The latest IDC report has revealed the top 10 CIO agenda predictions for the Asia Pacific region.
IDC predicts that by 2025, half of the A1000 organizations will face challenges adapting to divergent regulatory changes and evolving compliance standards, which could hinder their market adaptability and AI innovation.
APEJ governments’ rigorous enforcement has led to high-profile cases, creating apprehension among CIOs and potentially delaying digital capability implementation. Compliance measures will vary by location, requiring investments in country-specific data storage tools and localized AI frameworks, increasing cost, complexity, and technical resource needs.
Organizations are advised to establish robust data governance and ethical AI frameworks, collaborate with legal professionals for a multijurisdictional compliance strategy, and adopt agile, automated compliance approaches to address rapidly changing requirements.
By 2025, 70 percent of organizations will formalize policies and oversight to address AI risks such as ethical concerns, brand reputation, and personally identifiable information, aligning AI governance with strategic business goals.
A shift in AI adoption will highlight the need for ethical AI governance, with 41 percent of APEJ organizations prioritizing data governance policies for GenAI usage. CIOs will need to implement robust data governance structures, including data lineage, privacy safeguards, and secure storage for PII, while developing metrics to measure AI’s impact effectively.
Organizations should establish governance frameworks aligning AI models with company principles, legal and ethical standards, and data governance transparency to prevent biases.
An AI review board should monitor projects, prioritize ethical concerns, and employees must be trained and upskilled in AI, automation, and analytics for successful implementation and management.
In 2025, 40 percent of CIOs will focus on high-impact initiatives to address technical debt, aiming to gain a competitive advantage. Over 68 percent of CIOs in the region are adopting modern development tools like integrated development environments, agile DevOps, low/no code, and AI tools to drive modernization and reduce technical debt.
This approach can accelerate development cycles, enabling faster enterprise initiatives and the introduction of new AI features. By minimizing technical debt, CIOs can reduce maintenance costs, manage resources more effectively, and allocate funds toward innovation.
To address these challenges, organizations should balance technical debt management with future investments, build advanced cybersecurity capabilities using AI analytics, and follow best practices in architecture and lifecycle planning to prevent the creation of new technical debt.
In 2026, more than one-third of organizations will still be in the experimental, point-solution phase of AI, with 40 percent needing to refocus on enterprise use cases to achieve ROI.
In the region, only 3 out of 24 GenAI proof-of-concepts reached production in the past 12 months, largely due to unclear direction and isolated use cases that do little for business growth.
Scaling AI will require smooth integration with existing IT infrastructure, legacy systems, and data architectures, presenting technical challenges and increasing complexity. The shift to enterprise AI will also raise demand for specialized talent, potentially creating a skills gap.
To move AI into production effectively, organizations must build strong vendor relationships, collaborate with line-of-business teams, and hire the right talent. They should invest in workforce development, form cross-functional teams across IT, business, and data science, and develop an integrated data strategy for seamless collaboration. Establishing an AI center of excellence will also be crucial.
Rajani Baburajan
