Discovery Workshops: The Must-Have in Your AI Journey

There's a pattern we often see in companies exploring AI: a lot of excitement, a few vendor demos, maybe a pilot that goes nowhere, and then a quiet retreat to the status quo. Not because AI doesn't work — it does. But because the wrong problem was picked, or the right problem was never properly defined in the first place.

This is exactly why Discovery Workshops exist. And it's why, at Switch, they're not a nice-to-have; they're Step One.

The Real Problem With AI Adoption Isn't Technology

The organizations that struggle most with AI adoption aren't failing for lack of technical capability. They're failing because they skipped the thinking part.

They jumped from "we should be doing AI" to "let's build something" without spending time in the space between: understanding what's actually broken, what would truly make a difference, and whether an AI-based solution is even the right answer.

Discovery Workshops are designed to close that gap. They create a structured, collaborative space where business leaders, operational teams, innovation, UX, and technology experts sit in the same room and work together to find the pain worth solving.

What a Discovery Workshop Actually Is

At Switch, a Discovery Workshop is a facilitated working session that brings together key stakeholders from your organization alongside our Innovation Hub team, including UX Research, Innovation, and Commercial leads.

The goal isn't to pitch a solution. The goal is to understand the business.

A well-run workshop does more than generate ideas; it prevents organizations from building the wrong thing. At Switch, we see these sessions as a way to deliver four things before a single line of code is written: clarity on which problem is actually worth solving, alignment across teams that may not yet share the same view, focus on the opportunities with the highest potential, and better-informed decisions that let clients move forward with less risk and more confidence.

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That's what makes the workshop valuable in itself, and that’s why over the course of the session, we work through:

• Process mapping and friction identification:  Where are the bottlenecks? What tasks eat up the most time? Where do errors cluster?
• Challenge prioritization: Not every pain point deserves an AI solution. We help teams separate the high-impact problems from the noise.
• Opportunity framing: Once a real business problem surfaces, we shape it into a clear hypothesis: what would measurably change if this were solved?
• Use case definition: We identify one or two concrete AI use cases with clear success metrics, realistic scope, and an obvious path forward.

The output is a decision-ready shortlist of opportunities, grounded in your reality rather than what sounds good in a proposal.

Two Types of Conversations, One Method

When clients come to a Discovery Workshop, they usually arrive in one of two places.

Some already have an idea:  "We think AI could help us process contracts faster" or "We want to automate our customer intake." In these cases, the workshop is about pressure-testing that idea: Is the business problem real? Is the data available? Is the expected value actually quantifiable?

Others arrive with a more open question: "We know AI matters, but we're not sure where to start." This is just as valid, and actually where workshops shine brightest. We bring a structured ideation process that combines horizontal use cases (applicable across industries, like document analysis, customer service automation, or internal copilots) with vertical ones specific to your sector. The combination gives the conversation depth and keeps it grounded in practical, achievable outcomes.

Both paths lead to the same destination: a prioritized initiative with defined metrics and a clear path to validation.

From Discovery Workshop to What Happens Next

A Discovery Workshop is not the end of the journey; it's the beginning. The reason it matters so much is what it unlocks downstream.

Once a use case is identified and validated in the workshop, the process moves into structured qualification (what we call the Align phase), which assesses technical feasibility, data readiness, and organizational capacity. Only after that alignment does a Proof of Concept begin — a fast, low-risk, typically complimentary prototype designed to test both technical viability and business value before any significant investment is made.

This sequencing matters. It means you're not betting on a solution before you've validated the problem. It means the first real dollar spent goes toward something that's already been co-designed with your team and pressure-tested against your reality.

The methodology draws on the same framework that AWS uses across its AI Innovation Center programs, and it's one of the reasons Switch, as AWS AI Services Competency Partner, is particularly well-positioned to guide organizations through this process.

A Real Example

Abstract methodology is easier to understand with a concrete case. A leading logistics operator in Uruguay, already a Switch client, embraced the workshop as a space to openly share their operational challenges and work together toward the best way to address them.  

The team ran a collaborative, iterative session that mapped out operational processes, surfaced day-to-day friction points, and explored the organization's information needs from multiple angles. No assumptions were made upfront about what the solution would be.

What emerged wasn't a technology recommendation. It was a shared understanding: a clearly defined business problem that both teams could see, name, and agree was worth solving. That clarity became the foundation for everything that followed.

From there, we moved into the next phase together: validating the opportunity, assessing feasibility, and defining the scope of a first initiative.

That finding directly shaped the next step: a first MVP initiative to be built on AWS; this path forward was concrete, low-risk, and grounded in what the organization actually needed.

None of that would have been possible, at least not that cleanly, without the structured discovery session that preceded it.

Why This Approach Builds Confidence (And Speeds Up Decisions)

One of the less obvious benefits of a Discovery Workshop is its impact on internal alignment and executive buy-in.

When an AI initiative emerges from a collaborative session that includes business leaders, operational teams, and a clear methodology, rather than arriving fully formed from an external vendor, it carries a different kind of weight. The people who have to approve it helped define it. The metrics it's measured against are the ones they chose.

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That changes the conversation at the boardroom level. Instead of defending a technology investment, you're presenting a business decision backed by evidence from your own organization.

It also dramatically reduces implementation risk. Solutions built on top of well-understood problems, with pre-validated data and clearly defined success criteria, simply have a higher success rate than those that don't.

What Makes a Good Use Case

Not every operational challenge is a good candidate for AI. In workshops, we apply a consistent lens across three dimensions:

Impact — Does solving this problem create measurable business value? Can we define specific KPIs — cost reduction, time savings, productivity gains, improved customer satisfaction — that would shift if the solution works?

Feasibility — Is the data available and of sufficient quality? Is the technical complexity proportionate to the expected benefit? Does it fit within a sensible architecture?

Readiness — Does the organization have the internal sponsorship, the data governance, and the operational willingness to support a pilot and adopt a solution?

When all three dimensions align, you have a use case worth building. When they don't, you've saved significant time and money by finding out early.

The Invitation

If you've been circling AI conversations in your organization,  curious, maybe cautious, not quite sure where to start, a Discovery Workshop is the most practical first step available to you.

It produces clarity. And in most cases, it reveals at least one opportunity your team didn't know it had.

Switch runs these workshops with a consistent methodology; the outcomes are always specific to the organization in the room.

If you'd like to explore what one might look like for your team, we're ready to start that conversation.

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