AI Automation Design Sprint - Accelerator (4 Days)
This four-day AI automation design sprint takes your team from problem framing to a high-fidelity, user-validated AI prototype that is ready for build. Working alongside a fractional CTO, your stakeholders co-create the solution, observe real users interacting with it, and leave with a defensible implementation plan. The output is a tangible artefact your engineering team or vendor can pick up immediately.
Expected Outcome
For organisations serious about adopting AI automation, the cost of slow, unfocused exploration is significant. Every quarter spent debating use cases is a quarter where competitors capture efficiency gains, talent walks away, and internal scepticism grows. A structured sprint replaces opinion with evidence, and replaces slideware with something users have actually touched. The return on investment is measured in avoided waste. By validating fit, feasibility, and desirability before committing six-figure build budgets, you de-risk the entire programme. Most clients recover the sprint cost within the first iteration of build savings, and gain a reusable methodology their teams can apply to future automation initiatives.
What You Get
- A high-fidelity, working AI prototype you can demonstrate to stakeholders and customers
- A user-validated solution with documented qualitative and quantitative feedback
- A complete implementation roadmap covering scope, sequencing, and dependencies
- A target technical architecture aligned to your existing stack and data estate
- Captured user feedback and behavioural insights that inform product decisions
- Measurable team capability uplift in modern AI tooling and validation practices
Overview
The AI Automation Design Sprint Accelerator is a four-day, fractional CTO-led engagement that compresses months of AI strategy work into a single focused week. Delivered by 941 Consulting, the sprint blends innovation consulting, hands-on AI prototyping, and structured user validation to move your team from ambiguous opportunity to a tested, investment-ready solution. It is the most complete format in our AI sprint range and is designed for organisations that want a working prototype, a credible roadmap, and internal alignment before committing capital to full implementation.
Who this is for
- Series A to Series C scale-ups with a clear automation hypothesis but no validated solution
- Mid-market and enterprise teams whose previous AI experiments stalled in proof-of-concept purgatory
- SaaS, fintech, and B2B services companies under pressure to ship AI features credibly
- Product and operations leaders who need to align engineering, commercial, and executive stakeholders
- Founders without an in-house CTO who require senior technical leadership for a critical decision
- Innovation teams that need a repeatable sprint methodology they can run themselves later
Use cases
- A Series A SaaS startup needing to validate an AI copilot feature before committing engineering resources to a full build
- A mid-market e-commerce business wanting to automate customer support triage with measurable confidence in the model
- A B2B services firm exploring document automation for contract review and onboarding workflows
- A fintech scale-up evaluating AI-driven fraud detection and looking for a safe, evidence-based first step
- An enterprise innovation team that needs a defensible business case to unlock budget for an internal AI platform
Deliverables
- High-fidelity prototype delivered as a clickable flow or working AI pipeline
- Sprint report deck summarising decisions, evidence, and recommendations
- User test recordings, transcripts, and structured feedback synthesis
- Implementation roadmap with phases, milestones, and effort estimates
- Target technical architecture diagram and component breakdown
- Data and API requirements specification for downstream build
- Build plan including team shape, tooling, and sequencing
Our Methodology
- 1Problem understanding and stakeholder alignment workshop
- 2Solution design and divergent ideation with the core team
- 3Prototype development using modern AI tooling
- 4Moderated user testing with target personas
- 5Implementation planning and architectural decisioning
- 6Knowledge transfer and capability handover
Best Practices
- User-centred design grounded in real customer evidence
- Agile, time-boxed development to force decisions
- Continuous testing and feedback throughout the sprint
- Comprehensive documentation for downstream teams
- Cross-functional team collaboration from day one
- Real-world validation rather than theoretical analysis
Frequently asked questions
How long does the AI automation design sprint take?
The Accelerator format runs across four consecutive working days, typically Monday to Thursday, with a wrap-up review on the following day. The compressed timeline is intentional: it forces decisions, prevents scope creep, and keeps senior stakeholders engaged from start to finish.
How much does an AI automation sprint cost?
The four-day Accelerator is fixed at twelve thousand pounds, inclusive of facilitation, prototyping, user testing logistics, and all deliverables. There are no hidden fees. Lighter one-day and two-day formats are available if you need a smaller first step before committing to the full sprint.
Who runs the sprint?
The sprint is led personally by Romain Eude, founder of 941 Consulting and an experienced fractional CTO. You work directly with a senior practitioner throughout, not a junior consultant, which is why a single week can deliver outcomes that traditional consultancies stretch over months.
What deliverables do I get at the end?
You receive a working prototype, a sprint report, user test evidence, an implementation roadmap, a target architecture, data and API requirements, and a build plan. Everything is documented in formats your engineering team or external vendor can act on immediately.
Can you work with our existing tech stack?
Yes. The sprint is tool-agnostic and we deliberately design solutions that fit your current data estate, cloud provider, and engineering practices. We assess compatibility during the first day so the prototype reflects what is realistic to build, not an idealised greenfield architecture.
Related Solutions
AI Automation Design Sprint - Discovery (1 Day)
This one-day AI automation discovery sprint gives your team a structured, evidence-based view of where AI can deliver real value across your operations. Facilitated by an experienced fractional CTO, the day combines short discovery interviews, collaborative ideation, and pragmatic feasibility scoring. You leave with a personalised opportunity map and a clear recommendation on which automation idea to pursue next.
AI Automation Design Sprint - Prototyping (2 Days)
This two-day AI automation prototyping sprint transforms a chosen concept into a functional demo your stakeholders can interact with. Working alongside a fractional CTO, your team co-builds the prototype using modern AI platforms, validates it against real inputs, and leaves with a clear technical path to production. The output is a credible artefact, not a slide.
Cloud Cost Optimization Sprint
The Cloud Cost Optimization Sprint delivers a structured one-day review of your AWS environment to uncover immediate cost-saving opportunities. We benchmark spend against usage patterns, identify oversized or idle resources, and quantify the savings achievable within thirty days. You receive a prioritised, evidence-backed roadmap that turns cloud cost optimisation into measurable financial impact.
Ready to Get Started?
Contact us today to discuss how we can help you achieve your technology goals