STOCKHOLM, SE / ACCESS Newswire / February 24, 2026 / Compliance teams are moving faster with generative AI, but some are also inheriting a new risk: confident-sounding output that cannot be traced back to primary sources. Sorena AI says the gap between helpful drafts and audit-ready execution is widening, and that false confidence can turn into rework, delayed deal cycles, and unpleasant surprises when customers or regulators ask teams to prove completeness.
"In Governance, Risk Management, Compliance (GRC), the output is not a paragraph. It is the evidence trail behind it," a Sorena AI spokesperson said. "If you cannot show your work, you do not have readiness. You have exposure."
The warning comes as organizations face overlapping requirements across cybersecurity, AI governance, privacy, and sustainability, while also trying to shorten the cycle time for customer due diligence, security questionnaires, and audit preparation.
Most organizations do not struggle with GRC because they lack effort or expertise. They struggle because the operating model is structurally inefficient: regulatory updates, customer questionnaires, audits, certifications, and internal reviews arrive continuously, and each one triggers the same cycle of context switching, manual coordination, duplicated work, and last-mile evidence assembly.
Sorena AI says it built its platform to remove that drag by changing where the work happens: humans decide, systems execute. Instead of tracking tasks and deadlines, the company positions Sorena as an execution layer that maps obligations, assembles evidence, produces audit-ready outputs, and keeps claims tied to a verifiable source of truth.
Benchmark results: coverage beats confidence
AI has made it easy to get a fast answer. GRC requires something harder: complete, correct, and auditable execution. In an internal 2026 benchmark, Sorena said it evaluated its Research Copilot against the same requirements used to evaluate a leading general-purpose AI assistant (baseline), using a two-pass scoring process grounded in source documentation.
The results were consistent across tasks spanning privacy audits, AI governance, regulatory timelines, sustainability readiness, employment law, and technical reviews:
Sorena: 100% requirement coverage; 0 factual errors recorded
Baseline: 25% average coverage; 183 factual errors flagged
Sessions: 43 real-world scenarios
**Requirements:** 4,332 granular requirements scored
The real failure mode: fragmentation
GRC is inherently complex. What is avoidable is fragmentation: the information needed to stay compliant is scattered across documents, drives, tools, and inboxes; ownership becomes unclear; timelines misalign; and outputs go stale quickly. The business pays for it: launches slip, sales cycles stall, and audits become disruptive events instead of routine checks.
Traditional GRC tooling improves visibility, but it does not fix the underlying cost center: execution. Most platforms still require teams to manually interpret requirements, find sources, collect evidence, reconcile versions, and package outputs.
Sorena's model: proof-first execution
Most AI tools optimize for fluent output. Compliance demands something else: verifiable output. The most dangerous failure mode in GRC is not being wrong loudly. It is being wrong quietly, when partial coverage looks complete until a customer, regulator, or internal review proves otherwise.
In regulated environments, confidence is not enough. Teams need:
Source-linked evidence (not summaries without receipts)
Paragraph-level traceability (so reviewers can follow the chain)
Repeatable workflows (so the same question does not get answered three different ways)
Security boundaries (so sensitive data stays in the right place)
Sorena's platform is designed to make those requirements the default, not an afterthought.
Sorena says it delivers execution across three pillars:
Research Copilot: multi-agent research with verified output, inline citations, and confidence signals
Assessment Autopilot: end-to-end assessment workflows that produce auditable packages with reviewer routing, policy guardrails, sign-offs, and timestamps
SSOT (Single Source of Truth): a trusted information layer that indexes millions of primary-source documents, refreshes continuously, and links claims back to original sources while keeping private data inside the customer tenant with role-based access control and activity logging
Research Copilot: verified answers with citations you can audit
Sorena's Research Copilot is built for regulatory and compliance work, not generic chat. It is designed to:
Take natural-language questions from security, legal, and compliance teams
Search regulatory libraries, your internal knowledge base, and approved public sources in parallel
Verify claims against trusted documents and return inline citations that point to the original document and paragraph
Provide confidence signals and structured follow-ups to accelerate next steps
Assessment Autopilot: turn questionnaires and frameworks into an auditable package
Assessments are where compliance work becomes expensive because the same requirements repeat across customers, frameworks, and audits. Sorena's Assessment Autopilot streamlines the full pipeline:
Import documents or trusted source URLs
Extract requirements with traceability to the original line
Generate evidence-backed draft answers
Route items to reviewers with fast assignment workflows
Apply policy guardrails and custom rules
Ship an audit-ready package with citations, sign-offs, and timestamps
The result is less rework, faster turnaround, and a cleaner story during audits and customer diligence.
ESG compliance: track evolving EU requirements without losing scope
ESG is expanding fast because voluntary accountability has not been enough, and assurance expectations increasingly resemble financial reporting. Sorena says it helps teams treat ESG as execution, not theater: research requirements with cited output, assess applicability per product and region, generate prioritized action plans, and track evidence continuously across EU and national requirements. The company also argues that AI is not free for the planet, and that computing should be spent on eliminating waste: duplicated research, manual reconciliation, and last-minute rework.
The outcome: trust at the speed of delivery
The compliance bottleneck is not a lack of effort. There is a lack of proof that teams can reuse. Sorena says it is built to turn compliance into a measurable operating capability: evidence that is verifiable, outputs that are auditable, and workflows that do not collapse under deadline pressure.
About Sorena
Sorena AI empowers every team involved in governance, risk, and compliance with AI-powered solutions that deliver verified, cited answers and audit-ready outputs so organizations can move faster with less risk.
Read the full methodology and results in Sorena's compliance benchmarks for modern regulation.
Benchmark note: Results are based on an internal evaluation conducted in 2026. The baseline used a leading general-purpose AI assistant. Results may vary by use case and document types. Sorena does not provide legal advice.
Contact Details:
Company name: Sorena
Email: info@sorena.io
SOURCE: Sorena
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