The document discusses AIOps (Artificial Intelligence for IT Operations) as a solution to the alert fatigue and inefficiencies in IT management, particularly in the context of digital transformation initiatives that struggle to meet their goals. It highlights the growing reliance on advanced analytics and automation, with projections of significant increases in AIOps adoption, while also addressing the challenges of data accuracy and talent shortages. Ultimately, AIOps is positioned as a necessary tool for organizations to improve operational effectiveness and reduce human error.

1. 1
Service-Centric AIOps
Reduce the noise with artificial intelligence.

2. Digital Transformation: The Pressure is On
$1.7 trillion (USD)
IDC estimates will be expected
investment in digital
transformation initiatives by 2019.
70%
of complex, large-scale
change programs don’t
reach their stated goals.
84%
of CEOs expect digital
initiatives to increase
profit margins.

3. 3
Alert Fatigue is Beyond Alarming
60%
of financial services
organizations receive
100,000+
alerts per day.
Out of a sampling of
2,542 anomalous events,
only 23.2 were actual
threats, a ratio of nearly
110:1 – the rest were false
positives.
110:1
Is the increase in value-added
work if you shift just 10% of the
IT budget away from
time-intensive incident
management and remediation.
33%-50%

4. Let’s talk about AIOps.
“AIOps is gearing up to
become the next big thing in
IT management...When the
power of AI is applied to
operations, it will redefine the
way infrastructure is
managed.”
- Forbes, 5 Ways AIOps Will
Influence Enterprise IT
Operations

5. What’s the AI Appetite?
● How manageable are modern IT
environments?
● How are enterprises experimenting
with artificial intelligence and machine
learning?
● What AIOps capabilities are they
looking for?
● Which AIOps promises are the most
compelling?
● What are the barriers to AIOps
adoption in their organization?

6. Trend #1: AIOps Is No Longer A Science Project
Bottom line?
The usage of advanced analytics and
automation for IT management use
cases is just getting started.
Gartner projects an eight-fold increase
in AIOps adoption by 2022.
Source: 2018 Top 5 technology predictions, OpsRamp blog

7. Trend #2: Insights and RCA Drive AIOps Usage
Bottom line?
Across the board, respondents resoundingly
agreed: AIOps is a chief solution in the
battle against data smog.
In fact, using AIOps to extract the signal
from the noise is one of the primary use
cases.
Source: MIT Technology - Data Smog: Surviving the Info Glut

8. Trend #3: AIOps Gives Teams Relief
Bottom line? As AIOps tools grow in
sophistication, expect to save time
and money with actionable event context
and data-driven recommendations.
AIOps will let you focus on high-visibility
projects instead of spending all your time on
mundane operational tasks.

9. Trend #4: Barriers Are All About Quality and Talent
Bottom line? Accuracy, data quality and
transparency are the biggest AIOps
roadblocks.
IT leaders will need to identify emerging
AIOps challenges and partner with
technology vendors to prioritize the right
solutions.

10. AIOps Is the Thing.
Without AIOps, human error, hardware failure, and
software failure will continue to plague IT. This
problem becomes more prevalent with hybrid IT,
micro services, and SaaS applications that interact
with traditional applications.

11. 11
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