Organizations across the Asia-Pacific, Japan, and Greater China (APJC) regions are racing to keep up with the demands of artificial intelligence, but many are finding themselves unprepared for the challenges ahead. The Cisco’s 2024 AI Readiness Index, unveiled this week at Cisco Live APJC in Melbourne, paints a stark picture: while the desire to harness AI’s potential is at an all-time high, the reality is that many organizations are struggling in several key business areas.
A Region of Early Adopters and Growing Challenges
I was curious to see the results of the APJC study as that region tends to be an early adopter of emerging technology. At the event, Dave West, GM of APJC for Cisco, described the region as being Cisco’s “canary in a coal mine” as often the first use cases of emerging technology come from there. I was looking to see if the combination of excitement and trepidation found in other regions would hold true there and that appears to be the case.
Cisco surveyed 7,985 senior business leaders globally, including 3,660 in APJC. These leaders are responsible for AI integration and deployment at organizations with 500 or more employees. To determine overall readiness, Cisco assessed AI readiness using six pillars: strategy, infrastructure, data, governance, talent, and culture.
High AI Investment, Low Returns
Many organizations are eager to adopt AI, with nearly half dedicating 10 to 30 percent of their IT budgets to AI projects. However, these investments are not yielding the expected returns. More than 40 percent of the respondents reported minimal improvements in automating or streamlining their processes despite substantial spending. The findings suggest organizations struggle to turn these investments into meaningful operational gains.
Pressure to adopt AI primarily comes from company leadership, with 50 percent of organizations citing their CEOs and executive teams as the main drivers. Yet, support at the senior level appears to be waning. Enthusiasm among leadership teams has dropped to 75 percent from 82 percent last year. The decline in support is even more pronounced among middle management and employees, with nearly a third of organizations reporting resistance or reluctance from their staff to adopt AI.
Organizations are better prepared strategically, with many prioritizing AI for cybersecurity, IT infrastructure, and data management. For example, 42 percent of organizations have made significant progress in deploying AI for cybersecurity, while 40 percent focus on infrastructure improvements and 34 percent on enhancing data management capabilities.
Data Management Struggles and Fragmentation Issues
The challenges extend to data management. Only 31 percent of organizations feel well-prepared to leverage data for AI initiatives. Many are grappling with fragmented data systems, with 82 percent experiencing issues centralizing and accessing data across their organizations. This fragmentation impedes AI integration, as most companies lack fully unified data systems.
Governance is also becoming more challenging as regulations change. The introduction of the EU’s AI Act in August 2024, along with new guidelines in countries like Japan, South Korea, and Australia, has forced organizations to rethink their AI policies. Still, less than a third of organizations report having comprehensive governance frameworks.
Talent Gaps and Rising Costs of AI Expertise
Another pressing issue is the talent gap. Only 31 percent of organizations feel confident in their talent readiness, and nearly a quarter admit not having the necessary in-house expertise to deploy AI effectively. Many are turning to contractors to fill these gaps, with 46 percent opting for short-term external support. However, competition for skilled AI professionals has driven up costs, with 53 percent of leaders citing rising expenses as a main hurdle.
The Cultural Shift Needed for AI Integration
Despite these setbacks, the urgency to adopt AI is greater than ever. Most organizations (98 percent) have felt pressure to deploy AI technologies over the past year. Nevertheless, only 28 percent have fully developed change management plans to guide cultural shifts needed for AI integration. Meanwhile, 62 percent are still working on them. The lack of a clear strategy might explain why cultural readiness has declined, with the number “chasers” dropping from 44 percent to 32 percent, and “laggards” increasing to 15 percent.
In this race to embrace AI, organizations recognize they are running out of time. Many believe they have a year or less to implement effective AI strategies before losing their competitive edge. Therefore, it’s important to overcome obstacles in infrastructure, data management, governance, talent, and culture or risk falling further behind as AI evolves rapidly.
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