Organisations working with artificial intelligence and machine learning have an average of four projects underway, and plan to add 15 more within the next three years, according to a Gartner survey. The small survey of 106 Gartner ‘Research Circle’ members, found about three in five of the respondents had AI deployed today. By 2022, Gartner predicts the organisations to each have 35 AI-powered applications and projects in place. “We see a substantial acceleration inAI adoptionthis year,” saidJim Hare, research vice president atGartner. “The rising number of AI projects means that organisations may need to reorganize internally to make sure that AI projects are properly staffed and funded. It is a best practice to establish an AI Centre of Excellence to distribute skills, obtain funding, set priorities and share best practices in the best possible way,” he said. The top two use cases for AI currently deployed was to improve decision making and recommendations, and process automation. About a third had a virtual assistant or chatbot, and 14 per cent had embedded AI in products. The most common motivations for rolling out AI was to improve the customer experience and to automate repetitive or manual tasks. Cost reduction and revenue growth were also cited as motivators. “It is less about replacing human workers and more about augmenting and enablingthem to make better decisions faster,” Hare said. Adopting AI comes with considerable challenges, respondent reported. The most common were a lack of skills (cited by 56 pre cent of those questioned), understanding AI use cases (42 per cent), and concerns with data scope or quality (34 per cent). “Finding the right staff skills is a major concern whenever advanced technologies are involved. Skill gaps can be addressed using service providers, partnering with universities, and establishing training programs for existing employees,” said Hare. “However, establishing a solid data management foundation is not something that you can improvise. Reliable data quality is critical for delivering accurate insights, building trust and reducing bias. Data readiness must be a top concern for all AI projects,” he added. Related content brandpost Sponsored by Freshworks When your AI chatbots mess up AI ‘hallucinations’ present significant business risks, but new types of guardrails can keep them from doing serious damage By Paul Gillin Dec 08, 2023 4 mins Generative AI brandpost Sponsored by Dell New research: How IT leaders drive business benefits by accelerating device refresh strategies Security leaders have particular concerns that older devices are more vulnerable to increasingly sophisticated cyber attacks. By Laura McEwan Dec 08, 2023 3 mins Infrastructure Management case study Toyota transforms IT service desk with gen AI To help promote insourcing and quality control, Toyota Motor North America is leveraging generative AI for HR and IT service desk requests. By Thor Olavsrud Dec 08, 2023 7 mins Employee Experience Generative AI ICT Partners feature CSM certification: Costs, requirements, and all you need to know The Certified ScrumMaster (CSM) certification sets the standard for establishing Scrum theory, developing practical applications and rules, and leading teams and stakeholders through the development process. By Moira Alexander Dec 08, 2023 8 mins Certifications IT Skills Project Management Podcasts Videos Resources Events SUBSCRIBE TO OUR NEWSLETTER From our editors straight to your inbox Get started by entering your email address below. Please enter a valid email address Subscribe