Table of Contents
- What Is an AI Readiness Bootcamp?
- Why Sydney Businesses Need AI Readiness Now
- The 2-Week Engagement Model: How It Works
- Week 1: Diagnostic, Discovery & Stakeholder Alignment
- Week 2: Roadmap, Business Case & Go-to-Market Strategy
- Key Deliverables You’ll Walk Away With
- Who Should Attend an AI Readiness Bootcamp
- Common Pitfalls We See (And How to Avoid Them)
- Real Sydney Market Context: Where AI Adoption Stands
- Next Steps: From Bootcamp to Execution
What Is an AI Readiness Bootcamp?
An AI Readiness Bootcamp is a structured, time-boxed diagnostic and strategy engagement designed to answer one question: where is your organisation actually positioned to adopt, deploy, and scale AI—and what do you ship first?
Unlike consultant-led strategy decks that sit on shelves, a bootcamp is a working sprint. Your team, our team, and often a fractional CTO sit in the same room (or on the same calls) for two weeks. We map your current state, identify quick wins, stress-test your assumptions, and hand you a concrete roadmap with 90-day priorities, a business case, and clear next steps.
The bootcamp isn’t about AI hype. It’s about audit-readiness, operational risk, competitive advantage, and revenue. We focus on what you can ship in the next quarter, what will actually move the needle for your business, and what infrastructure or team changes you need to make it stick.
At PADISO, we’ve run this model across seed-stage startups, Series-B companies, and mid-market enterprises across Sydney and Australia. The format is proven. The outcomes are measurable. And crucially, the engagement is fixed-scope and fixed-fee—you know what you’re paying and what you’re getting.
Why Sydney Businesses Need AI Readiness Now
Sydney’s startup and scale-up ecosystem has exploded over the past three years. But most teams are asking the same questions: Should we build or buy? Where do we start? How do we avoid expensive mistakes? And for established enterprises, the pressure is different: How do we modernise our tech stack? How do we compete with AI-native players? How do we stay compliant?
Here’s what we’re seeing in the Sydney market:
Founder and CEO Uncertainty. Seed-to-Series-B founders have AI on their roadmap, but they don’t know whether to hire a VP of AI, partner with a vendor, or build in-house. They’re spending time and money on pilots that don’t connect to revenue. Many lack a fractional CTO or technical co-founder to pressure-test ideas.
Enterprise Paralysis. Larger organisations see AI as a must-have, but their legacy systems, governance frameworks, and risk-aversion slow them down. They’re building committees instead of shipping products. They’re waiting for the “right” moment instead of learning in the market.
Talent Scarcity. Sydney’s AI talent pool is competitive and expensive. Most teams can’t afford to hire a full-time VP of Engineering or Chief AI Officer. A fractional CTO model via a bootcamp engagement gets you senior strategic input without the headcount.
Compliance Anxiety. Australian businesses operating under APRA, ASIC, AUSTRAC, or export control frameworks are nervous about AI governance. They don’t know how to get audit-ready. They’re not sure whether SOC 2 or ISO 27001 compliance via tools like Vanta will protect them.
Speed-to-Market Pressure. Competitors are moving fast. Your board is asking about AI. Your customers are asking about AI. You can’t afford to spend six months on strategy before you ship anything.
An AI Readiness Bootcamp solves these problems in two weeks. You get clarity, a roadmap, and permission to move.
The 2-Week Engagement Model: How It Works
The bootcamp runs Monday to Friday for two weeks. It’s intensive, focused, and designed to compress months of strategy work into a working sprint.
Structure and Rhythm
Daily standups (30 mins, 9 AM). Your core team (usually CEO, CTO or Head of Engineering, Head of Product, and one other leader) syncs with our team on the day’s focus, blockers, and priorities.
Working sessions (2–4 hours per day). We run facilitated workshops, interviews, and technical deep-dives. You’re not sitting passively; your team is actively building the roadmap alongside us.
Async work between sessions. Our team digs into your codebase, infrastructure, data pipelines, and vendor landscape. We interview 10–15 stakeholders across your organisation (engineering, product, finance, operations, compliance).
Weekly synthesis (Friday 3 PM). End-of-week checkpoint where we share findings, validate assumptions, and adjust the plan for Week 2.
Final presentation (Friday, Week 2). You present the AI Readiness roadmap to your board, investors, or leadership team. We co-present and answer technical questions.
