Companies are increasingly prioritizing artificial intelligence (AI) investments, yet many struggle with achieving the expected returns. While AI adoption is a growing focus, organizations face significant obstacles, including insufficient infrastructure and limited deployment success.
Cisco’s 2024 AI Readiness Index reveals that only 23% of businesses feel equipped with the necessary graphics processing units (GPUs) to handle current and future AI demands. The survey, which included 3,600 senior business leaders from across the Asia-Pacific region, highlighted the gap between ambition and preparedness for AI adoption. Additionally, only 15% of respondents feel fully ready to implement AI-powered technologies, a slight decrease from 17% the previous year. This decline indicates the hurdles companies encounter as they attempt to deploy and capitalize on AI innovations.
The index evaluates six key areas of AI readiness, including strategy, data governance, and organizational culture. Despite these challenges, 98% of businesses in the Asia-Pacific region reported heightened urgency to adopt AI. The primary pressure stems from leadership, with 49% attributing the push to their CEO or leadership team, while 36% felt pressure from their board of directors.
Rising Investment in AI Despite Uncertainty
Companies are allocating substantial resources toward AI, with 50% setting aside between 10% and 30% of their IT budget for AI initiatives. Some even plan to increase their AI spending to at least 40% of their IT budget over the next few years. Half of the organizations surveyed also identified the need to improve their IT infrastructure’s scalability and management as a critical focus.
A significant portion of AI budgets is being directed toward cybersecurity (42%), IT infrastructure (40%), and data management (34%). These investments are aimed at improving operational efficiency, profitability, and competitiveness. However, more than 40% of companies have not seen the expected returns from their AI investments, with some even reporting underwhelming results in areas like process automation and operational assistance.
Dave West, Cisco’s President for Asia-Pacific, Japan, and Greater China, emphasizes that companies must adopt a comprehensive approach to AI implementation. He stresses the importance of modern digital infrastructure to meet the evolving demands of AI workloads and network requirements, such as power and low latency.
Shifting Focus Toward AI Success and Measurable Outcomes
A recent IDC report further highlights the growing demand for AI success, particularly in the Asia-Pacific region. Business leaders now expect an 80% success rate on their generative AI projects by 2027, a significant increase from the current rate of 62%. This shift marks a move from experimenting with AI technologies to embedding AI within core business functions and pursuing measurable outcomes.
IDC predicts that AI will become a key economic driver in the region, with AI spending expected to grow 1.7 times faster than overall digital technology investments over the next three years. This surge could contribute an estimated $1.6 trillion in economic impact by 2027. Additionally, by 2025, 70% of organizations are expected to formalize policies to address AI-related risks, including ethical concerns and the handling of personally identifiable information.
A crucial factor in achieving AI success is access to high-quality data. By 2027, 50% of large organizations in the Asia-Pacific region are expected to adopt data-as-a-product strategies, helping break down data silos and streamline AI applications. However, IDC also predicts that over a third of businesses will remain stuck in the experimental phase of AI by 2026.
Sandra Ng, IDC’s Group Vice President, predicts that 2025 will mark the “AI Pivot,” a shift from experimentation to scaling AI effectively across business strategies. Organizations will need to move beyond isolated pilot projects, adopting structured governance, high-quality data, and scalable infrastructure to achieve meaningful, measurable business outcomes.