EMA’s market research report, “AI-Driven Networks: Leveling Up Network Management,” is based on a survey of 250 North American IT decision-makers who have direct experience with the application of AI/ML and AIOps (AI for IT operations) technology to network management. Overall, 92% of them believe that AI-driven networking will lead to better business outcomes, but they told EMA that their organizations need to improve how they evaluate and implement this technology, and they need better solutions from their vendors. Get more insights when you check out these slides.

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AI-Driven Networks:
Leveling Up Network Management
Shamus McGillicuddy
Vice President of Research, Network Infrastructure
and Operations
Enterprise Management Associates (EMA)
smcgillicuddy@enterprisemanagement.com
Sponsored by

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Watch the On-Demand Webinar
• AI-Driven Networks: Leveling Up Network Management On-Demand
Webinar: https://info.enterprisemanagement.com/ai-driven-
networks-webinar-ss
• Check out upcoming webinars from EMA here:
https://www.enterprisemanagement.com/freeResearch
© 2023 Enterprise Management Associates, Inc.

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Featured Speaker
Shamus McGillicuddy is a Vice President of Research
at Enterprise Management Associates (EMA), where
he leads the network infrastructure and operations
practice. He has nearly two decades of experience
in the IT industry. His research focuses on all aspects
of managing enterprise networks, including network
automation, AIOps-driven network operations, multi-
cloud networking, and WAN transformation.
© 2023 Enterprise Management Associates, Inc. 3
Shamus McGillicuddy
Vice President of Research
Network Infrastructure and Operations

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Sponsors
© 2023 Enterprise Management Associates, Inc. 4

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Agenda
© 2023 Enterprise Management Associates, Inc. 5
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Research Goals and
Methodology
How Do You Get
AI-Driven Network
Management?
3
How AI Benefits
Network Engineering
and Operations
4
Success with AI is
Growing, but
Challenges Remain

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Research Goals and
Methodology

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AI Hype Wave is Cresting
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Do people still believe in this tech?
Are they doing a better job with it?
How did they get there?
90% of IT pros believed AI-driven
networking would lead to better business
outcomes
Only 30% had been completely successful
with applying AIOps and AI/ML to network
management
Updating 2021 Research: Revolutionizing Network Management with AIOps
© 2023 Enterprise Management Associates, Inc. 8
findings research goals
2021 2023

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2023 Methodology
Survey 250 IT Pros With AI-Driven Network Management Experience
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Top job titles
Company size
(employees)
Annual revenue
Top industries
38.4% 500 to 2,499
31.2% 2,500 to 4,999
18.8% 5,000 to 9,999
11.6% 10,000 or more
33.6% IT director
20.4% IT manager/supervisor
11.6% CIO/CTO
8.4% Network engineer
6.0% Network/Systems
administrator
5.2% IT vice president
4.4% Network architect
37.2% $50 million to less than
$500 million
26.0% $500 million to less than
$1 billion
34.0% $1 billion or more
2.8% No revenue/unknown
25.6% Manufacturing
18% Banking/Finance/
Insurance
12.8% Retail
8.8% Healthcare/Hospitals
7.6% Construction/Civil
engineering
6.8% Professional/Business
services
3.6% Education
3.6% Energy/Utilities
IT groups
21.6% CIO suite
20.0% IT tool engineering team
16.2% Network or IT operations
12.0% Cloud operations
10.0% Network engineering
10.0% IT security/cybersecurity
6.0% IT architecture
4.8% Data center operations

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How Do You Get
AI-Driven Network
Management?