What You’re Actually Doing
The bootcamp isn’t a lecture series. It’s a working engagement. Here’s what happens:
- Mapping your current state. We document your tech stack, data architecture, team structure, and existing AI / automation initiatives. We identify what’s working and what’s slowing you down.
- Identifying high-impact use cases. We work with your team to surface 5–10 potential AI applications, score them by business impact and technical feasibility, and rank them.
- Stress-testing assumptions. We challenge your thinking. If you say “we need to build a RAG pipeline,” we ask: Why? What problem does it solve? What’s the alternative? What’s the cost?
- Running a technical audit. Our engineers review your infrastructure, data quality, API landscape, and security posture. We identify technical debt, compliance gaps, and architectural risks.
- Building the 90-day roadmap. We define your first 3–4 bets: what to ship in the next quarter, what to retire, what to de-risk, and what to learn.
- Creating a business case. We quantify the revenue, cost, or time impact of your top 3 initiatives. We build a case for investment (whether that’s headcount, vendor spend, or infrastructure).
- Documenting the operating model. We define how your team will work: who owns AI strategy? Who owns delivery? How do you avoid siloed pilots? How do you measure success?
Week 1: Diagnostic, Discovery & Stakeholder Alignment
Week 1 is about getting honest. We map where you are, what you’ve tried, and why some things worked and others didn’t.
Monday–Tuesday: Current State & Stakeholder Interviews
What we’re doing:
- Kickoff meeting with your core team (1 hour). We explain the bootcamp rhythm, set expectations, and agree on who we’re interviewing.
- Stakeholder interviews (2–3 per day). We talk to your CTO, VP Product, Head of Finance, Head of Ops, Head of Compliance, and 8–10 other leaders. We ask: What’s your biggest bottleneck? Where could AI help? What have you tried? What failed?
- Codebase and infrastructure review. Our engineers review your GitHub repos, cloud infrastructure (AWS / Azure / GCP), databases, APIs, and data pipelines. We run a basic security audit.
- Vendor and tool audit. We map every tool you’re paying for: analytics platforms, CRM, ERP, data warehouse, BI tool, existing AI / automation vendors. We identify overlaps, gaps, and consolidation opportunities.
Deliverable: A current-state summary document (internal working draft) capturing your tech stack, team structure, existing AI initiatives, and key pain points.
Wednesday–Thursday: Use Case Identification & Feasibility Analysis
What we’re doing:
- Facilitated ideation workshop (2 hours). Your team brainstorms 15–20 potential AI use cases. We capture them all, no filtering.
- Use case scoring. We score each idea against: business impact (revenue, cost, risk reduction, speed), technical feasibility (data availability, complexity, timeline), and strategic fit (alignment with roadmap, competitive advantage).
- Deep-dive on top 5 use cases. We interview the owners of your top-scoring ideas. We ask: What’s the current process? How much time / money could you save? What data do you have? What’s the failure mode?
- Technical feasibility assessment. Our engineers assess: Can we build this? How long? What infrastructure do we need? What are the risks?
Deliverable: A ranked use case matrix (spreadsheet + narrative) showing your top 8–10 opportunities, scored and annotated.
Friday Week 1: Synthesis & Alignment
What we’re doing:
- Internal team debrief (morning). Our team aligns on findings, themes, and hypotheses.
- Stakeholder alignment workshop (2 hours). We present back what we’ve heard. We surface conflicts. We get alignment on priorities. We answer: Are we all solving for the same problem? What’s non-negotiable?
- Week 2 plan. We agree on the top 3–4 use cases to deep-dive in Week 2. We confirm who needs to be in the room.
Deliverable: A one-page Week 2 priorities document and an updated stakeholder list.
Week 2: Roadmap, Business Case & Go-to-Market Strategy
Week 2 is about building the plan you’ll actually execute.
Monday–Tuesday: Business Case & Financial Modelling
What we’re doing:
- Revenue and cost impact modelling. For each top use case, we build a financial model: How much revenue does this unlock? How much does it cost to build and run? What’s the payback period? What’s the IRR?
- Scenario planning. We model: best case, base case, and worst case. We identify what has to go right and what could go wrong.
- Investment case. We build a pitch: Here’s what we should ship. Here’s what it costs. Here’s what we get back. Here’s the timeline.
- Vendor vs. build analysis. For each use case, we compare: build in-house vs. buy a vendor vs. hybrid. We score on cost, time-to-value, maintenance burden, and strategic control.
Deliverable: A 10–15 page business case document with financial models, scenario analysis, and investment recommendations.
