How do you plan to undergo an AI migration in your business?
Tough question, isn’t it?
A few years back, Artificial Intelligence was still just the main topic in a Spielberg blockbuster, not an enterprise operations strategy leveraged by some of the largest and most complex companies in the world. Today, however, the professional world is abuzz with the talk of AIOps while a large and ever-increasing number of companies are taking the plunge and quickly identifying ways to transform their business with this new and exciting technology. Oh yes, The Fourth Industrial Revolution is here to stay.
If you pay attention to what experts, such as Gartner, are saying, there’s plenty of talk about how AI will impact our lives and the world at large but few conversations about how to take that first baby step into AIOps. The Harvard Business Review suggests taking small, initial steps towards AI Migration through any number of ways including buying the technology, building it, or a combination of both. With all the information out there and companies of all flavors offering some sort of AI solution, the very first step is still difficult to identify. The question begs to be asked: Buy what? Build what?
While AI implementation in the enterprise will be different for every company, Walmart.com would want to concentrate on e-commerce or contact centers improvements, All Covered may want to focus on infrastructure and compute performance, and we all know Equifax is scrambling to address their recent security issues. No matter what area is most important to your business, there are a few questions you can ask to decide where to focus and how to make the correct steps towards AI migration and integrate AIOps into your business successfully.
In order to help you get started we have created four questions to help you guide your decision:
1. What part of my digital business will get the most benefits from AIOps with the smallest impact on my team, customers, and operations?
The best way is to identify an area where the biggest impact on a group or division can be realized with a high number of incidents in a given period. If your biggest cost center is your Red Team Incident Response Group on your Security team because they are highly experienced, capable professionals (thereby incredibly expensive), and they spend their time reacting and not innovating, that is a great starting point. If your users are regularly and frequently reporting application slowdowns before your support team identifies them, there could be an area of great impact. Incidents and tickets are always a great place to test solutions. Especially if those solutions are transparent to the users and a test represents no impact on your operations.
2. What criteria do I use to short list vendors?
It’s not the “what” we do that’s important, it’s the “how” that matters. Each vendor in this space is addressing AIOps in their own unique way. Most vendors will require extensive domain knowledge and configuration, while others will aggregate and correlate pre-programmed alerts, certain vendors are technology-as-a-service, and some are AI log analysis and correlation platforms. Because of the massive impact AIOps has over time, the importance of choosing the right vendor to evaluate cannot be overstated. Some key factors to consider: Is the AI built into the architecture or is the AI an integrated add on? How does the application consume data and what sources does it use? What does it do with the data it consumes? Does the application rely on pre-programmed alerts or thresholds? Is the correlation done on alerts or on system performance data?
3. How will my day-to-day operations change with the implementation of this new technology?
This is the most overlooked question during the transition from legacy operations to AIOps. Artificial Intelligence Operations forces a paradigm shift in how companies deliver services and manage digital performance. Just like every innovation in IT operations from Sneakernet and floppy disks to automation, teams have had to adjust how they perform their work and interact with tools. Understanding the changes that AIOps brings to tactical execution and preparing for those changes in advance, will speed up the transition and encourage adoption.
4. How do I ensure acceptance and adoption of AIOps across all related functional areas of my business?
Speaking of adoption…. AI Adoption relates to success and AIOps is no different. The challenge of post implementation adoption for AIOps lies in its usage by your team and the impact it has on your users. AIOps requires less attention that traditional operations and performance management solutions and often times users won’t consciously notice that they aren’t complaining about application slowdowns anymore. It will just sort of stop happening.
When this does happen, one tactic is to share, share, share, and then share some more. It sounds silly, for sure, but the more you communicate the more your impact is felt by both your users and your team. During the evaluation process you can include a large number of people on a distribution list that highlights actions and results, and you can partner with your vendor to conduct presentations for the team at large, both pre- and post-implementation.
When it comes to customers, a simple, impactful e-mail to the users most affected by the issues that led to the evaluation is a great way to emphasize your commitment to user experience and responsiveness.
On the journey to Digital Transformation, AI migration plays a crucial role in defining which businesses will make the breakthrough and succeed the transition to a fully-functional digital business, providing flawless customer experience. Businesses that make the necessary shift as part of The Fourth Industrial Revolution, embracing the vast variety of AI/ML predictive analytics tools will thrive.
Will your organization be there?
Loom Systems delivers an AIOps-powered log analytics solution, Sophie,
to predict and prevent problems in the digital business. Loom collects logs and metrics from the entire IT stack, continually monitors them, and gives a heads-up when something is likely to deviate from the norm. When it does, Loom sends out an alert and
recommended resolution so DevOps and IT managers can proactively attend to the issue before anything goes down.
Get Started with AIOps Today!