How are businesses to adapt to technological shifts, including artificial intelligence and the subsequent needs for improved security?
To learn about these possible shifts, Digital Journal heard from Benoit Grange, chief product and technology officer, Omada.
Identity sprawl will remain a major risk in 2026
On the subject of identity theft and related issues, Grange finds: “With organizations struggling to govern an expanding mesh of digital identities across human, machine, and AI entities, over-permissioned roles, shadow identities, and disconnected IAM systems will continue to expose organizations to credential-based attacks and lateral movement.”
Considering the impact of AI is central to addressing these risks, Grange points out: “AI will also reshape traditional social engineering: synthetic voices, deepfakes, and adaptive phishing will erode the reliability of static authentication, forcing organizations to adopt continuous and context-aware verification as the new baseline.”
Autonomous agents will force identity governance to evolve
Is governance fit for purpose in the world of advanced technology? Possibly not. Here Grange predicts: “Healthcare, financial services, and critical infrastructure will remain top targets, as data sensitivity, legacy systems, and cross-border dependencies amplify risk.”
Some economic sectors will be hit harder through the technological wave. The ones most likely to be affected are: “The most transformative shift will be in industries rapidly adopting AI-driven automation, from finance to logistics, where autonomous agents increasingly handle operational tasks, compliance workflows, or even access decisions. These environments will demand identity governance at machine speed.”
MCP will become the backbone of a new digital trust fabric
Grange explains how one approach can offer businesses improved security: “2025 showed us what happens when autonomy outpaces accountability. AI systems began acting across business processes with little visibility into who or what was making decisions. This exposed a critical gap: governance frameworks built for human users are insufficient for autonomous agents acting at runtime.”
The Model Context Protocol (MCP) is an open standard, open-source framework intended to standardise the way AI systems like large language models integrate and share data with external tools, systems, and data sources.
As to the proposed solution: “At the same time, the Model Context Protocol (MCP) emerged as a promising foundation for secure collaboration between AI systems defining how agents exchange context, identity, and authorization in real time. This could be the backbone of a new digital trust fabric.”
