Architecting the Beyond.
Transform decisions into intelligence — with AI consulting that delivers measurable business impact.
StratAI helps enterprises move beyond the AI hype — identifying real opportunities, building responsible strategies, and delivering measurable outcomes.
Five
Core AI Consulting Service Lines
End-to-End
From use case discovery to managed deployment
ROI-First
Every engagement anchored to business outcomes
Unbiased
Vendor neutral guidance across all AI platforms
Our Service Lines
Strat AI - Five disciplines.
One integrated practice.
We bring structure to AI adoption — helping leadership teams move from curiosity to conviction, and from pilot projects to enterprise-grade transformation.
AI Use Case Identification
Systematically uncover where AI delivers the highest-impact value within your organisation — backed by data, not guesswork.
AI Strategy for Enterprises
A clear, board-ready AI strategy that aligns with your business objectives, technology landscape, and operating model.
AI Governance
Build the frameworks, policies, and controls that ensure your AI is ethical, compliant, and trusted at every level.
AI Optimization & Cost Engineering
Squeeze maximum value from your AI investments — reducing operational cost, improving model performance, and eliminating waste.
Managed AI Consulting Services
An embedded AI consulting capability — ongoing strategic, technical, and operational support as your AI estate grows.
Ready to Begin?
Let's discuss your AI ambitions. Book an initial conversation with our consulting team — no commitment required.
Built for enterprise AI realities, not ideals.
Designed to handle the messy, complex, and constrained environment of a real company, rather than operating in a perfect, theoretical “sandbox” settings.
Business-First Lens
We start with your P&L, not the technology. Every recommendation is grounded in commercial value and feasibility — not vendor roadmaps.
Vendor Agnostic
We have no commercial relationships with AI vendors. Our job is to find what's right for you — not what earns us the largest referral fee.
Structured Methodologies
Repeatable, proven framework — not bespoke improvisation on every engagement. You get speed, consistency, and predictable outputs.
Governance by Design
We embed responsible AI thinking from the first workshop. Compliance and ethics aren't an afterthought — they're load-bearing pillars.
Long-Term Partnership
We're not in the business of one-off strategy documents. Our engagements are built to evolve alongside your organisation's AI maturity.
Practitioner-Led
Our consultants have held operational roles inside enterprises — as heads of data, digital leaders, and technology executives. We speak your language.
Your AI transformation
starts here.
Whether you’re at the beginning of your AI journey or looking to optimise what you’ve already built — we have the expertise to help.
Service 01 / 05
AI Use Case Identification
Stop guessing where AI can help your business. We apply a structured discovery methodology to surface high-impact, feasible use cases — aligned to your strategy, data, and operational context.
The Challenge
Most AI initiatives fail before they begin.
Executives feel pressure to “do AI,” yet without a disciplined approach, teams waste months exploring use cases that are technically unfeasible, commercially immaterial, or strategically misaligned.
The result is a graveyard of proof-of-concepts, sceptical boards, and demoralised teams — all while competitors move ahead with targeted, high-value AI deployments.
— McKinsey, 2024
A rigorous, four-phase discovery process.
We bring structure, speed, and commercial rigour to use case identification — typically delivering a prioritised portfolio within 4–6 weeks.
Strategic Alignment Workshop
We begin by mapping your organisation's strategic priorities, OKRs, and the specific business problems that leadership most urgently needs to solve. This ensures every AI use case we identify is commercially anchored, not technically driven.
Opportunity Landscape Scan
Using our proprietary industry benchmarks and AI capability framework, we systematically scan every function across your business — Finance, Operations, HR, Sales, Supply Chain, Customer Experience — for AI applicability. We assess both horizontal (cross-industry) and vertical (sector-specific) opportunities.
Data & Feasibility Assessment
A use case is only as good as the data that enables it. We evaluate your existing data assets, quality, and infrastructure readiness to determine which ideas are truly actionable today — and which require foundational work first.
Value Scoring & Portfolio Prioritisation
We score every identified use case across four dimensions: financial impact, implementation complexity, time-to-value, and risk. The output is a ranked, investable portfolio — with a clear recommendation on where to start, and a sequenced roadmap for what comes next.
What you walk away with.
AI Use Case Catalogue
A fully documented inventory of 20–60 prioritised AI use cases, each with a business case summary, feasibility rating, data requirements, and indicative ROI range.