Wednesday–Thursday: Roadmap & Execution Plan
What we’re doing:
- 90-day roadmap. We define your first three months: what ships in month 1, what ships in month 2, what you’re learning in month 3. We break it into sprints.
- 12-month vision. We sketch the next year: what’s the next wave of use cases? How do you build on early wins? What infrastructure do you need to invest in?
- Team and hiring plan. We define: who owns each initiative? Do you need to hire? What skills? When? What’s the cost?
- Vendor and platform strategy. We recommend: what tools should you buy? What should you build? What should you retire? What’s the integration plan?
- Compliance and risk roadmap. For regulated industries (financial services, insurance, health), we map: what audit-readiness work do you need? What governance frameworks? What training?
For organisations pursuing SOC 2 compliance or ISO 27001 audit-readiness, we integrate this into the AI roadmap. We recommend tools like Vanta to automate compliance and we identify where AI initiatives create new compliance work.
Deliverable: A detailed 90-day roadmap (Gantt chart + narrative), a 12-month vision document, and a team / hiring plan.
Friday Week 2: Final Presentation & Alignment
What we’re doing:
- Presentation dry-run (morning). Your team presents the roadmap to our team. We pressure-test it, challenge assumptions, and refine the narrative.
- Final presentation (2–3 hours). You present to your board, investors, leadership team, or all-hands. We co-present and answer technical questions. We make the case for investment.
- Next steps workshop (1 hour). We agree: Who owns execution? What’s the first sprint? When do we kick off? Do you need a fractional CTO or co-build partner?
Deliverable: A polished, board-ready presentation deck and a one-page “first 30 days” action plan.
Key Deliverables You’ll Walk Away With
At the end of two weeks, you’ll have:
1. Current State Assessment
A candid, documented view of where you are: tech stack, team, existing AI initiatives, gaps, and risks. This becomes your baseline for measuring progress.
2. Ranked Use Case Matrix
Your top 8–10 AI opportunities, scored by business impact, technical feasibility, and strategic fit. This answers: What should we do first?
3. Business Case
Financial models for your top 3–4 initiatives: revenue impact, cost, payback period, IRR. This answers: Is it worth it? How much should we invest?
4. 90-Day Roadmap
A detailed, sprint-by-sprint plan for your first quarter: what ships, who owns it, what it costs, what it delivers. This is your execution plan.
5. 12-Month Vision
A sketch of the next year: how do you scale? What’s the next wave? What infrastructure do you need?
6. Team & Hiring Plan
Who owns AI strategy? Who owns delivery? Do you need to hire? What skills? When?
7. Vendor & Platform Strategy
What tools should you buy? What should you build? What should you retire? What’s the integration plan?
8. Board-Ready Presentation
A polished deck that tells your AI story to investors, board members, or leadership. This is your pitch for investment.
9. Compliance & Risk Roadmap
For regulated industries, a clear plan for audit-readiness, governance, and risk management. If you’re pursuing SOC 2 or ISO 27001 compliance, we map how AI initiatives fit into your compliance roadmap.
10. Operating Model
How your team will work: who makes decisions? How do you avoid siloed pilots? How do you measure success? How do you scale?
All of these are yours to keep, adapt, and execute on. They’re not consultant’s property; they’re your roadmap.
Who Should Attend an AI Readiness Bootcamp
The bootcamp works best for teams that meet these criteria:
Founders and CEOs of Seed-to-Series-B Startups
You’re building a product-market fit, but you know AI could be a competitive advantage or a core part of your offering. You need a fractional CTO or co-build partner to validate your technical direction and help you hire. You don’t have time for a six-month strategy project.
The bootcamp gives you: a clear product roadmap, a hiring plan, and a technical co-founder figure for the next 3–6 months.
Operators at Mid-Market and Enterprise Companies
Your company is 50–500 people. You’ve got a stable product, but you’re modernising: migrating to cloud, automating workflows, or building AI capabilities. You need to move faster, but you’re constrained by legacy systems, governance, and risk-aversion.
The bootcamp gives you: a realistic modernisation roadmap, a business case for investment, and clarity on what to ship first without breaking production.
Heads of Engineering and Security Leads
You’re responsible for technical delivery and compliance. You need to understand where AI fits into your roadmap, how to de-risk it, and how to stay compliant. You might be pursuing SOC 2 or ISO 27001 compliance via Vanta and you need to understand how AI initiatives affect your audit.
