Way back, Artificial Intelligence (AI) was just a side experiment, but now? — it is one of the boardroom-level investment priorities.
A recent study entitled “Lenovo CIO Playbook 2026: The Race for Enterprise AI”, with insights from the International Data Corporation (IDC), found that 96% of enterprises across the Asia Pacific Region plan to increase AI spending by an average of 15% this year. In ASEAN+, including the Philippines, that number rises up to 98%
For business leaders such as Chief Financial Officers, Chief Information Officers, and Risk Officers, this raises a critical question: Are you investing in AI and strategically governing it?
The AI Investment Surge is Real, and It’s Accelerating
Organizations are presently investing in:
- Generative AI (GenAI) & Agentic AI
- Public cloud AI services
- AI security and trust tools
- Data governance and quality improvement
- AI integration with existing enterprise systems
Hence, in ASEAN+, the top investment priority is particularly for AI integration with devices, infrastructure, and enterprise systems. Thus, it reflects a pragmatic regional approach, embedding AI directly into legacy environments to extract value quickly and benefit operations.
For Philippine enterprises, this means that AI is no longer a “tech initiative”. Rather, it is becoming part of core infrastructure, integrating finance, customer service, marketing, operations, and even compliance systems.
From Experiments to ROI: Expected Measurable Returns
Furthermore, the study revealed that 91% of ASEAN+ organizations expect positive Return on Investments (ROI) from AI scaling. Some of the reported areas of measurement include:
- IT and data analytics
- Cybersecurity
- Customer service automation
- Software development
- Operational efficiency
Also, a much more compelling reason is that enterprises are estimated to generate an average of $2.70 billion in total value for every $1 invested in AI.
But aside from the captivating numbers and compelling anticipated results, there are still nuances that must be acknowledged & ultimately resolved: around 67% are piloting or systematically adopting AI, 15% are still at an early stage, and roughly 18% are still considering adoption.
And when it comes to agentic AI or autonomous AI systems capable of independent decision-making, around 43% of enterprises need more than 12 months before adopting, while only 11% say they are prepared now.
Indeed, scaling up is the real challenge for enterprises.
AI Investment Without Governance Is a Risk Multiplier
As enterprises increase spending, AI governance serves as the moderator.
In ASEAN+, 39% of enterprises have an established comprehensive AI governance framework, while 44% are still developing policies. Their major concerns are primarily due to a lack of responsible AI controls, Poor data security, and poor quality.
With this, it reveals where many organizations face a silent exposure:
- AI tools deployed without internal control mapping
- Data used without thorough quality validation
- Hybrid cloud workloads without compliance monitoring
- Finance teams are using AI outputs without appropriate audit trails
For CFOs and compliance managers, this has serious implications for internal control, cybersecurity exposure, data privacy vulnerabilities, and the reliability of financial reporting.
On the other hand, in the Philippines and across the ASEAN+, regulatory bodies are strengthening expectations involving governance, risk, and transparency. AI adoption without proper policies may create compliance problems rather than being a competitive advantage. Additionally, the region’s strong preference for hybrid cloud, at around 70% among enterprises, reflects both promptness and governance maturity, which can be considered a balance between innovation and risk management.
Overall, AI readiness in the present is not defined by how fast you deploy, but by how well you control it.
Moving From Adoption to Accountability
Without a doubt, Asia-Pacific Enterprises are entering the execution phase of AI, wherein spending is increasing, expectations are rising, and returns are measured.
Yet, for a successful scaling up of AI, it requires:
- Well-established Governance frameworks
- Risk and compliance alignment
- Infrastructure readiness
- Data quality discipline
Here at Babylon2k, we see a clear shift: The majority of enterprises are no longer asking, “Should we adopt AI?” — they are rather asking, “How do we expand and use it responsibly?”
For accountants, finance leaders, and business owners, the next step is not more tools — but structured governance. To help you out as a leader, some of the key questions your organization should be asking are the following:
- Do we have an AI governance framework aligned with our risk management?
- Are AI-driven financial outputs subject to internal audit controls and monitoring?
- Is our data governance structure AI-ready?
- Do we have board-level oversight on AI strategy?
- Are we prepared for regulatory review of AI-enabled processes?
AI investment without accountability can erode trust, but with governance in place? — It builds sustainable enterprise value.
Need guidance on AI governance, risk controls, or enterprise compliance alignment? — Book a consultation with us!
Babylon2k supports businesses in building structured, accountable, and regulator-ready AI strategies. Let’s ensure your AI investments create measurable value, not unmanaged risk.
Reference: Business World – Asia Pacific Enterprises Plan to Increase AI Investments
