Limitations Hinder Wider Usage of AI Despite Growing Enterprise Adoption

According to IBM’s Global AI Adoption Index 2023, approximately 42% of enterprise-scale companies (companies with more than 1,000 employees) have actively implemented artificial intelligence (AI) in their business. Of those companies, 59% have increased their rollout or investments in AI. The expansion of AI at the enterprise level is driven by factors such as more accessible AI tools, the need for process automation, and the integration of AI into off-the-shelf business applications.

Rob Thomas, senior vice president of IBM Software, stated that organizations are leveraging AI in areas where it can have a significant impact, such as IT automation, digital labor, and customer care. While 40% of surveyed companies are still in the early stages of adopting AI, Thomas is confident that they will overcome barriers like the skills gap and data complexity in the coming year.

The top factors driving AI adoption are advances in AI tools, cost reduction and process automation needs, and the increasing integration of AI into standard business applications. Among companies exploring or deploying AI, the most significant investments are being made in research and development and workforce development. For IT professionals, the most important enhancements to AI are easier deployment tools and increased availability of AI and automation skills.

Financial services and telecommunications are the most mature industries in AI adoption. Countries leading in active AI use include India, China, Singapore, and the UAE, while lagging markets include Spain, Australia, and France. The main use case for AI is automation, with areas like IT processes, document processing, and customer self-service being the most common applications. Other areas where AI is being utilized include security, business analytics, fraud detection, and human resources.

The top barriers preventing AI deployment include limited skills and expertise, data complexity, and ethical concerns. Generative AI poses specific barriers related to data privacy and trust. To tackle these barriers, companies should define their AI strategies, ensure data readiness, address skills gaps, and incorporate AI governance from the start.

AI has an impact on the workforce, with some companies struggling to find employees with the right skills. Automation tools are being used to reduce manual tasks and automate customer self-service, while training and reskilling efforts are less prevalent. Trustworthy and governed AI is important, but many companies are facing difficulties in implementing it. Steps such as reducing bias, tracking data provenance, explaining AI decisions, and developing ethical AI policies are crucial.

IBM’s survey was conducted among 8,584 IT professionals in various countries in November 2023.

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