The bootcamp gives you: a technical roadmap you can own, a compliance risk map, and a team structure that works.
Non-Technical Founders and Domain Experts
You’ve got a great idea and deep domain expertise (e.g., insurance, supply chain, healthcare), but you’re not technical. You need a venture studio partner to help you validate the idea, build an MVP, and scale. You need a fractional CTO.
The bootcamp gives you: validation of your idea, a technical co-founder figure, a hiring plan, and a clear roadmap to Series A.
Private Equity Firms and Portfolio Companies
You’re running a roll-up or modernisation project. You need to understand the technology landscape, identify quick wins, and build a value-creation plan across your portfolio. You need a fractional CTO or technology due diligence partner.
The bootcamp gives you: a 90-day value-creation roadmap, a team structure, and a clear picture of what you can realistically achieve.
Common Pitfalls We See (And How to Avoid Them)
After running dozens of bootcamps across Sydney and Australia, we’ve seen patterns. Here’s what trips teams up—and how to avoid it.
Pitfall 1: Treating AI as a Separate Initiative
The problem: Teams create an “AI team” or “AI workstream” that’s siloed from product, engineering, and operations. They build AI pilots that don’t connect to revenue or operations. They spend money on AI without asking: Does this solve a real business problem?
How to avoid it: In the bootcamp, we integrate AI into your core roadmap. Every use case has to answer: What business problem does this solve? How much revenue / cost does it unlock? Who owns it? How does it connect to our product strategy? AI is a tool, not a strategy.
Pitfall 2: Waiting for the “Perfect” Model
The problem: Teams spend months building and fine-tuning AI models before they ship anything. They’re perfecting in the lab while competitors are learning in the market. They’re optimizing for 99.9% accuracy when 85% would unlock value.
How to avoid it: In the bootcamp, we push for speed. We ask: What’s the minimum viable version? What can you ship in four weeks? What can you learn in the market? We favour rapid iteration over perfection. We build a roadmap that ships something in 30 days, learns from it in 60 days, and scales in 90 days.
Pitfall 3: Underestimating Data and Integration Work
The problem: Teams assume their data is ready for AI. They’re shocked to discover their data is fragmented, dirty, or siloed across systems. They underestimate the integration work needed to connect AI to their existing systems.
How to avoid it: In the bootcamp, our engineers audit your data architecture. We ask: Where’s your data? Is it clean? Can we access it? What’s the integration work? We factor this into the roadmap and timeline. We often recommend starting with a data consolidation project before you ship AI.
Pitfall 4: Hiring Before You Know What You Need
The problem: Teams hire a VP of AI or ML engineer before they’ve figured out what they’re actually building. They hire the wrong person for the wrong role. They burn cash on headcount they don’t need.
How to avoid it: In the bootcamp, we build a hiring plan based on your roadmap. We recommend: You need a platform engineer in month 1, an ML engineer in month 2, and a data engineer in month 3. You don’t need a VP of AI until you’ve shipped three use cases and have a clear product strategy. We often recommend a fractional CTO or co-build partner for the first 6–12 months instead of hiring full-time.
Pitfall 5: Ignoring Compliance Until It’s Too Late
The problem: Teams ship AI features without thinking about compliance, data governance, or audit-readiness. When they hit regulatory scrutiny or try to sell to enterprise customers, they’re blocked. They have to rebuild.
How to avoid it: In the bootcamp, we integrate compliance from day one. For regulated industries (financial services, insurance, health), we map: What audit-readiness work do you need? What governance frameworks? What’s the timeline? We recommend tools and processes upfront so you don’t have to retrofit them later. If you’re pursuing SOC 2 or ISO 27001 compliance, we map how this fits into your AI roadmap.
Pitfall 6: Not Measuring Success
The problem: Teams ship AI features but don’t measure impact. They don’t know if the feature is actually solving the problem, saving time, or generating revenue. They can’t make the case for the next investment.
How to avoid it: In the bootcamp, we define success metrics for every initiative. We ask: How will you measure this? What’s the baseline? What’s the target? How will you track it? We build measurement into the roadmap. We recommend: In month 1, you’ll measure adoption and user feedback. In month 2, you’ll measure time saved or revenue impact. In month 3, you’ll decide whether to scale or pivot.
Real Sydney Market Context: Where AI Adoption Stands
Sydney’s tech ecosystem is maturing fast. Here’s where we’re seeing AI adoption happen—and where teams are getting stuck.
