Singapore – Only 26% of enterprises say they are well prepared to resolve conflicts between artificial intelligence (AI) agents, systems and automated workflows, despite 82% of executives expressing confidence in their organisations’ ability to govern, integrate and monitor AI agents as deployment expands.
The findings come from research released by OutSystems in collaboration with CIO Dive and KPMG, based on a survey of more than 850 IT decision-makers. The research examines enterprise readiness as organisations move from AI experimentation towards broader deployment of agentic systems.
Over the next five years, 71% of executives expect applications to coordinate work across systems, teams and business processes or support more complex, multi-step workflows.
“82% of executives say they can keep pace with governing AI agents, yet only 26% say they can resolve conflicts between them,” said Tiago Azevedo, CIO of OutSystems.
“That gap is where the real work happens. Having put agents to work across the business, I’ve learned that safety comes from building control into the platform, not reviewing it afterward. Enterprises that enforce policy while agents run will move faster, because they won’t have to stop and ask if they can trust what they built,” Azevedo continued.
Governance remains largely human-led
Although 83% of respondents rely on existing IT, security or compliance processes, specialised reviews, or centralised policies and monitoring to oversee AI agents, only 5% have automated controls, audit trails and formal human review points in place.
The findings suggest that many organisations have established governance procedures but have yet to translate them into automated controls that operate consistently as AI agents execute tasks.
As adoption grows, businesses are also facing the challenge of managing interactions between models, applications, data and third-party tools. Rather than relying on a single vendor, organisations are prioritising integration and flexibility across their technology environments.
Integration with existing applications and systems was identified as a priority by 74% of respondents, while 63% highlighted agent orchestration across systems. Another 62% valued the ability to switch between models, vendors and platforms over time.
Reliability and enterprise data remain priorities
The research highlights the importance of evaluating complete AI workflows rather than testing individual agents in isolation. This includes assessing interactions between agents, handling exceptions and conflicting actions, and establishing rollback mechanisms.
Some 81% of executives said testing, evaluating and validating agent behaviour was very or extremely important when selecting AI platforms or tools.
Data consistency and context sharing were also identified as significant challenges, with 35% of respondents citing them as a major obstacle to agent orchestration. The findings point to the need for AI agents to work with governed enterprise data, application states and established business processes.
“Assurance for agentic systems must be engineered from day one—you cannot simply inspect it after the fact,” said Michael Harper, Managing Director at KPMG.
“Traditional logging and procedural governance were built for static software, not dynamic AI. To bridge the gap between high confidence and true operational readiness, enterprises need the ability to execute policy-as-code and runtime guardrails. That gives businesses the autonomy to innovate while keeping end-to-end workflows secure, reliable, and focused on business outcomes,” Harper continued.
Operational gains outweigh broader transformation
Enterprises are increasingly assessing agentic AI based on its operational impact. Error reduction was the leading measure of success, cited by 64% of executives, followed by compliance and risk reduction, employee productivity and cost reduction.
However, only 12% of respondents said agentic AI had accelerated the launch of new products, services or customer experiences. The findings indicate that organisations are beginning to realise operational benefits, while wider business transformation remains at an early stage.
OutSystems said its Agentic Systems Platform is designed to help organisations build, orchestrate and govern agentic systems across complex technology environments as businesses expand their use of AI.
