Has your IT org adopted AIOps?

Operations Management Machine Learning (ML)

Fully adopted AIOps8%

Implementing AIOps46%

Partially adopted AIOps17%

Evaluating AIOps benefits21%

We're not considering it7%

Show me results2%

116 PARTICIPANTS

757 views

Content you might like

What are the top key performance indicators (KPIs) you expect to improve for your business with the help of Data Analytics & AI?

Customer satisfaction & loyalty35%

Operational efficiency through predictive and root cause analysis56%

Fraud detection and prevention43%

Asset tracking and investment planning33%

Marketing and customer intelligence ("Segment of One")23%

Performance management of IT and/or network infrastructure17%

Automated infrastructure management10%

Automated customer experience management11%

View Results

What is the one business pain point / challenge that you regularly face, that you wish AI had solved it? The problem could be a time consuming, routine task that is frustrating to handle. It may happen daily / weekly / monthly, and you may lose many hours on it which results in delays / added cost.

Read More Comments

Does your contract lifecycle management tool deliver on their AI/ML promises?

Yes65%

No34%

We are in the process of implementing a chatbot for our local government site with intentions to deploy for internal use only for testing. We are having problems quantifying is the cost around token consumption. I know that cost varies depending on the model used, but does anyone have any useful estimators. Consumption calculators I have found don't seem particularly useful. What methods for estimating cost did you use? Did you use number of searches against the site?

‘AI’ Business Model – With many components flowing into the AI domain (cost, data, E&C, people, value, strategy, duplication of everything, etc.), I’ve started to think about splitting out ‘AI’ from the operating model and putting it into a separate legal entity. This way, I could manage a) risk and compliance, b) cost, c) resource allocation, d) governance, e) IP, f) revenue generation, etc.

Of course, this isn’t new in general, but I’m especially interested in how this approach could help with the ongoing challenge of ensuring compliance with data privacy and regulations related to LLMs and data access/usage over time.

My question: Is anyone else thinking about this, or has anyone already done it? I know there are examples in the literature, but I wanted to float this here for general comments and discussion.

Read More Comments