Your Ultimate Guide to the 33A AI Design Sprint®: From Strategy to Execution.

Part 1: The Big Picture: Understanding the AI Design Sprint® Framework

Let’s start with the fundamentals. What exactly is this framework, who is it for, and how did it come to be?

What is the 33A AI Design Sprint®?

Think of it as a highly structured, collaborative workshop that gets all the right people in a room to solve a specific business problem using AI. It is a systematic process that combines methodologies from Design Thinking, Service Systems Design, and AI.

The main goal is to de-risk and speed up the adoption of AI within your company. Instead of lengthy debates and abstract planning, the sprint pushes teams towards creating tangible, testable ideas. It’s intentionally designed to be accessible for non-technical business leaders, empowering them to confidently lead AI initiatives.

The framework guides a cross-functional team from a vague challenge to a validated concept, complete with a technical brief and a clear roadmap for development

How is it different from the Google Design Sprint?

This is a common and important question. The 33A AI Design Sprint® is a deliberate evolution of the highly successful Google Design Sprint (GDS) developed at Google Ventures. It inherits the core philosophy of intense, time-boxed problem-solving to get fast results.

But the Danish agency 33A has specifically adapted and enhanced it for the unique challenges of AI. Here are the key differences

• Focus on AI: The 33A sprint is exclusively tailored for AI-related challenges, such as process automation, data strategy, or transforming products with AI. The GDS is more general, often used for product features or user interface design.
• Service Systems Design: This is a crucial addition. Many high-value AI projects aren’t just about a single digital product, but about redesigning an entire business workflow, like an HR onboarding process or a supply chain flow. Service Systems Design provides the tools to map, analyse, and remodel these complex internal systems, a classic challenge the standard GDS is not explicitly equipped to handle.
• Specialised Tools: The sprint uses a unique set of proprietary tools like AI Cards®, GenAI Cards®, and AI Ethics Cards® to make complex technology understandable and facilitate brainstorming for a non-technical audience.
• Modular and Flexible: While a traditional GDS is often a continuous five-day process, the 33A framework is more flexible. It can range from a one-day strategy session to a full two-week cycle from idea to prototype.

This specialised approach has earned an endorsement from Jake Knapp, the inventor of the original Google Design Sprint, and has been adopted by global corporations like Porsche, Microsoft, Bayer, and Mercedes-Benz.

Who should participate in an AI Design Sprint?

The framework is built for a diverse audience within an organisation. Success hinges on assembling a cross-functional team of about three to six experts. This isn’t just a meeting for the tech department. The ideal team includes:

• A designated “Decider”: This is essential. The Decider is a project leader or executive with the authority to make key decisions and break ties, ensuring the process keeps moving forward.
• Business Experts: People who understand the business area inside and out, from departments like marketing, sales, finance, operations, or HR. They bring the real-world context of customer needs and business pain points.
• IT and Data Specialists: Individuals who can provide immediate context on the organisation’s technical infrastructure, data availability, and systems.
• Non-Technical Leaders: A key principle of the sprint is to empower business leaders. No prior technical or AI knowledge is required to participate or even lead the ideation process. The tools and methodology are designed to bridge the knowledge gap.

What are the core principles that make it work?

The sprint’s success isn’t magic, it’s down to a set of guiding principles embedded into its structure.

• Simple Over Complex. No Tech Needed: This is the foundational idea. The sprint abstracts away intimidating technical jargon, using tools like the AI Cards® to turn complex capabilities into understandable concepts that business users can work with.
• Fast Results & Low Risk: The process is engineered for speed, aiming to move from an idea to a working prototype in as little as two weeks. This speed directly contributes to de-risking the project by front-loading validation. You test your ideas before you commit to the high cost of building them.
• Working Together, Alone: This counterintuitive technique is critical for generating high-quality, unbiased ideas. Participants are given time to think and sketch their ideas individually before sharing them with the group. This prevents “groupthink” and ensures a diversity of thought is captured.
• Tangible Over Discussion: To avoid getting lost in abstract conversations, ideas are immediately made concrete using sketches, notes, and the physical act of sorting cards. This ensures everyone is debating the same, clearly defined concept.
• Getting Started Over Being Right: The aim is to break “analysis paralysis”. The framework encourages teams to make a decision, create a testable hypothesis, and move forward quickly, knowing the process is designed for learning.
• Don’t Rely on Creativity: Innovation isn’t left to chance. The structured exercises and tools are designed to systematically generate solutions, removing the pressure on individuals to have a “eureka!” moment.

