The Dumb Reason Your AI Project Will Fail




  • 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)