Opportunity Heat Map
A visual matrix mapping use cases against impact and complexity — giving leadership an instant, intuitive view of where to focus AI investment
Implementation Roadmap
A phased, sequenced plan for progressing from first pilot to scaled AI deployment — with clear milestones, resource requirements, and risk mitigations
Data Readiness Report
An honest assessment of your data estate’s readiness to support AI — including gap analysis and recommended remediation steps to unlock your highest-value use cases.
Pilot Recommendation Brief
A detailed recommendation for your first 1–3 AI pilots, including scope definition, success metrics, vendor considerations, and expected timeline.
Stakeholder Alignment Pack
Communications materials to bring your board, executive team, and key stakeholders along for the journey — including a business case narrative and FAQ document.
Know exactly where AI can move your business.
Book a complimentary scoping call to discuss your context and how our Use Case Identification service can be tailored to your needs.
Service 02 / 05
AI Strategy for Enterprises
A comprehensive, board-ready AI strategy that translates your organisation’s ambitions into a coherent, executable plan — with the right foundations, the right sequencing, and the right governance from day one.
Strategy is not a slide deck.
It's a system.
We build AI strategies that connect your business model, operating model, and technology architecture — so your AI investments reinforce each other rather than running in parallel silos.
AI Vision & Ambition Setting
Co-creating a compelling, authentic AI vision that your leadership team believes in and your organisation can rally around — without the empty buzzwords.
Operating Model Design
Defining how AI will be built, owned, and scaled inside your organisation — central CoE, federated model, or hybrid — with the right talent, culture, and incentive structures.
Technology Architecture Blueprint
Assessing your current data and technology stack and mapping the target-state AI architecture — including platform choices, build vs. buy recommendations, and integration dependencies.
Investment Planning & Business Cases
Providing the financial rigour to justify AI investment — with credible ROI projections, cost-to-build estimates, and a portfolio view of your AI spending across a 3–5 year horizon.
Talent & Capability Strategy
Mapping the skills your organisation needs to build vs. hire vs. partner — with a practical plan for upskilling existing teams and attracting specialist AI talent.
Change Management & Adoption
Designing the leadership, communication, and cultural change programme that turns AI strategy into lived practice — not a document that gathers dust on a SharePoint.
The StratAI Enterprise AI Strategy Framework.
Value
Where does AI create the most value for your business and customers?
Capability
What people, processes, and platforms are needed to deliver that value?
Governance
How do we ensure AI is responsible, controlled, and trusted by stakeholders?
Scale
How do we move from early wins to an enterprise-wide AI capability?
Your AI Strategy Package.
Enterprise AI Strategy Document
A comprehensive 20–30 page strategy document covering vision, strategic priorities, operating model, technology architecture, investment plan, and governance framework.
Board & Executive Presentation
A polished, board-ready presentation distilling the strategy into a compelling narrative — designed to secure executive buy-in and investment commitment.
3-Year AI Roadmap
A structured, phased implementation roadmap with clear milestones, resource requirements, and decision gates — translated into a Gantt-style planning tool.
Technology Assessment Report
An objective evaluation of your current data and technology stack against the requirements of your AI strategy — with vendor-neutral recommendations.
AI Operating Model Blueprint
A detailed design for how AI will be organised, governed, and delivered inside your enterprise — with role definitions, RACI matrices, and process flows.
Investment & Business Case Model
A financial model supporting the AI investment case — with scenario analysis, expected NPV, payback period, and risk-adjusted return on investment.
AI strategy that earns board conviction.
Let’s discuss your organisation’s AI ambitions and how a StratAI engagement can turn them into a coherent, investable strategy.
AI Governance &
Responsible AI
Build the frameworks, policies, and oversight mechanisms that make your AI trustworthy — protecting your organisation from regulatory, reputational, and ethical risks while enabling confident AI deployment at scale.
Ungoverned AI is a liability, not an asset.
AI regulation is accelerating. The EU AI Act, UK AI Code of Practice, and sector-specific guidelines from financial and healthcare regulators are reshaping compliance expectations across industries.
Beyond regulation, organisations face mounting pressure from customers, employees, investors, and civil society to demonstrate that their AI is fair, explainable, and safe.
AI governance done well is not a constraint on innovation — it’s the foundation that allows you to scale AI with confidence.
Regulatory Compliance
EU AI Act, UK AI Code of Practice, GDPR, and sector-specific AI regulation requirements.
