A well-conducted integration of AI (Artificial Intelligence) can make the difference between action and inaction.
The consecutive crises have generated legitimate concern about the future. Despite the waves of Covid, the war in Ukraine, the increase in episodes of climatic chaos associated with political and financial uncertainties, we continued to get up every morning to go to work, we did not stop taking care of the children … We actually managed to adapt.
This finding is the same for businesses. Before the pandemic, IT teams were mainly responsible for managing IT outages. This crisis has forced almost all IT organizations to improve the management of their digital services. Today, the digital environment can no longer be managed independently within the company. Just as manual IT organizations are no longer suitable for tracking production and services deployed by sales teams. We must consider these new constraints as a beneficial evil that forces the implementation of changes in digital management. Integrate AIIT is expected to adapt. Until then, IT teams fixed problems once they were detected. They constantly had to solve the same problems with setting up manual responses like emails, crisis cells and phone calls. This organization of consecutive responses to problems that have already arisen can no longer meet the expectations of today’s digital world. With predictive intelligence, IT service teams can move away from dealing with point outages. They let the AI identify and drive problem solving. With the Predictive AIOps tool, IT teams use AI to predict and prevent failures before they affect the rest of the production chain. By bringing these two functions together on a single AI-powered platform, the magic happens. IT problems can be predicted as their resolution that is anticipated before they affect users or the business. Step One: Data How to integrate AI? The memorization and routing of computer incidents are good bases in which AI can make improvements. As the AI improves from historical data, it can be taught to route a ticket automatically without human intervention. To be optimized, it needs to be fed with a sufficient quantity of good quality data. Building an effective auto-routing AI solution requires having a large database of historical data associated with processes that have not undergone any recent significant changes (e.g. a decision made two weeks ago escalate certain incidents to another office or the formation of a new team). The AI uses this data to learn and eventually predict which tickets go to which teams. Once the historical data is integrated and the technology is deployed, the next step is to change the mindset of the impacted teams. Once the data is retrieved and the technology is deployed, the next step towards successful AI integration requires a cultural shift. Here are three tips to change the mindset of employees in order to allow a good integration of AI. 1) Be aware that, while AI can solve identified and specific problems, it is not a miracle solution. It takes time to learn. This is why expectations of AI must be realistic and start with a small pilot project. to align their imperatives with key indicators. 3) Focus on overall end-user experience rather than technology and features. Based on the comments then collected, consider adapting the parameters. It should always be kept in mind that success is not only about deploying AI technology but also and above all about empowering teams. Throughout the process, steps should be taken to build teams’ confidence in their AI. For example, in the auto-routing use case, start in “recommendation” mode. This gives teams the ability to see the AI-generated prediction. Managers can choose to accept or reject this recommendation. By monitoring the recommendations and comparing them to the usual routing, the teams involved will always be in “control” mode until they have full confidence in the routing ability of the AI. It should always be kept in mind that success is not only about integrating AI and that it is also about empowering the teams. Not only does this improve AI results, but it gives teams and managers time to build their confidence in the technology. By starting with a gradual integration that will show the effectiveness of AI, IT teams will often become AI evangelists. IT leaders will also be more eager to amplify the power of AI across IT organizations. Start your AI journeyWith the predictive intelligence of ServiceNow, teams can start their automatic routing by already connecting to the data generated by their department. This allows IT departments to be more proactive. They improve responsiveness, productivity and enable employee self-service access. And this is only part of the proposed improvements. Predictive Intelligence Workbench supports IT managers in their thinking. They can understand the different use cases and business problems they want to solve, then implement an AI solution that suits their needs. With a little imagination and the right approach, AI enables endless applications and improvements at all levels of the business.