSPs will be able to build orchestration within AI
and take multi-stage actions to head off problems before they take hold. The
outbound chatbot can then contact the customer to confirm the problem is fixed.
MSPs will be identifying and then proactively isolating, investigating, and resolving
anomalies before they become events. AI is progressing toward eliminating
disruptive events by detecting anomalies very early and taking proactive
actions.
More businesses will focus their AI use
cases on finding practical solutions to fix real problems
IT teams have been challenged to direct their
resources strategically because the AI world is moving so fast, and most
companies don't have enough people to do everything they want to do with it. Forward-looking
organizations will focus on those areas where AI can have a tangible positive
impact, using their experts to train these AI models and validate that they do
the right things. People have lost trust in AI partly because the models are
being developed so quickly, and they're learning so fast that there's a lot of
noise coming out of them. We need people with the knowledge to do checks and
balances on AI outputs, apply context and human perspective on the technology,
and confirm that the experts agree with what the machines tell us.
As part of the transition toward more
strategic implementations of AI, human expertise within IT will be even more critical
in 2025 and beyond. Enterprises will increasingly focus on ensuring the
technology supports the overall business goals, and strong technical and
operational experience will be key to achieving success. The additional clarity
gained by IT and business leaders in recent years will both enable and motivate
organizations to move away from experimental programs and instead prioritize
practical applications of AI, where it can help solve real problems.
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ABOUT THE AUTHOR
Frank Kelly, Vice president at Hughes
Network Systems, LLC, is the chief technology officer for Hughes Business
Solutions, responsible for identifying innovation and technology to improve
service effectiveness and efficiency for enterprise services. In this capacity,
he oversees the strategic direction and implementation of machine learning and
artificial intelligence, in addition to applying agile development and service
delivery techniques and integrating DevOps technologies into Hughes services.
Mr. Kelly earned a master's degree in information technology from Hood College,
Maryland, with a focus on network management. He also holds a bachelor of
science degree in computer science from the University of Maryland.