As Earth Day 2026 (April 22) unfolded under the theme “Our Power, Our Planet,” conversations across Asia-Pacific pivoted sharply from carbon accounting to tangible carbon action. Yet this shift occurred amid intensifying geopolitical fractures and socioeconomic pressures that continue to test the resilience of governments, businesses, and technology leaders.
The World Economic Forum’s Global Risks Report 2026 identified geoeconomic confrontation as the top near-term risk, followed closely by interstate conflict and extreme weather. In Asia, these risks manifest in ongoing Taiwan Strait tensions, border frictions (such as Thailand-Cambodia), and broader supply chain disruptions from Middle East conflicts and U.S.-China dynamics.
UNESCAP’s Economic and Social Survey of Asia and the Pacific 2026 notes that while the region maintains faster growth than the global average, deepening geopolitical conflicts and trade fragmentation are complicating sustainability efforts.
Geopolitical headwinds are reshaping Asian priorities
Economic uncertainty and resource competition have amplified the stakes for sustainability. Climate pressures—intensifying pollution, water stress, and extreme weather—intersect with energy security concerns, as nations seek reliable renewable sources amid volatile fossil fuel markets.
Governments in Southeast Asia are ramping up Earth Day campaigns linking everyday behaviours to national climate goals, even as domestic political tensions (e.g., protests in Indonesia and the Philippines) and infrastructure scandals test public and investor confidence.
For businesses, this fluid environment demands agile IT strategies. CIOs are orchestrating responses that prioritise resilience: diversifying supply chains, investing in sovereign AI and cloud infrastructure, and embedding risk governance into digital transformation.
Forrester’s 2026 Asia Pacific Predictions highlight that sovereignty will shape AI infrastructure choices for half of firms, with “diverse cloud” strategies blending hyperscalers to navigate geopolitical uncertainty.
Gartner and IDC reports similarly underscore a pragmatic turn: AI investments are accelerating (projected to grow significantly faster than overall digital spending in APAC), but with stricter demands for measurable ROI, governance, and alignment with sustainability.
Agent sprawl: A threat to net-zero progress
In this context, the explosive growth of autonomous AI agents poses a unique challenge. Uncontrolled “agent sprawl”—the proliferation of ungoverned AI agents—threatens to exponentially increase compute, data storage, and energy consumption, directly undermining net-zero pledges.
Liher Urbizu, president and MD of Southeast Asia, SAP acknowledged the dual nature of AI adoption:
“What we hear is that the bulk of our customers understand the potential of AI. And they are actively pursuing strategies to implement AI. Yet there are risks associated with deploying AI. The first one is shadow AI… The third one is, as you well mentioned, the agentic sprawl.” Liher Urbizu
He emphasised interconnected risks: shadow AI leading to data leakage and uncontrolled agents accessing data without proper governance. “Our answer to that is it has to be governed, it has to be controlled, and it has to be made use of in a perfectly auditable way, and that can be traced. And when you do that, then you can get the best of AI without the risks of AI,” he continued.
Embedding carbon-aware policies into agent workflows
True sustainability, Urbizu argued, requires treating carbon data with the rigour of financial data. SAP’s Green Ledger exemplifies this by tracking sustainability impacts at the transaction level across supply chains.
Responding in the affirmative to the question of the possibility of embedding carbon-aware policies into sustainability initiatives, Urbizu added: “SAP has made a very big bet on sustainability because it is at the core of our DNA.”
SAP recently launched five new sustainability agents at Sapphire 2026, including a Footprint Optimisation Agent that identifies emissions hotspots and a Sustainability Regulatory Readiness Agent for audit-ready reporting. These tools help counter the energy demands of sprawling agents while driving down energy use.
Urbizu stressed Scope 3 emissions visibility: “You have to look at the entire supply chain… our agents access supplier data… through the business network… [and] talk to non-SAP agents” via open APIs, all while maintaining ISO-compliant governance and auditability.
Data governance and human oversight as foundations
Poor data quality fuels redundant processing and energy waste. Urbizu highlighted the importance of metadata for context: “Data in itself is not enough. You need data, and you need the metadata surrounding the data.”
Agents must operate with human-in-the-loop supervision.
“Every decision made by an agent must be human-supervised. The ultimate decision maker should be a human… You want to understand what decision the agent is making, why… what are the data sources… and the reasoning.” Liher Urbizu
For decommissioning low-value agents, he pointed to tools like LeanIX for asset management and integration with HR systems (SuccessFactors) to treat agents as “digital coworkers” with clear lifecycles.
This aligns with broader APAC CIO sentiment. In a FutureCIO discussion on 2026 priorities, Gartner VP Analyst Owen Chen urged leaders to embed governance: “CIOs must move beyond experimentation to embedding AI as a core competency.”
Another FutureCIO piece on mitigating AI costs quoted industry voices emphasising “robust data governance, cybersecurity, and workforce readiness” for sustainable success.
Starting points for SAP customers and beyond
For organisations on SAP S/4HANA or exploring the ecosystem, Urbizu advised tailored roadmaps. Cloud-native users can activate embedded AI features quickly, while on-premise setups should prioritise phased migration, beginning with sustainability modules. “The value of public cloud… is that we’re… democratising the access to AI… for sustainability,” he noted, benefiting enterprises and SMEs alike.
Industry groups reinforce this. IDC stresses ecosystem strategies for AI governance and outcome-based services, while Forrester warns against performative shifts and advocates pragmatism over hype.
Charting a responsible path forward
As Asia grapples with overlapping crises—geopolitical realignment, climate urgency, and AI proliferation—CIOs emerge as orchestrators of balanced progress. By governing agent sprawl, embedding carbon awareness, and ensuring auditable, human-supervised decisions, technology leaders can align AI acceleration with planetary boundaries.
Urbizu’s closing optimism resonates: SAP agents are built “in compliance with ISO standards… perfectly governed by our authorisation control system and our audit and traceability system.” In 2026 and beyond, true leadership lies not in unchecked innovation, but in purposeful, sustainable intelligence.
Click on the PodChats player to hear more about how CIOs are embedding genuine carbon action in the age of autonomous AI.
- Give us the agentic sprawl in Southeast Asia in 2026.
- How do you embed “carbon-aware” policies directly into agent workflows? This should force autonomous agents to defer non-urgent batch processing to times when renewable energy is available.
- With Earth Day commitments tightening, what technical controls are required to mandate energy consumption caps per agent, treating efficiency as a governance rule rather than a post-execution report?
- To ensure agents don’t inadvertently increase waste, how do you establish trusted data lineage for Scope 3 emissions, enabling an agent to verify a supplier’s carbon intensity before autonomously placing an order?
- Given that poor data quality leads to redundant processing, what data governance rules are necessary to prevent agents from repeatedly querying or transforming the same inefficient datasets, wasting energy?
- How do you build a “sustainability audit trail” for every autonomous decision, allowing CIOs to trace a specific agent’s actions back to their energy costs and carbon footprints for regulatory reporting?
- As we manage agents like digital coworkers, what “retirement criteria” ensure that low-value, high-frequency agents are automatically decommissioned to prevent long-term energy leakage? (leanIX)
- To avoid “shadow agent” sprawl doubling your infrastructure emissions undetected, what discovery tools can catalogue every autonomous agent and calculate its real-time energy consumption against your Net Zero milestones?
- With stakes higher than Shadow IT, how do you differentiate between essential agents that optimise sustainability (e.g., logistics routing) versus “rogue” agents that create unnecessary digital waste and technical carbon debt?
- Where is the starting point for my organisation to move towards a more sustainable IT operation?
