November 20, 2026 • 4 Min Read
As AI takes on more responsibility across the enterprise, the definition of trust is changing. Here’s what that means for cybersecurity, governance, and the people making it all work.
For years, cybersecurity has centered on a familiar set of questions. Who can access what? Is the data protected? Are the right controls in place?
Those questions still matter. Now there’s another one worth asking: What happens when technology starts making decisions and taking action on our behalf?
AI is moving beyond generating content and answering questions. It’s accessing systems, analyzing sensitive information, triggering workflows and, increasingly, completing tasks with limited human involvement.
That’s opening up new possibilities for businesses. It’s also changing what it means to trust the technology running them.
As CIOs, CTOs and CISOs look toward 2027, cybersecurity and AI governance are becoming more closely connected than ever.
Trust Is Getting a New Job Description
According to the World Economic Forum’s Global Cybersecurity Outlook 2026, 87% of respondents identified AI-related vulnerabilities as the fastest-growing cyber risk during 2025.
Organizations are paying attention. The same research found that the share of organizations assessing AI tools for security increased from 37% to 64% in just one year.
And the conversation is expanding beyond protecting systems and data.
Consider an AI agent that can retrieve customer records, update information in an ERP or initiate a financial transaction. The organization needs to understand what that agent can access, what it’s authorized to do, and how its actions can be monitored.
That brings identity, permissions, and accountability into a much broader conversation.
An AI agent may have access to the right system. Whether it should take a particular action is another question entirely.
When AI Starts Making Moves
The distinction between AI assistants and AI agents is becoming increasingly important.
An assistant might help an employee draft a report. An agent could gather the information, update records, and distribute the finished report across multiple platforms.
Each additional capability introduces decisions about access, oversight, and responsibility.
Who approves an agent’s permissions? What happens when it encounters something unexpected? Which actions require human approval? And who can step in when needed?
These questions are becoming part of enterprise AI governance: the policies, processes and controls organizations use to manage how AI is developed, deployed and used.
Frameworks like the NIST AI Risk Management Framework provide a foundation for identifying, measuring and managing these risks.
The practical challenge is applying those principles across systems, departments, and workflows that are constantly evolving.
People Still Have a Pretty Important Role
As AI takes on more work, the role of human judgment becomes more specific.
A routine data update may need automated monitoring. A financial transaction above a certain threshold may require approval. A decision affecting an employee or customer may call for closer human review.
The right level of oversight depends on the action, its consequences, and the organization’s risk tolerance.
This is also where human-centered design plays a meaningful role.
Understanding how employees interact with AI helps organizations design clearer approvals, more useful alerts and practical ways to review or override automated decisions.
The experience matters. A human approval step is only useful when the person has enough information, context, and authority to make the decision.
RGP’s 2026 AIxHuman research highlights the growing relationship between AI productivity, human expertise and the organizational decisions that shape results.
As AI becomes more autonomous, designing how people and technology share responsibility will be an important part of earning trust.
Five Questions Worth Asking Before 2027
As cybersecurity and AI governance strategies evolve, these questions can help technology leaders evaluate where they stand.
- Do we know what AI can access and do?
Look beyond the tools themselves to their permissions, integrations, data access and ability to take action.
- Who’s accountable for AI-driven decisions?
Establish clear ownership for automated processes, including who monitors performance and handles exceptions.
- Where does human judgment belong?
Identify decisions that require review, approval, or intervention based on their potential business impact.
- Can we see what happened?
Consider how AI activity is logged, monitored, and investigated, particularly when agents operate across multiple systems.
- Are our governance practices keeping pace?
Review policies and controls as AI capabilities, business requirements and regulations evolve.
Trust Is Something You Build Into The Work
Cybersecurity and AI governance will continue to evolve as technology becomes more capable and connected.
For CIOs, CTOs and CISOs, 2027 brings an opportunity to think more broadly about trust: who has access, what technology is authorized to do, how decisions are made and where people remain accountable.
That means bringing security, governance, technology, and business teams into the same conversation.
Because as AI takes on more responsibility, knowing what it can do is only part of the equation. Knowing what it should do, and who’s responsible when it does, is where trust really begins.