Business leaders consider the implementation of AI as a solution for all enterprise-related issues, including automation of workflows, chatbots, a good understanding of clients, etc.
IT leaders state that implementation of AI boosts help desks’ productivity and systems’ performance. In a recent survey conducted by Interop, ITPro, and InformationWeek, 64% of the respondents state that their organizations have implemented at least 1 AI-based project. They state that the implementation has resulted in good to very good results.
Analyzing the characteristics of successful AI leaders, 54% use AI for predictive maintenance, 50% use it for Supply chain and inventory optimization, and 50% for manufacturing analytics as stated by zdnet.com. By implementing AI-based applications, IT leaders hope to see benefits like better product support, customer experience, more efficient IT operations, and improved cybersecurity measures.
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IT leaders state that when implementing AI tech, security is the biggest concern. The level to which the AI algorithm is available to the technology users, also known as the model transparency is the second cause of concern. A high degree of transparency helps to reduce bias and elevate system trust. However model architecture can be breached, making the system and network vulnerable to attacks.
CIOs state that cybersecurity has improved along with productivity and customer support. AI-based tools are used for predictive analytics, which helps the systems to make better decisions, manage demand planning, improved incident response, and management. The tools have been implemented for intelligent and efficient search suggestions and as chatbots for the help desk.
CIOs believe that while organizations require AI to better productivity, there is a shortage of resources trained in AI skills. IT leaders state that the resource pool faces a shortage of data modeling and machine learning skills along with infrastructure skills.
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Most IT leaders wish to implement specific AI tech like Deep Learning, intelligent robotic automation, and machine learning as part of core competencies. CIOs state that AI projects take time to be successfully implemented. Typically an AI project requires a minimum of 6 months to 1 year for successful and effective implementation. In a survey conducted by Zdnet.com, 25% of the respondents stated that AI projects went over budget, while 45% stated that the project cost was within the budget. Now for organizations that deployed less successful AI projects, 40% stated that their projects resulted in crossing the budget. A mere 21% of respondents stated that the project took less than 6 months while 32% stated that the implementation took just over a year.
