What explains the disappointing end? Well, it’s hard — in fact, very hard — to integrate AI models into a company’s overall technology architecture (View Highlight)
It is a practice involving building, integrating, testing, releasing, deploying, and managing the system to turn the results from AI models into desired insights of the end-users. At its most basic, AIOps boils down to having not just the right hardware and software but also the right team: developers and engineers with the skills and knowledge to integrate AI into existing company processes and system (View Highlight)
For any business wanting to leverage on the benefits of AI, what truly matters is not the AI models themselves; rather, it’s the well-oiled machine, powered by AI, that takes the company from where it’s today to where it wants to be in the future. Ideals and one-time projects don’t. AIOps is therefore not an afterthought; it’s a competitive necessity. (View Highlight)