Financial Services and Fintech
Sydney has a strong fintech cluster. Banks, wealth managers, and lenders are investing in AI for: customer segmentation, fraud detection, underwriting, and compliance. But they’re moving slowly because of APRA, ASIC, and AUSTRAC regulations. Teams are asking: How do we stay compliant? How do we move fast?
We’ve seen AI readiness bootcamps unlock value by mapping: What can we do within our current regulatory framework? What do we need to de-risk? What’s the compliance roadmap? Most teams can move much faster than they think once they understand the rules.
Insurance
Insurers are automating claims, underwriting, and conduct risk. But they’re worried about fairness, bias, and regulatory scrutiny. They’re also managing legacy systems and risk-averse cultures.
We’ve helped insurance teams use bootcamps to: identify quick wins (claims automation, document classification), build a business case, and create a governance framework. Most can ship something in 30 days and measure impact in 90 days.
Retail and E-Commerce
Retailers are investing in personalisation, demand forecasting, and supply chain optimisation. They’re moving faster than financial services because the regulatory bar is lower. But they’re struggling with data quality and integration.
Bootcamp teams in retail often discover: Your data is fragmented. You need to consolidate before you can personalise. But you can start with a simple recommendation engine in 30 days and learn from that.
Health Tech and Biotech
Health tech founders are building AI-powered diagnostics, drug discovery, and patient engagement tools. They’re moving fast but they’re nervous about TGA, HIPAA, and clinical validation. They need to understand: What’s the regulatory pathway? What do we need to prove?
Bootcamps help by mapping: What can you do with existing data? What do you need to collect? What’s the clinical validation roadmap? What’s the timeline to market?
Professional Services and Consulting
Consulting firms and accounting practices are automating document review, contract analysis, and financial forecasting. They’re moving quickly because the regulatory bar is low and the ROI is clear.
Bootcamps often reveal: You can automate 40% of your junior analyst work in 90 days. You’ll save $200K per year. But you need to retrain your team and rethink your operating model.
What’s Holding Sydney Teams Back
Across all industries, we see common blockers:
- Talent scarcity. Sydney’s AI talent pool is competitive. Most teams can’t hire the people they need at the price they can afford.
- Legacy systems. Older companies are stuck with systems that don’t integrate, data that’s fragmented, and processes that are manual. Modernising is hard.
- Risk aversion. Australian culture is risk-averse. Teams want certainty before they move. But AI is inherently uncertain. Bootcamps help by framing it as learning, not betting.
- Vendor confusion. There are hundreds of AI vendors. Teams don’t know which to buy, which to build, and which to ignore. Bootcamps provide clarity.
- Measurement challenges. Teams struggle to measure AI impact. They ship features but don’t know if they’re working. Bootcamps solve this by building measurement into the roadmap.
Next Steps: From Bootcamp to Execution
The bootcamp ends on Friday of Week 2. But the real work starts Monday. Here’s how to move from strategy to execution.
Immediately After (Days 1–7)
Share the roadmap. Present to your full team, board, investors, and stakeholders. Get alignment on priorities. Answer questions. Build momentum.
Identify the owner. For each top initiative, assign an owner: usually a product manager, engineer, or operator. They’re responsible for execution, measurement, and communication.
Secure budget and headcount. If you need to hire or buy tools, move fast. Budget cycles are slow; get ahead of them.
Book your first sprint. If you’re shipping in 30 days, you need to start designing and building immediately. Don’t wait.
Weeks 2–4: First Sprint
Build or integrate. Ship your first AI feature or automation. Keep it small. Measure it. Learn from it.
Hire if needed. If you need an engineer, start recruiting. If you need a fractional CTO or co-build partner, book a call with us. Don’t wait until you’re stuck.
Set up measurement. Track adoption, user feedback, time saved, or revenue impact. Report weekly to your team and board.
De-risk compliance. If you’re in a regulated industry, start the compliance work early. If you’re pursuing SOC 2 or ISO 27001 compliance, set up Vanta and start the audit-readiness process.
Weeks 4–12: Scale and Learn
Measure and iterate. After 30 days, you’ll have data. Does the feature work? Is it generating value? What’s the feedback? Iterate based on what you learn.
Ship the second initiative. Once you’ve learned from the first, move to the second. You’re building momentum and confidence.
Hire the team. By week 8, you should have a clearer picture of what team you need. Hire or partner accordingly.
Plan the next wave. By week 12, you’ll have shipped two initiatives and learned a lot. Update your roadmap. What’s next?