More questions on the Big Picture

Q: Is this framework only for large corporations like Porsche and Microsoft? A: Not at all. While those large corporations have successfully used the framework, it is designed to be applicable to organisations of all sizes, from startups to large enterprises. The principles of de-risking innovation and aligning teams are universal. The modular nature of the offerings, from short intros to full sprints, allows smaller organisations to engage at a level that suits their budget and resources.

Q: You mentioned ‘Service Systems Design’. What does that actually mean in this context? A: ‘Service Systems Design’ is a way of looking at a business challenge holistically, considering all the components involved. Instead of just focusing on a single piece of software, it designs the entire system of people, processes, and technology. In the context of the AI Design Sprint, this means that when you’re looking to automate a process, you don’t just think about the AI tool. You map out the entire workflow, such as an HR onboarding process, and redesign it to show how employees interact with the new technology and how the steps change. This is vital because most valuable AI applications augment or change how people work, which is a classic service design challenge.

Q: What exactly is the role of the ‘Decider’ and why is it so important? A: The ‘Decider’ is a team member, typically a project leader or executive, who has the authority to make key decisions and break ties. Their role is crucial for maintaining the sprint’s pace and effectiveness. In any creative process, teams can get stuck debating options. The Decider listens to the arguments and makes the final call, allowing the team to move forward without getting bogged down in endless discussion. This authority ensures that the sprint produces concrete decisions and not just a list of possibilities.

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Part 2: The Workshops Explained: Finding Your Starting Point

The 33A AI Design Sprint® isn’t a rigid, one-size-fits-all process. A key part of its design is its flexibility, offering different entry points to match your organisation’s maturity in its AI journey. The choice of where to begin depends entirely on how much clarity you already have regarding your AI objectives.

Think of the structure as a funnel, moving from a broad strategic view to a focused solution. The three entry points are:

1. Entry Point A: AI Opportunity Mapping (The 30,000-foot view for teams uncertain where to start).
2. Entry Point B: Framing (Focusing on a specific business unit or department that has been identified as a target).
3. Entry Point C: Concept Development (Designing the solution for a specific work process that has already been identified).

Let’s dive into the two main workshop formats that represent these entry points: Opportunity Mapping and the Sprint for Process Automation.

AI Opportunity Mapping: “Where should we even begin with AI?”

This is the widest entry point, a high-level, strategic workshop designed specifically for leadership teams. It directly answers the common executive question: “We know we need to do something with AI, but we have no idea where to start”.

The goal of Opportunity Mapping is to scan the entire organisation, or a broad portfolio of products and services, to uncover and prioritise the most valuable and impactful AI opportunities.

How does the Opportunity Mapping workshop work?

The process is systematic and tool-driven, and can often be completed in as little as one day.

1. Establish a High-Level View: The workshop starts with the business itself, not with technology. The team begins with a large-scale artefact that represents the area of focus, such as the company’s organisational diagram for a process focus, or simplified customer journeys for a product focus.
2. Systematic Ideation with AI Cards®: This is where the magic happens. Using a specialised canvas and the proprietary AI Cards®, the team systematically maps business pain points onto the high-level view. They then match potential AI capabilities from the cards to these high-impact areas, generating a landscape of potential projects.
3. Prioritise and Decide: The session moves from a wide array of possibilities to a structured evaluation. The team works together to prioritise the generated ideas, reaching a collective decision on the single most valuable opportunity to tackle first.

What is the outcome?

You don’t just leave with a long list of vague ideas. The tangible outcome is a prioritised backlog of potential AI projects and, crucially, a clear, consensus-driven decision on which specific area to focus on next. This sets the stage perfectly for a more detailed Framing or Concept Development workshop.

AI Design Sprint® for Process Automation: “How can we make our internal workflows smarter?”

This is the framework’s flagship offering for boosting internal efficiency and is the most common application of the sprint. Its purpose is to guide a team in identifying company processes that are ripe for automation and to collaboratively design a detailed AI solution concept. It’s frequently used to improve workflows in departments like HR, Sales, Finance, or Marketing.