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Solution Strategies for Applying AI to Networks
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AI and IT management overall
84% say applying AI to IT management is a
high priority
• Lower priority = failure with AI-driven
networking
94% are allocating budget for applying AI to
IT management in general
• Budget availability drives success with
AI-driven networking

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Most Organizations Need to Improve How They Evaluate Solutions
© 2023 Enterprise Management Associates, Inc. 12
Silo perspectives on ability to evaluate
• Network engineering and NetOps teams
are pessimistic
• CIO’s suite, CloudOps, IT tool engineering
teams are optimistic
How to evaluate
• 56% Explainable AI tools/resources
• 52% In-depth conversations with vendors
about algorithm development & training
• 51% Industry analyst engagement
• 49% Vendor content
• 49% PoCs
ORGANIZATIONAL EFFECTIVENESS WITH EVALUATING AI/ML
TECHNOLOGY APPLIED TO NETWORK MANAGEMENT

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How AI Benefits
Network Engineering
and Operations

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Top Use Cases
© 2023 Enterprise Management Associates, Inc. 14

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Data center modernization/private cloud
Cloud-native applications/app modernization
Public cloud/multi-cloud migration
Benefits of Using AI-Driven Network Management
© 2023 Enterprise Management Associates, Inc. 15
Most common gains
AI helps the network team support:
47% Network optimization
Network agility
Improved security/compliance*
Network resiliency
Operational efficiency
36%
36%
35%
34%
* Experienced by most successful organizations
40%
38%
38%
Successful orgs also report IoT and VDI opportunities

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69% report that AI-driven networking led to at least some
improvement in overall end-user experience
92% believe AI-driven networking leads to better
business outcomes
A Better Network Experience
© 2023 Enterprise Management Associates, Inc. 16
Up from 90% in 2021
Warning: enthusiastic agreement has shrunk from 56% to 50%
since 2021
24% report this improvement as significant
Stronger improvements among most successful users of AI tech
Commercial AI/ML and AIOps solutions deliver better results than
homegrown AI projects

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Success with AI is
Growing, but
Challenges Remain

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Fully Successful Users of AI Increased From 30% to 36% Since 2021
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Perception gaps:
• IT execs 2x as positive as
technical personnel
• Members of network
engineering, IT architecture,
CloudOps are more pessimistic
than CIO’s suite and IT tool
engineering team
OVERALL SUCCESS WITH APPLYING AI/ML AND AIOPS TECHNOLOGY
TO NETWORK MANAGEMENT THUS FAR

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Individual Perspectives on Success
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IT vice president
$9 billion financial
services company
“I’m on the right path because we’re doing it right by taking our
time. You can’t just buy something and have it work. Often, people
are struggling to understand what [AIOps] means, and it takes time
to explain it to them even though these are smart people.”
IT operations manager
$15 billion financial services
company
“It’s hard to say if we’ve been successful. We’re still in the
crawl-before-we-walk-and-run phase. Right now, I’d give us a four
or five out of ten because we’re not finished with the deployment
yet. I’m hoping for a seven or eight out of ten once we’re finished.”

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AI-Driven Networking Pain Points
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30% Security/compliance risk
28% Skills gaps
23% Budget issues
20% Cultural resistance/trust*
* Members of network engineering teams twice
as likely to select
25% Network complexity*
24% Data issues
23% Interoperability/integration problems
22% Algorithmic training on customer
network needs improvement
* Members of NetOps teams more likely to
struggle
Business issues Technical issues

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Tips for AI-Driven Networking Success
© 2023 Enterprise Management Associates, Inc. 21
Build up expertise around evaluating AI/ML and AIOps – lean on
your peers
Look for opportunities everywhere: Don’t confine AI to a single
network domain
Vendors with deep networking expertise are essential
(domain-agnostic has limited impact)
Don’t let cost influence deployment and administrative approach
to AI features
If you have it, mandate
that you use it
Orgs that integrate AI into more
processes do better
Orgs that only use it after legacy
tools/processes fail do worse
Embrace chatbots
Network assistants
ChatGPT?

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The AI-Driven Networks Research Report is Now Available!
Learn more and download
https://bit.ly/3VsyzjI
© 2023 Enterprise Management Associates, Inc. 22