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JTBD Isn't About a Framework. It's About Focus.

The real job of Jobs to Be Done? Building the shared context that lets leaders and teams make better decisions faster.

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After last week's Design Shift conversation, my inbox lit up with questions about how we actually apply JTBD in real organizations, especially when integrating AI, and the questions weren't about theory but about execution: "How do we get alignment?" "Where do we start?" "How do we avoid building the wrong thing?"

Here's what I've learned after more than a decade of applying this across sectors: the biggest risk in AI transformation isn't the technology. It's the absence of shared understanding on desired outcomes and focus across leadership and teams.

When design, product, engineering, business, and ops aren't aligned on what job you're actually trying to improve, you end up automating broken processes and optimizing work that shouldn't exist in the first place.

That's where JTBD becomes essential, not as a UX exercise, but as a leadership tool.

Context Is Your Competitive Advantage

Most leaders treat frameworks like JTBD as research methods. They're missing the point.

JTBD is a decision-making accelerator. It creates actionable shared language that your executive team needs to move from "Should we use AI?" to "Where should we deploy it, and why?"

When I work with leadership teams, JTBD gives us three things immediately:

Clarity: What specific job(s) are we trying to improve?
Structure: What's upstream, what's downstream, what breaks if we get this wrong?
Focus: What's the smallest unit of work where AI adds value without scaling chaos?

This transforms how your teams operate. Your engineers stop asking "What are we building?" and start asking "What job are we supporting?" Your operations team can see dependencies. Your board can see ROI.

Why Small Jobs Win Big

Here's what I tell every leadership team: start with smaller jobs in the context of big transformations.

The big job defines your realm and strategic intent. The smaller job lets you take action and build capability. Big jobs are essential for context and direction, but they're too abstract to automate effectively on their own. Little jobs, when anchored to that larger purpose, are where AI delivers tangible value and organizational trust gets built.

I worked with a global organization recently to integrate AI agents across service, sales, and onboarding. We mapped over 200 jobs across functions, then deployed AI only where the job performer and desired outcome were crystal clear.

Result? A few weeks from theory to a working prototype that hit a high-value opportunity. Not just because we moved fast, but because we had alignment on where to focus and why.

The Strategic Architecture Layer

This is what separates tactical AI adoption from strategic transformation: JTBD becomes your connective tissue between business goals, customer experience, and technology delivery — it cuts through the full stack.

When your leadership team understands this, the conversation shifts:

  • You're not "deploying AI" but enabling specific outcomes

  • You're not "using GenAI" but augmenting job performers

  • You're not "designing features" but optimizing systems

This clarity lets you answer the questions your board is asking: Where do we start? How big should we go? Why there?

What This Looks Like in Practice

Every JTBD+AI workshop I run with leadership teams follows the same pattern:

Map with the people doing the work. Top-down maps miss the nuance that makes or breaks AI deployment.

Never automate ambiguity. If the job isn't clear to humans, AI won't fix it, but will scale the confusion.

Keep jobs visible. Create a tangible artifact like a JTBD map that becomes your reference system in every strategic review, not just another research deliverable.

Make job conversations a habit. When your leadership team is fluent in "what's the job here?" you're ready for change because you can see it coming.

The Leadership Imperative

AI is moving fast. Your competition is moving even faster. But speed without context can create expensive mistakes and organizational confusion.

The leaders who win aren't the ones who deploy AI first but the ones who deploy it with purpose. JTBD provides that purpose, packaged in a language your entire organization can understand and act upon.

In a rapidly changing business environment, ambiguity is risky and expensive. Creating a tangible shared understanding and context is the leadership skill that enables high-performing product delivery and sustained momentum.

Next series: I'll walk through how to create JTBD maps that actually work at scale, plus the templates and traps every leader should know.

Want to explore this for your organization? Drop me a note. Let's build systems that scale, together!

Mario Ruiz helps design and business leaders navigate transformation through human-centered strategy. His work spans Fortune 500 and private companies across multiple sectors.

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Want to go deeper?

I've co-authored a comprehensive white paper with Paul Bertucci (Salesforce Distinguished Architect) that shows exactly how to integrate JTBD with Strategic Enterprise Architecture for digital transformation. "A New Paradigm in Digital Transformation" walks through the complete framework we use with Fortune 500 companies, including detailed capability mapping, AI integration strategies, and business value modeling that drives real ROI.

Download the full framework below and see how leading organizations are using JTBD to build competitive advantage through strategic technology decisions.

"A New Paradigm in Digital Transformation: Integrating Jobs to Be Done with Strategic Enterprise Architecture" by Paul Bertucci and Mario Ruiz

A New Paradigm in Digital Transformation.pdf1.60 MB • PDF File

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