A supplier releases a feature. An employee connects an agent to customer records. An approved assistant gains permission to update information it previously could only read. Each creates a business decision about how much responsibility to delegate.
In OneTrust’s 2026 AI-Ready Governance Survey, 87% of respondents say their organizations encourage agent use. That includes 47% with clear governance and controls and 40% whose capabilities are still developing.
Organizations are moving ahead with agent use. The question is what the business is prepared to authorize alongside it.
Access defines what an agent can reach. Authority defines what it may accomplish with that reach. Evidence gives someone else a basis for deciding whether the work stayed within those limits.
In 2027, those distinctions will become consequential in decisions about which AI capabilities organizations activate and how far they let them go.
Key Takeaways
- AI assurance becomes a commercial gate. Buyers will increasingly expect current, deployment-relevant evidence before activating or expanding consequential AI capabilities.
- An approved agent can still produce an unauthorized outcome. Leading programs will require clearer task boundaries and tested ways to intervene.
- Material AI changes become new assurance events. Leading enterprises will revisit approval when capabilities or operating conditions change, even without a new purchase.
- Customer permission becomes part of the AI conversation. Early implementations will connect customer choices to subsequent processing within individual services.
When Assurance Determines Adoption
A feature is ready, yet the customer waits. The unresolved question may be whether earlier testing covers what the capability can now do. A familiar supplier and an existing contract leave that question open.
“Customers need assurance that reflects the capability they are being asked to use. When functionality changes, earlier testing may leave new questions unanswered. Relevant evidence helps them understand the exposure and decide whether they are comfortable enabling it.”
–Tim Mullen, Chief Information Officer, OneTrust
Only 28% of survey respondents report governance evidence and audit trails, the least common activity listed. That finding raises a practical concern for suppliers asked to demonstrate how a particular deployment is controlled.
We expect buyers of consequential AI-enabled services to place greater weight on current, deployment-relevant evidence during 2027. Missing answers may delay activation or narrow the scope of use.
For suppliers, resolving assurance questions becomes part of getting the capability accepted. For buyers, evidence needs to support a decision about whether to proceed and under which conditions. Its value depends on the uncertainty it resolves.
When Permitted Actions Exceed the Job
Consider an agent tasked with reducing cloud spending while preserving order-processing deadlines. It scales down capacity and postpones batch jobs. Both actions fall within its technical permissions.
The bill improves. Overnight orders miss their deadline.
The agent performed permitted actions whose combined effect breached a condition of the authorized task. A record showing that each action passed its check would leave the business failure unexplained.
This is already an operating concern. In the survey, 48% of respondents report at least one incident involving unapproved actions by AI systems or agents during the past year. Separately, only 5% report clear coordination and accountability across the AI lifecycle.
Those findings describe different issues. Together, they make ownership of delegated work an immediate leadership question.
“The human in the loop cannot be a spectator. They must have the knowledge, skillset, corporate buy-in, critical judgment and courage to challenge the AI, rather than be persuaded by a polished, organized output. Oversight needs to examine whether the purpose is worthy, the direction is correct, and mistakes are being minimized.”
–Odia Kagan, Partner & Co-Chair, Privacy & Data Security, Fox Rothschild LLP
Business owners need to define unacceptable consequences. Reviewers need enough context to recognize them and a workable way to intervene.
We expect leading high-consequence agent programs to make task-specific authority and tested intervention more explicit deployment conditions in 2027. Reliably evaluating the combined outcome of permitted actions remains a harder, emerging practice.
When a Change Reopens the Decision
An approval rests on assumptions about a capability and its use. Another connection can change those assumptions without changing the supplier’s name or prompting a new purchase.
In OneTrust’s research, 39% identify limited visibility into third-party AI components, vendors, or data sources as a delay factor. Separately, 28% say vendor AI tools were adopted before full assessment.
The first finding concerns what teams can see. The second concerns when review happens. Organizations need to address both to recognize when changed work exceeds an earlier decision.
We expect leading enterprises to begin treating material AI changes as new assurance events in 2027. That review should follow the changed exposure and retain evidence that remains applicable.
A new connector may require examination of additional data access. Broader responsibilities may require a business owner to reconsider the task’s limits. If restricting the capability would interrupt a critical workflow, someone also needs authority to decide what can continue.
A change notification begins that process. Accountability requires a decision about what follows.
When a Conversation Changes the Permitted Use
A customer asks an assistant to reserve a coat. During the conversation, they explain that it is a gift and describe the recipient’s preferences.
The details help complete the request. Reusing them for future product recommendations introduces a separate decision about permitted use.
The broader data challenge is substantial: 52% of survey respondents identify data quality, access, privacy, or security concerns as a delay factor. Meanwhile, 39% prioritize better visibility into risk and data use.
These findings reinforce the need to understand what information enters AI workflows and how it is used afterward. Conversations can reveal details a service never asked for, making the limits on subsequent use more consequential..
Where an additional choice is required, the customer’s answer needs operational effect. Declining optional advertising use should change that processing while allowing the reservation to proceed where possible.
We expect early implementations to connect choices with processing within individual services during 2027. Consistent enforcement across providers will take longer. An instruction to an assistant, a technical permission, and legal consent remain distinct.
The leadership task across these decisions is to make authority clear enough to enforce and revisable when conditions change. Trust grows through work that can be examined independently, with someone accountable for the risk that remains.
The 2027 OneTrust Predictions Report, Architecting AI Governance: Blueprints for a Moving Maze, examines how these expectations could shape AI adoption. Read the full report for the forecasts and perspectives from more than 20 experts, with no registration required.
To bring these insights into your next planning discussion, download the practical checklist.
Key Questions for AI Governance Leaders
