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11/07/2026 8:30 pm
TL;DR: AI adoption is expanding across productivity, customer engagement, and security use cases, while the same research says 27% of executives are already investing in AI-enabled cybersecurity and 75% of companies use AI in network security, according to GlobalSign-cited survey findings. The governance problem is no longer whether AI matters, but whether identity, access, and monitoring controls can keep pace with how fast it is being embedded into operations.
NHIMG editorial — based on content published by GlobalSign: 15 AI statistics and trends shaping 2023
By the numbers:
- The 64% of companies believe AI will play a fundamental role in improving overall productivity.
- According to research, AI is already used in more than 75% of network security solutions in the global enterprise landscape.
Questions worth separating out
Q: How should security teams govern AI workflows that use service accounts and API keys?
A: They should treat each workflow as a governed identity, not as a standalone model.
Q: Why do AI tools create new identity and access risks for enterprises?
A: Because the tool itself rarely acts alone.
Q: What breaks when AI governance is separated from IAM?
A: Ownership becomes fragmented and revocation becomes slow.
Practitioner guidance
- Inventory every AI-connected identity Catalogue service accounts, API keys, tokens, delegated permissions, and connector accounts used by AI tools across production and test environments.
- Apply least privilege to AI workflows Reduce connector scope to the minimum data set and action set required for each use case.
- Define approval points for AI-assisted actions Require human approval for AI outputs that can change access, terminate sessions, modify records, or trigger security response.
What's in the full article
GlobalSign's full article covers the statistical breakdown and source-by-source trend details this post intentionally leaves at the summary level:
- The original survey citations behind the market-size, productivity, and security adoption figures.
- The Spanish-language commentary and framing around AI adoption, consumer concern, and workplace impact.
- The full list of 15 statistics, including the Capgemini, Brouton Lab, and Free Agent references.
- The article's closing interpretation of what the 2023 AI trend landscape suggests next.
👉 Read GlobalSign's statistics roundup on 2023 AI adoption and security trends →
AI adoption is outpacing governance controls, but where do teams start?
Explore further
11/07/2026 8:59 pm
AI adoption is creating identity governance debt faster than most programmes can absorb. The article’s numbers show scale, but the real issue is control drift: AI tools are being inserted into workflows before owners have defined access boundaries, data scope, and audit expectations. That is not a model-quality problem alone, it is a governance problem across IAM, NHI, and AI operations. Practitioners should treat every AI workflow as an identity-bearing system from day one.
A question worth separating out:
Q: Which controls matter most when AI is used in security operations?
A: Prioritise identity scope, logging, and approval boundaries. AI-assisted triage can improve response speed, but actions that change containment, access, or configuration should remain reviewable by a human. The control goal is to preserve auditable decision chains, not to remove judgement from the loop.
👉 Read our full editorial: AI adoption is outpacing security governance models
