What's an AI Design Sprint™?

Hi there,

This week, I had an exciting time leading an AI Design Sprint™ in person. It was refreshing to collaborate face-to-face after so many online meetings.

While the AI Design Sprint™ works perfectly online (we still used a Miro board instead of a physical canvas), there's something unique about being together in the same room in person.

And since a lot of you have asked me what an AI Design Sprint™ is and how it works, I'll focus on that in today's newsletter.

Let's go!

📣 Join me for DSC Europe, November 20-24 in Belgrade, where I'll speak alongside an incredible lineup of speakers including Cassie Kozyrkov, Jepson Taylor, and Tarry Singh!

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Why companies often start with AI by accident - and why that's problematic

Most companies jump into their first AI project by chance. They may be inspired by a competitor's success or feel impulsive about a new technology.

While there's an element of excitement in this approach, it often leads to costly mistakes down the road.

Imagine being months into a project, six-figure budget tanked, and then questioning the purpose of it all.

The AI Design Sprint™ essentially helps you avoid this pitfall.

It's a proven framework that doesn't fixate on the technology, but instead starts with understanding the business, pinpointing pain points, and identifying potential AI applications.

This user-centered methodology prioritizes business needs to uncover valuable AI use cases.

Invented in Denmark, global impact

Created by 33A in Denmark, the AI Design Sprint comes highly recommended by none other than Jake Knapp, inventor of the Google Design Sprint.

Renowned organizations around the world, including brands like Porsche, Microsoft, Bayer, and Mercedes-Benz, have leveraged this approach with 33A to unlock powerful AI use cases for their business.

Tailoring the AI Design Sprint™ to You

The AI Design Sprint adapts to your specific business context through three distinct entry points:

A: Start at the top: This approach engages top-level management, focusing on high-impact business areas and identifying AI opportunities from an organizational, or products/services perspective using the so-called AI Cards (more on these below). That’s why this module is called Opportunity mapping.

For example, if you run an AI Design Sprint™ for a large corporation, you could map out business pain points and AI opportunities on the org chart as shown in the (hypothetical) example below:

B. Department-focused approach: This is the most common entry point. It starts with a particular department, like HR, Sales, or Marketing. Within this department, we typically try to improve existing processes by automating or augmenting them with AI. Hence, this module is called Process Automation.

For example, we could look at the HR department and see how AI can help address specific pain points in that department before building a solution concept for a use case:

C. Product-focused approach: Here, the sprint starts with a specific Product or Service, and explores how AI can improve the customer experience here along the customer journey. For example, this could focus on improving a company's mobile app or e-com store.

Common principles

Irrespective of the starting point, the following core themes remain consistent across all modules:

• Aligning with business objectives

• Collating pain points

• Team alignment

• User focus

• Mapping AI capabilities to address these challenges

That’s the DNA of every session.

Demystifying AI with AI Cards

A powerful core component of every AI Design Sprint™ is the AI Cards. They are a brilliant innovation designed to make AI concepts easily accessible to non-technical business people.

These cards break down AI capabilities from a user's perspective, making it easier to see how AI can resolve current business challenges.

Each card, categorized by color, represents a different level of complexity, with yellow indicating the simplest and green the most complex.

In total, there are:

• 77 AI Cards

• 13 AI categories

• 231 use case examples

Here’s an example of how the AI Cards look like:

Developing Solution Concepts with an AI Design Sprint™

No matter if you choose the Process Automation, or Products & Services entry point, there are two phases that are covered in a sprint:

Phase 1: Framing Session

This initial phase sets the stage, providing context and structure around the business problem. Depending on the module, this could involve mapping different process steps in a department processes (Process Automation module), or outlining the user journey within a particular product/service (Products & Services module).

In both cases, the goal is to identify key focus areas for an AI-enabled solution and prepare you for a deep dive in the concept development session.

Typically, this framing-session talks about half a day.

Phase 2: Concept Development & Assessment

In the Concept Development phase, we transform an existing business workflow (or product user journey) into an improved, AI-powered process.

The goal is to develop an in-depth solution design that addresses specific pain points in the given process, and remodel that process with AI automation or augmentation.

In this phase, we want to think big. We want to embrace AI's opportunities and envision how it can transform our business. (The – much-needed – reality check comes in the Assessment session that follows).

The Concept Development phase is a deep dive, involving multiple steps and iterations, covering both process and technical aspects, as well as ethical concerns and describing the human-AI interaction.

Ultimately, the result of this phase is a thought-out solution design for our AI use case.

It takes about half a day of focused team work for a given process.

Assessment

The Assessment phase is typically a direct follow-up to the Concept Development phase.

The same team that created the AI solution in Concept Development also gauges its technical feasibility, employee benefit, and business value – with the support of the sprint facilitator, of course.

This includes reviewing high-level data requirements, as well as the roles and skills required in the organization to launch and maintain the use case.

Depending on the complexity of the use case, this assessment takes another half to full day.

Results & Next Steps

As the result of an AI Design Sprint™, we now have two things:

1. An overview of AI opportunities / use cases relevant to our business

2. A detailed solution concept for a selected use case of high relevance

The solution concept is the basis for a more detailed technical feasibility check and a requirements doc for delivering a prototype or POC in the next step.

Depending on the use case, we might break it down into even smaller steps or increments using the Atomic Use Case approach. In an agile way, we develop the use case further and improve it incrementally towards our expected solution.

This is how we bring the solution concept into production, by taking step-by-step actions and continuously improving the process with real-user feedback.

Conclusion

The AI Design Sprint™ offers a structured, user-centric path to ensure your AI projects align with your business objectives and truly add value.

It's a journey that turns abstract AI ideas into tangible, impactful business solutions - in just 2 days!

As always, if you're looking to get started, I'm here to guide you.

Feel free to book a call with me (and use code FREEFLOW for free checkout), or just reply to this email to explore how I can help you grow your business with AI.

See you next Friday!

Tobias