This sprint takes a team from a broad departmental view down to a specific, well-defined solution concept. It can be entered at either

Entry Point B (Framing) or Entry Point C (Concept Development).

What does the Process Automation sprint involve?

The sprint follows a clear, phased progression.

Phase 1: Framing (Optional Entry Point B)

You start here if you’ve identified a department but not the specific process within it that needs attention.

• Map the Territory: The team maps out all the major tasks and responsibilities of the chosen department.
• Find the Sweet Spot: Using the Process Automation Canvas and AI Cards®, the team analyses these tasks to pinpoint the single process that offers the most value if it were automated. This framing session identifies the ‘sweet spot’ where AI can have the biggest impact.

Phase 2: Concept Development (Entry Point C)

This is the core design phase of the sprint, where the team dives deep into designing the actual solution.

• Map the Current Process: The workshop begins with a detailed mapping of the chosen work process, identifying specific steps, pain points, and inefficiencies.
• Brainstorm with AI & GenAI Cards®: The team performs a structured brainstorming exercise, using the cards to match specific AI capabilities to the pain points in the process map to generate solution concepts.
• Design the “To-Be” Process: From these ideas, the team develops a holistic solution, visualizing a remodelled “AI-work process” directly on the canvas to show how new AI-powered steps integrate with or replace manual ones.
• Perform an Ethics Check: This is a crucial, integrated step. The team uses the AI Ethics Cards to systematically discuss the potential ethical implications of their solution, ensuring responsible innovation is baked into the design from the start.

Phase 3: Assessment

Once a concept is developed, it undergoes a structured assessment.

• Evaluate the Solution: Using tools like the Data Sources Cards and Resources & Roles Cards, the team evaluates the concept across three critical dimensions: technical feasibility, value for the employee, and the overall business case.

More questions on the Workshops

Q: Can we skip Opportunity Mapping and go straight to Process Automation? A: You can, but only if you have sufficient clarity. The framework is designed with multiple entry points for this reason. If your team has already identified a specific work process they wish to improve, you can jump directly into Concept Development (Entry Point C). If you’ve targeted a department but not a specific process, you would start with Framing (Entry Point B). However, if there is broad uncertainty about where AI can even be applied, starting with the high-level Al Opportunity Mapping is highly recommended to ensure you focus on a problem that is truly valuable to the business.

Q: What if our leadership team doesn’t have a full day for Opportunity Mapping? A: The framework is designed for flexibility. While a full day allows for a deep dive, some modules are designed to generate value in as little as eight hours. The key is the focused, structured nature of the workshop. It condenses what would otherwise be weeks of scattered meetings into a single, highly productive session. It’s best to discuss specific time constraints with a certified facilitator, who can advise on how to tailor the session to get the most value out of the time available.

Q: Is Process Automation only for back-end, internal processes? A: While improving internal operational efficiency in departments like HR, Finance, or Sales is the most common application, the principles are not limited to back-end processes. The methodology is rooted in Design Thinking and Service Systems Design, which are used to improve any system of interaction. The same tools and techniques can be used to analyse and remodel customer-facing workflows or to transform existing products and services with AI capabilities.

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Part 3: The Engine Room: A Look at the Proprietary Tools

The promise of “no tech knowledge needed” is made possible by a cleverly designed suite of proprietary tools. These tools are the engine of the sprint, transforming complex technology into a tangible and collaborative brainstorming format.

The AI Cards® and GenAI Cards®: Demystifying Technology

The AI Cards® are the central innovation of the framework, existing in both physical and digital formats for flexible use. Their purpose is to organise the vast landscape of AI from a user’s perspective, not a technologist’s.

• Structure: The deck is grouped into about 13 high-level categories (e.g., “AI sees,” “AI forecasts,” “AI hears and talks”) that provide a digestible overview. The full deck contains between 77 and 99 cards, each describing a single AI capability in plain language.
• Use Cases: The real power comes from the reverse side of each card, which provides real-world business use cases (over 200 in the full deck) that illustrate how that capability is applied.