AI Bias & Fairness Risks
Discriminatory outputs, unrepresentative training data, and disparate impact across demographic groups.
Data Privacy & Security
Protecting sensitive personal and commercial data used in AI training, inference, and model outputs.
Explainability & Auditability
Demonstrating how AI decisions are made, particularly in high-stakes domains like credit, hiring, and healthcare.
The five pillars of responsible AI at StratAI.
Fairness & non-discrimination
AI systems must not produce outcomes that unfairly disadvantage individuals or groups based on protected characteristics. We design audit mechanisms and fairness metrics into every governance engagement from the outset.
Transparency & Explainability
Stakeholders affected by AI decisions have a right to understand how those decisions are made. We help organisations implement explainability standards appropriate to the risk level and regulatory context of each AI system.
human oversight & control
Humans must remain meaningfully in control of consequential AI decisions. We design “human-in-the-loop” mechanisms, override procedures, and escalation paths that preserve accountability without eliminating the efficiency benefits of automation.
privacy & Data stewardship
AI governance must embed data privacy by design — covering data minimisation, purpose limitation, consent management, and the specific challenges of using personal data in AI training and inference.
accountability & auditability
Every AI system in production must have a clear owner, a documented audit trail, and a defined process for investigating and responding to incidents. We build these structures into your governance framework as non-negotiable requirements.
End-to-end AI governance.
Built to scale.
AI Governance Framework Design
A comprehensive governance structure covering AI oversight bodies, decision rights, escalation paths, and accountability mechanisms — tailored to your organisation’s size and complexity.
AI Risk Assessment & Classification
Systematic assessment of your existing and planned AI systems against risk tiers — ensuring appropriate oversight and controls are applied proportionate to potential impact.
Responsible AI Policy Suite
A complete set of policy documents covering AI ethics principles, acceptable use, model development standards, vendor AI procurement, and incident response procedures.
Regulatory Compliance Readiness
Gap analysis against relevant AI regulations (EU AI Act, GDPR, UK AI Code of Practice, FCA AI guidance, NHS AI frameworks) with a prioritised remediation roadmap.
Model Risk Management
Implementing model validation, monitoring, and documentation standards — ensuring every AI model in production is tracked, tested, and managed throughout its lifecycle.
AI Ethics & Fairness Review
Independent review of AI systems for bias, fairness, and discriminatory impact — including data audits, model card production, and remediation recommendations.
Deploy AI with confidence and accountability.
Talk to us about building a governance framework that protects your organisation and enables responsible AI at scale.
AI Optimization
&
Cost Engineering
AI costs are spiralling for most enterprises — unchecked cloud inference spend, redundant tools, underperforming models, and opaque vendor contracts. We fix that — systematically and measurably.
AI spend without AI ROI is just expensive tech debt.
As organisations scale AI deployment, costs compound rapidly. Cloud compute for LLM inference, data pipeline infrastructure, multiple overlapping AI platform subscriptions, and expensive specialist labour can push AI TCO far beyond initial business cases.
Model performance degrades over time. Data drift, concept drift, and changing business conditions silently erode the value your AI was supposed to deliver.
Most organisations have no systematic way to track AI’s financial return — making it impossible to make informed decisions about where to invest and where to cut.
40%
of enterprise AI spend is estimated to be waste or underutilised capacity
3×
AI infrastructure costs can be reduced through systematic cost engineering without sacrificing performance
60%
of AI models in production have never undergone a formal performance review
$2M+
average annual AI cost savings identified in our enterprise optimization engagements
Six levers of AI optimization.
AI Cost Transparency & FinOps
Building full visibility into your AI cost stack — attributing cloud compute, storage, API, and tooling costs to specific use cases and business units. Enabling informed decisions about where AI investment is earning its keep.
Model Performance Optimisation
Systematic evaluation of production AI models — assessing accuracy, latency, drift, and business outcome alignment. Identifying where models need retraining, fine-tuning, or replacement.
Infrastructure Right-Sizing
Auditing your AI infrastructure against actual usage patterns — eliminating over-provisioned compute, optimising inference architecture, and migrating to cost-appropriate deployment patterns (serverless, batched inference, edge).
AI Portfolio Rationalisation
Auditing your organisation’s full AI and ML tool landscape — identifying overlapping vendors, consolidation opportunities, and underutilised platform licences that can be renegotiated or eliminated.