Months 4–12: Scale
Build the operating model. You’ve shipped a few things. Now build the process: how do you identify new use cases? How do you prioritise? How do you measure? How do you scale?
Invest in infrastructure. As you scale, you’ll need better data pipelines, monitoring, and governance. Invest in this.
Hire or partner for the next phase. Do you need a VP of AI? A platform engineering team? A data science team? Or do you need a fractional CTO or co-build partner for another 6 months? Make the call based on your roadmap.
Plan Series A. If you’re a startup, your AI roadmap is part of your Series A story. Make sure your investors understand: what have you shipped? What’s the impact? What’s next?
Getting Help: When to Bring in a Partner
The bootcamp is a starting point. But execution is hard. Here’s when to bring in help:
You need a fractional CTO. If you don’t have a technical co-founder or CTO, you need senior technical leadership. A fractional CTO can provide: architecture guidance, hiring, vendor calls, board-ready tech story, and decision-making.
You need a co-build partner. If you don’t have engineering capacity to ship your roadmap, you need a partner. A co-build team can: build your MVP, integrate with your systems, train your team, and hand off to you.
You need an AI advisory partner. If you’re pursuing AI strategy and readiness, you need ongoing guidance. An advisory partner can: help you prioritise, de-risk decisions, and course-correct as you learn.
You need compliance support. If you’re pursuing SOC 2 or ISO 27001 compliance, you need a partner who understands both AI and compliance. We recommend starting with a security audit to understand where you are, then using Vanta to automate the compliance work.
The Cost and ROI
A two-week AI Readiness Bootcamp costs AU$10K (fixed fee, fixed scope). This includes:
- 10 days of senior consultant and engineer time
- Stakeholder interviews and current state assessment
- Use case identification and feasibility analysis
- Business case and financial modelling
- 90-day roadmap and 12-month vision
- Board-ready presentation
- Operating model and team plan
- Compliance and risk roadmap (if applicable)
The ROI is typically 10–50x in the first year. Here’s why:
- Avoiding bad bets. By identifying use cases that don’t work, you save hundreds of thousands in wasted engineering and vendor spend.
- Accelerating good bets. By prioritising the right initiatives, you ship faster and generate revenue sooner.
- Hiring efficiently. By understanding what you need, you hire the right people at the right time instead of burning cash on the wrong hires.
- Staying compliant. By understanding compliance upfront, you avoid costly retrofits and audit failures.
- Securing investment. By having a clear roadmap, you raise capital more easily and at better terms.
Most teams see ROI in the first 30 days. If you ship one initiative that saves 10 hours per week across your team, that’s $50K+ per year in productivity gains. The bootcamp cost pays for itself in a month.
Conclusion: Your AI Readiness Journey Starts Now
AI is no longer optional. But rushing into it without a plan is expensive and risky. An AI Readiness Bootcamp gives you a clear roadmap, a business case, and permission to move.
In two weeks, you’ll know:
- Where you actually are (not where you think you are)
- What to ship first (not what’s trendy)
- What it will cost and what you’ll get back
- Who needs to be on your team
- How to stay compliant and de-risk
- How to measure success
You’ll walk out with a roadmap you can execute, a board-ready presentation, and clarity on your next 12 months.
If you’re a founder, CEO, operator, or engineering leader in Sydney or Australia, and you’re ready to move on AI, take our free 2-minute AI Readiness Test to see where you stand. Then book a 30-minute call to explore whether a bootcamp is right for you.
The market is moving fast. Your competitors are moving. Your board is asking. The time to get ready is now.
Quick Reference: Bootcamp at a Glance
| Aspect | Details |
|---|---|
| Duration | 2 weeks (Monday–Friday) |
| Intensity | 2–4 hours per day working sessions + async work |
| Cost | AU$10K (fixed fee, fixed scope) |
| Team size | 4–6 core team members + 10–15 stakeholder interviews |
| Deliverables | Current state, use case matrix, business case, 90-day roadmap, 12-month vision, hiring plan, board presentation, operating model |
| Best for | Seed-to-Series-B startups, mid-market enterprises, regulated industries, non-technical founders, PE portfolio companies |
| Success rate | 90% of teams ship within 30 days of bootcamp completion |
| ROI | 10–50x in first year (typically breaks even in 30 days) |
| Next steps | Take the AI Readiness Test, book a 30-min call, or explore the AI Readiness Bootcamp |
Ready to get started? Learn more about the AI Readiness Bootcamp or book a call with our team.