Boomi: AI Agent Governance and Why it Can't Wait
The explosive global growth of AI agents has created a governance vacuum that threatens both business operations and ethical standards across the world.
From financial to healthcare services, organisations are deploying AI agents at unprecedented rates, yet governance frameworks remain underdeveloped or entirely absent in most regions and sectors.
Rapid proliferation of AI agents across industries is outpacing management strategies.
Gartner estimates that 33% of enterprise software applications will include agentic AI functionality by 2028.
Deloitte also reports that 26% of organisations are exploring autonomous agent development.
What’s behind this boom in AI agents?
The chance to automate tasks that have escaped automation so far and to dramatically streamline workflows, unleashing dramatically improved productivity across organisations.
AI agents, which can often be built within a few hours or even minutes, bring the power of AI to everything from customer interactions to financial decision-making.
But as AI agent implementation increases, leading to agent sprawl and exacerbating digital complexity, one pressing question remains: how can we achieve governance for AI agents so that their benefits aren’t outweighed by their risks?
Looking into this urgent matter, Boomi offers these insights and solutions for enterprises.
The dilemma of unmanaged AI agents
Boomi, a leader in AI-driven automation, points out that unmanaged agents pose risks such as security vulnerabilities, compliance issues and unclear lines of responsibility.
The deployment of autonomous and semi-autonomous AI agents without proper oversight introduces multifaceted risks that transcend national borders and industry sectors.
When agents operate with open system permissions or handle sensitive data without appropriate guardrails, they create security risks that cybercriminals can exploit for costly data breaches.
AI agents acting on their own brings up even more concerns such as rogue agents, unintended consequences, bad business decisions and the difficulty of explaining agent decisions.
Without clearly defined lines of accountability that respect company policies, local regulations and international standards, organisations risk creating blind spots where no one takes responsibility for AI-driven outcomes.
The keys to AI transparency and trust
While there are challenges surrounding AI agent governance, businesses can follow core principles to ensure that they are implementing AI responsibly.
Build governance into the complete AI agent lifecycle
Governance should be intrinsic to each phase of the AI agent lifecycle, from development to testing to deployment and monitoring.
An organisation should be able to control who has permission to develop agents and what data, applications and services those agents can access, based on the company-wide access rights of the developers and end users.
To make it easy for developers to build agents that automatically comply with security policies and other mandated rules, a company can provide an agent development platform that supports composable architectures (software architectures with reusable components) and rules that can be applied automatically to agents.
Governance tools should also be in place for deploying agents, so that agents only run in environments where they’re authorised.
Centralise visibility for all agents across the organisation
Most organisations will soon have hundreds, thousands, or even more agents running in their IT environments.
Some will be internally developed; others will be purchased from software vendors or consultancies.
To ensure all these agents are well governed and compliant, it’s essential to have centralised visibility into their status and activity.
With a single, comprehensive dashboard for monitoring agents and logging their activity, stakeholders ranging from CISOs to business leaders can see which agents are active, what their security status is, how well they are performing, which tools they are accessing and whether they need to be disabled and repaired because of any software errors or compliance risks.
AI agent documentation for global compliance
Documentation requirements represent a critical governance component with international dimensions.
Organisations need comprehensive records of AI agent development, deployment decisions and operational parameters that satisfy regulatory requirements across all jurisdictions where the systems operate.
Keeping AI records improves transparency in global AI governance and allows organisations to explain how their AI agents operate and make decisions to stakeholders in every market they serve.
This documentation should be centralised, so stakeholders ranging from security teams to auditors can easily see which agents took which actions and why.
This transparency builds trust with users, customers and regulators worldwide.
International collaboration
The discussion around AI agent governance extends beyond individual organisations to industry and regulatory bodies across multiple continents.
Several international groups, including the OECD and IEEE, are working to develop standards and frameworks that could help establish common practices across sectors and borders.
While each organisation and region has unique requirements, certain governance principles apply universally.
Therefore, working together across national and sectoral boundaries can help develop frameworks that protect against common risks while allowing for necessary customisation to local conditions.
Human-in-the-loop oversight
Perhaps most importantly, keeping humans informed, educated and ’in-the-loop’ about relevant AI development achieves AI governance on a deeper level.
Combining autonomous governance with human oversight is particularly important for high-risk decisions.
Establish escalation protocols and audit trails to ensure accountability while maintaining operational efficiency.
Another way to keep AI agents and humans aligned and updated is dynamic policy adaptation.
Implement frameworks that update governance rules in real time as regulations evolve or AI models learn.
Boomi Agentstudio as an AI agent lifecycle management solution
Effective management of AI agents is not just about minimising risks and aligning with compliance standards; it also offers benefits including enhanced efficiency and stronger alignment with business objectives.
Boomi Agentstudio is the only full agent lifecycle management solution that empowers organisations to simply design, govern and orchestrate all AI agents at scale.
It integrates governance into the development process from the beginning, rather than treating it as an afterthought.
Boomi addresses AI governance gaps and offers centralised, vendor-agnostic agent management for enterprises looking to scale AI responsibly. But that’s not all.
Complemented by Boomi’s deeply rooted leadership in integration platform-as-a-service (iPaaS), the Boomi Enterprise Platform provides the foundation needed for agentic transformation.
It connects every application, data source, API and AI agent into a single ecosystem where applications work in concert, data is trusted, APIs are governed and secure and every AI agent is centrally governed and fully observable.
Meaning, enterprises can move beyond pilots, modernise workflows and scale AI agent deployments with confidence.