As featured on BusinessMirror: AI is helping revolutionize risk management
AI isn’t just evolving risk management — it’s helping reengineering it. Artificial intelligence (AI), including generative AI (Gen AI) and agentic AI, is driving a seismic shift in how organizations anticipate, assess, and act on risk. The old playbook of manual processes, backward-looking assessments, and fragmented frameworks is being replaced by intelligent systems that learn, adapt, and act in real time. According to the KPMG Future of Risk Survey, 400 executives rank AI and Gen AI as by far the most popular type of technologies for managing additional risk responsibilities in the next three to five years.
Risk teams have been using AI, such as automation and advanced data analytics tools, for various tasks for many years. In fact, 98 percent of respondents to the KPMG Future of Risk Survey said that digital acceleration such as AI and advanced analytics has already improved their approach to risk identification, monitoring, and mitigation. Looking forward, today’s risk leaders see massive potential in moving beyond the basic AI tools at their disposal to take advantage of the latest AI advancements, including Gen AI, to surface deeper risk insights, automate workflows, and turbocharge risk managers’ efficiency and productivity.
What separates the leaders from the laggards is how smartly, and boldly, they embrace and embed AI advances into their risk operations. Many are experimenting with “point-in-time” solutions — automating the edges or single step activities while leaving the core untouched. But the real opportunity lies in embedding connected AI solutions across the risk lifecycle, flipping the pyramid from productionheavy to decision-driven, and preparing for a future where agentic AI operates with minimal human oversight and humans spend more time on analyzing results, actively managing risk, and strategic imperatives.
The five stages of AI maturity in risk management
Impact can increase in risk management as AI capabilities mature, becoming transformative.
- Stage 1: Prototype – Organizations explore the use of automation, ML or AI but not in full production
- Stage 2: Siloed – Point solutions in production focused on single activities within risk which may or may not be connected to the organization’s governance, risk, and compliance.
- Stage 3: Integrated – Connected solutions for end-to-end activities within risk which are connected to GRC with human-in-the-loop for key decisioning.
- Stage 4: Agentic – End to end solutions in production focused on key processes within risk which are automated
- Stage 5: Transformative – Fundamental transformation in approaches to the risk framework and methodologies which replace tradition methods used today.
As organizations race to launch AI-powered products, they’re hitting a wall of internal friction: new product approval reviews, model risk requirements, and compliance hurdles that slow innovation to a crawl. Ironically, AI is both the accelerator and the constraint.
This duality is reshaping the risk function. AI can dramatically reduce costs, automate compliance, and surface hidden insights. But it also introduces new risks that demand a new kind of oversight. Risk teams must now manage the risk of AI in and of itself.
In the Philippine Context
In the Philippines, organizations are beginning to leverage AI to transform how they manage risk and safeguard operations. Major telecom providers, for example, are leveraging automation and data analytics to monitor network traffic, detect fraud, and prevent service disruptions. These early-stage applications, often focused on operational tasks, show how AI can enhance risk identification and real-time monitoring, laying the foundation for more integrated, predictive, and decision-driven risk management systems.
As this shift takes place, risk teams are moving beyond process management toward enabling better, more informed decisions. Organizations that integrate AI with strong governance and clear accountability will be better equipped to manage uncertainty and build resilience.
This excerpt was taken from the KPMG Thought Leadership publication “AI is helping revolutionize risk management”.
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This article is for general information purposes only and should not be considered as professional advice to a specific issue or entity. The views and opinions expressed herein are those of the author and do not necessarily represent KPMG International or R.G. Manabat & Co.