In a workshop, a team first maps out their business process and its pain points. Then, participants physically or digitally match the AI Cards® to the steps where an AI capability could solve a problem. This tactile, visual exercise allows non-technical users to effectively “design” an AI solution by composing it from a palette of understandable building blocks. Recognising the recent explosion in generative AI, 33A also developed a separate GenAI Cards® deck. This set of 85 cards focuses specifically on capabilities like text summarization, content creation, and code generation, with 220 use cases. The back of these cards may also list specific, accessible GenAI tools that can be used for immediate low-code or no-code prototyping.

Canvases and Ethics Cards: Providing Structure and Guardrails

While the cards provide the creative fuel, a set of canvases and other specialised decks provide the structure and ethical guardrails.

• The AI Design Sprint® Canvas: This is the central organising document for any workshop, available as a large-format printable PDF or a digital template for platforms like Miro. There are tailored versions for each module, such as the Process Automation Canvas. It provides the visual architecture for the entire session, guiding the team step-by-step.
• The AI Ethics Cards: This dedicated deck is used to prompt a structured discussion about the potential ethical implications of a proposed solution. This proactive approach ensures that responsible AI principles like fairness, bias, and transparency are a core part of the design process from the outset.
• Assessment Cards: During the final assessment phase, tools like the Data Sources Cards and Resources & Roles Cards facilitate a conversation about practical implementation. They prompt the team to think critically about what data is needed, its quality, and what skills will be required to build and maintain the solution.

More questions on the Tools

Q: Are the AI Cards® just a gimmick? How do they really help? A: They are far from a gimmick; they are a core mechanism that makes the sprint accessible and effective. Their real value lies in how they structure thinking. They demystify complex technology by breaking it into understandable capabilities. The physical (or digital) act of sorting and matching cards to pain points turns an abstract brainstorming session into a concrete, tactile exercise. This process forces a systematic analysis of a business problem and guides a non-technical team to design a complex AI solution in a way that feels playful and lowers the barrier to entry for what is fundamentally a disciplined strategic exercise.

Q: What happens if we identify an ethical issue with the Ethics Cards? Does that kill the project? A: Quite the opposite. The goal of the AI Ethics Cards is not to kill projects, but to make them better and more responsible. The cards are used to prompt a structured discussion among the team about potential issues like bias, fairness, and societal impact. By identifying these risks early in the design process, the team has the opportunity to proactively address them. The outcome isn’t cancellation, but rather the redesign of the solution to mitigate the ethical risks, ensuring that what you build is not only effective but also fair and trustworthy.

Q: Can we use our own brainstorming tools instead of the proprietary ones? A: The methodology and the proprietary tools are designed as a tightly integrated system. The canvases provide the step-by-step structure for the workshop , and the AI Cards® provide the specific, curated language to discuss AI capabilities in a way that is accessible to non-technical participants. While general brainstorming is always possible, the unique value of the 33A sprint comes from how these specific tools work together to guide a team through a complex process efficiently and effectively. Using them is key to replicating the successful outcomes the framework is known for.

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Part 4: From Idea to Reality: The Sprint Outcomes

A successful AI Design Sprint doesn’t just end with a good idea. It’s meticulously designed to produce tangible, actionable outputs that bridge the gap between the business concept and technical execution.

What are the tangible deliverables from a sprint?

The primary outcome is a comprehensive package that sets your development team up for success. This includes:

• One or Two Validated AI Solution Concepts: You’ll leave with a clearly defined and well-thought-out concept for an AI solution.
• A Detailed Technical Brief: This isn’t a vague wish list. It’s a blueprint for the next phase, translating the business-led concept into a language that developers can act on. It includes a full description of the solution, its required technical functionalities, identification of necessary data sources, and an initial assessment of its technical complexity.
• An Initial Business Case: A document outlining the value proposition and overall business case for the solution.
• A Development Roadmap: A clear, step-by-step plan for building a technical prototype.

What happens after the workshop?

The momentum from the sprint is channelled directly into the next steps of validation and development.

1. The Tech Check: This is a critical handoff. The Technical Brief is passed to an AI expert (this could be an internal data scientist, a consultant, or another technical stakeholder) who performs a formal technical feasibility check. This vital step validates that the concept is not just desirable, but also achievable with current technology and data.
2. The Technical Roadmap: Following a successful Tech Check, a meeting is held with the team to present the findings and collaboratively outline the concrete steps required to implement the solution.
3. Building the Technical Prototype: This plan guides the final stage of the sprint cycle: building a working model of the AI solution, complete with documentation. This functional prototype demonstrates the core functionality and serves as the foundation for a full-scale production launch.

