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AI Audit & Discovery Service – Comprehensive Assessment & ROI Roadmap
Most UK enterprises run scattered AI pilots that never scale. Shadow IT, data silos, and undefined governance burn budget while competitors operationalise models into EBITDA uplift. Salyant's AI Audit & Discovery Service maps your entire automation landscape—processes, data readiness, vendor contracts, regulatory exposure—and delivers a prioritised, costed roadmap tied to measurable margin improvement within 90 days.
INSIDE THIS PAGE
What the existing page covers
01
Why UK Enterprises Commission AI Audits Now
02
Four-Week Audit Methodology
03
Deliverables & Success Metrics
CONTINUING DOWN THE PAGE
More of the existing sections
01
Integration with Salyant Embedded AI Partnership
02
Frequently Asked Questions
Key Takeaway for Decision Makers
What does an enterprise AI audit service include and what ROI can UK companies expect?
An enterprise AI audit evaluates current AI usage, data infrastructure, governance gaps, and automation opportunities across operations, delivering a prioritised ROI roadmap with quantified cost savings and revenue uplift targets. UK mid-market firms typically uncover 15-30% process cost reduction and 2-5% revenue lift within first implementation phase.
Grounding Evidence: Based on Salyant delivery framework aligned with ISO/IEC 42001 AI governance standards, UK Government AI Assurance Framework, and benchmarked against 40+ UK enterprise engagements across financial services, manufacturing, and PE-backed portfolios.
Why UK Enterprises Commission AI Audits Now
The FCA's Consumer Duty, EU AI Act extraterritorial reach, and UK GDPR enforcement create compliance liability for undocumented AI systems. Meanwhile, PE operating partners require quantified AI thesis validation before follow-on investment. An independent audit satisfies both: it produces board-ready evidence of controlled innovation and identifies high-confidence automation levers.
Salyant's audit goes beyond tool inventory. We assess model risk classification, data lineage, vendor lock-in exposure, and organisational readiness—mapping each finding to a specific P&L line item. The output is not a PDF; it's an executable implementation plan with resource estimates, timeline, and success metrics agreed with your CFO.
- Regulatory exposure mapping against EU AI Act, FCA Consumer Duty, UK GDPR
- Shadow AI discovery across SaaS estate, custom models, and embedded vendor features
- Data readiness scoring for each high-value use case (completeness, quality, accessibility, licensing)
- Quantified ROI modelling: cost avoidance, revenue uplift, working capital release
- Implementation sequencing with dependency mapping and quick-win identification
Four-Week Audit Methodology
Week 1: Stakeholder workshops (COO, CTO, CISO, Data Lead, Business Unit Heads) to define scope, success criteria, and access requirements. Automated discovery scans SaaS estate, code repos, and data catalogues for undeclared AI components.
Week 2: Deep-dive assessment of 8-12 prioritised processes. Evaluation covers data pipelines, model performance, human-in-the-loop design, monitoring coverage, and vendor contract terms. Each use case scored on feasibility, value, risk, and time-to-value.
Week 3: Financial modelling workshop with finance team. Build bottom-up business cases: compute costs, licence fees, internal effort, risk mitigation spend, and expected benefit realisation profile. Sensitivity analysis on adoption rates and model drift.
Week 4: Board-ready deliverables presentation. Includes executive summary, detailed findings register, prioritised roadmap with 90/180/360-day milestones, resource plan, and governance framework proposal. Optional: implementation kick-off sprint planning.
- Automated discovery tooling reduces manual effort by 60% vs traditional consultancy
- Senior architect-led (not junior analyst) — partners with 15+ years enterprise delivery
- Fixed-price, fixed-scope engagement with clear exit criteria
- Knowledge transfer embedded: your team owns the assessment framework post-engagement
Deliverables & Success Metrics
You receive a version-controlled audit pack: (1) AI Asset Register with risk classification, (2) Data Readiness Heatmap per business function, (3) Use Case Pipeline with NPV/IRR modelling, (4) Governance Gap Analysis against ISO 42001 and sector regulations, (5) 90-Day Implementation Plan with RACI, budget, and go/no-go gates.
Success is measured by: number of production-grade use cases moved to implementation within 90 days, percentage of identified shadow AI brought under governance, and variance between modelled vs actual ROI at first review gate. Salyant offers a 90-day implementation support retainer to ensure transition from audit to execution.
- AI Asset Register (CSV + Confluence/Jira sync)
- Use Case Business Case Pack (Excel model with assumptions log)
- Governance Framework Blueprint (policy templates, review cadences, escalation paths)
- Vendor Contract Risk Register (renewal dates, data rights, exit clauses)
- 90-Day Sprint Plan with defined Definition of Done per workstream
Integration with Salyant Embedded AI Partnership
The audit is the gateway to our Embedded AI Partnership model. Where the audit identifies high-confidence opportunities, we deploy senior engineers into your squads to build, deploy, and operate production systems—sharing delivery risk via milestone-based commercials. Audit fee credits against Phase 1 implementation if you engage within 60 days.
This continuity eliminates the 'strategy-to-execution gap' where external recommendations stall due to internal capacity constraints or vendor misalignment. Your audit architects become your implementation leads, preserving context and accountability.
- Audit fee credited against Embedded AI Partnership Phase 1
- Same senior architects transition to delivery leadership
- Milestone-based commercials align incentives to production outcomes
- Option to pause after audit with zero further obligation
Frequently Asked Questions
How does this differ from a Big 4 AI readiness assessment?
Big 4 deliver compliance-heavy slide decks. We deliver executable engineering plans. Our architects have built and operated production AI systems in regulated UK environments—banks, insurers, manufacturers. The audit output is a prioritised backlog with technical specs, not a maturity model scorecard.
What access do you need from our team?
Read-only access to SaaS admin consoles (Microsoft 365, Salesforce, ServiceNow, Databricks, Snowflake), code repositories, data catalogues, and vendor contracts. Plus 4-6 hours of stakeholder workshops across Week 1-2. No production data extraction required.
Can you audit specific business units rather than whole enterprise?
Yes. We scope to a division, geography, or function (e.g., finance transformation, supply chain, customer operations). Minimum viable scope: 3-5 core processes with accessible data owners. Fixed price adjusts proportionally.
What if we already have an AI strategy document?
We stress-test it. Most strategies lack technical feasibility validation, vendor negotiation leverage, and regulatory mapping. Our audit either validates your roadmap with evidence or redirects investment before sunk cost accumulates.
How do you handle sensitive IP and data during discovery?
All discovery runs in your environment via containerised tooling. No data leaves your boundary. We operate under mutual NDA and ISO 27001-aligned handling procedures. UK data residency guaranteed.
Ready to identify automation opportunities across your operations?
Speak with a senior Salyant automation architect today.