Prompt & Pipeline Engineering
For LLM-based applications, optimising prompt design, context management, and inference patterns to dramatically reduce token consumption and API costs without sacrificing output quality.
AI ROI Measurement Framework
Designing the metrics, data collection, and reporting infrastructure to reliably measure the commercial return of each AI initiative — giving leadership a real-time view of AI investment performance.
From audit to savings in 8 weeks.
Wk 1–2
Discovery Audit
Full inventory of AI tools, costs, models, infrastructure, and contracts.
Wk 3–4
Analysis & Diagnosis
Performance benchmarking, cost attribution, and waste identification.
Wk 5–6
Recommendations
Prioritised optimisation roadmap with quantified savings estimates.
Wk 7–8
Implementation
Quick wins executed. Longer-term programme initiated with tracking in place.
Turn AI spend into
AI value.
Our AI Optimization audit typically pays for itself within the first month of savings identified. Let’s talk about what that could look like for your organisation.
Managed AI
Consulting Services
An embedded, on-demand AI consulting capability for your organisation — strategic guidance, technical expertise, and operational support available when and how you need it, without the cost or complexity of building it in-house.
Your AI consulting team — without the hiring risk.
Building an internal AI strategy and governance capability takes years and significant investment. Hiring and retaining senior AI talent is intensely competitive and expensive — and the landscape changes too quickly for internal teams to stay current without dedicated effort.
StratAI Managed AI Consulting Services provides a flexible, retained consulting model — giving you access to senior AI strategists, data architects, and governance experts on a subscription basis.
We function as an extension of your leadership team — attending steering groups, supporting delivery, reviewing vendors, and ensuring your AI programme stays aligned with strategy as the market evolves.
For organisations who need...
- Ongoing strategic AI guidance without hiring a full-time Chief AI Officer
- A trusted second opinion on vendor proposals, AI investments, and technology choices
- Continuity of governance and oversight as AI programmes grow in scope and complexity
- Access to specialist expertise (LLM engineering, AI risk, data architecture) on demand
- Support to stay ahead of the rapidly evolving AI regulatory and technology landscape
Three engagement models.
One team behind all of them.
Strategic Partner
Senior AI advisory for leadership teams. Ideal for organisations at the early stages of their AI journey who need board-level counsel and strategic direction.
includes
- Monthly strategy sessions with senior advisor
- Quarterly AI landscape briefings
- On-demand advisory calls (up to 4 hours/month)
- Vendor proposal review
- Board presentation support
Active Programme Support
Embedded consulting for organisations actively running AI programmes — providing hands-on support across strategy, delivery, governance, and optimisation.
Includes Everything in Advisory, Plus
- Dedicated engagement lead
- Weekly check-ins with delivery teams
- Attendance at AI steering group meetings
- Monthly governance & risk review
- Up to 3 specialist consultants on demand
- Quarterly AI maturity assessment
Full AI Consulting Capability
A fully embedded AI consulting function for large-scale, complex AI transformation programmes — acting as your organisation’s extended AI team across all workstreams.
Includes Everything in Embedded, Plus
- Dedicated multi-disciplinary team
- Hands-on delivery support for pilots
- Vendor management & procurement support
- Regulatory engagement support
- Training & capability building programmes
- Executive AI education sessions
Why an ongoing model
outperforms project-by-project.
Context Compounds
We learn your organisation deeply over time — your politics, your data, your technology decisions, your stakeholders. That accumulated context is enormously valuable and lost entirely with a project-based consultant who leaves at the end of an engagement.
Continuity of Governance
AI governance is not a one-time exercise. Models drift. Regulations change. New use cases emerge. Ongoing oversight — not an annual policy review — is what actually keeps your AI estate responsible and compliant.
Speed of Access
When a decision needs to be made quickly — a new AI vendor is pitching, a regulatory question arises, a pilot is underperforming — you need expertise immediately. A retained relationship means we're always in your corner, not warming up to your context from scratch.
Cost Efficiency
Managed services are significantly more cost-efficient than hiring senior permanent AI talent — especially given the volatility of the AI talent market. You get senior expertise at a fraction of the cost of a full-time Chief AI Officer or Principal AI Architect.
Your AI ambitions deserve a dedicated partner.
Let’s discuss which engagement tier is right for your organisation — and how StratAI can become the AI consulting capability your business has been looking for.