This entire cycle, from initial idea to a working prototype, can be completed in just two weeks, representing a dramatic acceleration compared to traditional development timelines.

More questions on Outcomes

Q: What level of detail is in the ‘Technical Brief’? A: The Technical Brief is designed to be a comprehensive and actionable document, not a high-level summary. It serves as the primary handover document to the technical team. It includes a detailed description of the AI solution concept, a breakdown of all the required technical functionalities, a clear identification of the data sources needed to power the solution, and an initial assessment of the solution’s overall technical complexity. The goal is to provide enough detail so that a technical expert can immediately begin to assess feasibility and plan development.

Q: Who performs the ‘Tech Check’ and what if they disagree with the team’s idea? A: The Tech Check is performed by an AI expert. This could be an internal data scientist from your company, a consultant from 33A or one of its partners, or another trusted technical stakeholder. Disagreement or challenges during the Tech Check are not considered failures; they are a crucial part of the de-risking process. The expert’s feedback is used to refine the concept, adjust the technical approach, or pivot if a major unforeseen obstacle is discovered. This validation step ensures that you don’t invest in building an idea that is technically impractical.

Q: A working prototype in two weeks sounds unrealistic. How is this possible? A: This dramatic acceleration is possible because the sprint fundamentally changes the development workflow. A traditional process can involve months of meetings, debates, and inefficient communication just to define the problem. The Al Design Sprint® condenses this entire alignment and ideation phase into a few intense, highly structured days. The team emerges with a crystal-clear, validated concept and a detailed Technical Brief. This means the prototyping phase isn’t about discovery or debate; it’s about focused execution on a pre-defined, pre-vetted plan. This extreme focus is what makes the two-week timeframe achievable.

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Final Thoughts: The Strategic Value of the AI Design Sprint®

Adopting this framework offers clear, strategic benefits that address the most common pain points in corporate AI innovation. The value proposition is centred on tangible outcomes related to risk, speed, and organisational capability.

The Benefits for Your Organisation

• Massive Risk Mitigation and Cost Savings: Failed AI projects are incredibly expensive. The sprint is explicitly designed to de-risk this investment by validating ideas and assessing technical feasibility before major development resources are committed. By avoiding projects that are not aligned with business needs, this approach can save a significant amount of time and capital.
• Radical Speed and Efficiency: The time-boxed, focused nature of the sprint condenses what could take months of meetings into a matter of days or weeks. This dramatically accelerates the innovation cycle and shortens your time-to-market for new AI-powered services.
• Deep Organisational Alignment: A frequently cited outcome is the powerful cross-functional alignment achieved between business leaders and IT experts. The sprint forces these groups into a shared, collaborative space with a common goal, fostering the teamwork necessary for success.
• Building In-House Capability: The process itself is an intensive, hands-on learning experience. Non-technical participants in particular leave with increased confidence and a much clearer, more practical understanding of AI’s capabilities. This builds your organisation’s overall “AI-readiness”.
• User-Centric, Value-Driven Solutions: By anchoring the entire process in real user needs and business pain points, the sprint ensures that the resulting concepts are directly tied to creating genuine value.

More Than a Process: A Catalyst for Cultural Change

Beyond the practicalities, it’s worth highlighting the profound cultural shift the AI Design Sprint® can initiate. It democratises innovation by empowering non-technical leaders with the tools and confidence to drive AI projects. This process forges a common language between business and IT, breaking down silos and fostering the deep alignment crucial for implementation.

The Power of the Ecosystem

Furthermore, the value doesn’t end when the workshop is over. 33A has built an entire ecosystem around the methodology. When individuals or teams get certified, they gain access to an exclusive Alumni Community Platform. This transforms a one-time training event into an ongoing professional relationship, offering continuous learning and a network of peers to share best practices with.

Your Easiest First Step

Finally, for anyone curious but not yet ready to commit to a full sprint, there is a very accessible starting point. 33A offers free 90-minute “Experience Sessions”. These live webinars are designed to give you and your team a tangible feel for the methodology by developing an AI concept in a team setting, all without requiring any prior technical knowledge. It’s the ideal way to test the waters and see if the approach is the right fit for your organisation. Sources