Is Your Business Moat AI-Resistant? The Jobs-to-be-Done Litmus Test
Traditional defenses are crumbling. Uncover the four pillars of a JTBD-powered strategy to thrive in the age of AI-driven replication.
Table of Contents
The Crumbling Walls: Why Traditional Moats Are Under Siege by AI
The Unseen Fortress: Anchoring Defense in the Customer's Job-to-be-Done
A Novel Moat Strategy: JTBD-Powered Innovation in the AI Era
Case Study Sketch: From Feature Arms Race to Outcome-Dominance
If you’re long on time, and want to dive into a much deeper analysis of developing a competitive advantage with business moats, check out this 70 page research report on my other blog (you should subscribe 😉):
The Crumbling Walls: Why Traditional Moats Are Under Siege by AI
For decades, businesses have relied on established "moats" to protect their market share and profitability. Think of brand strength, built over years of consistent delivery and marketing; network effects, where a service becomes more valuable as more people use it; intellectual property (IP), like patents and proprietary algorithms; and high switching costs, making it difficult or expensive for customers to change providers.
Enter the age of Artificial Intelligence, particularly Generative AI. Suddenly, these reliable defenses are looking less like stone fortresses and more like sandcastles against a rising tide.
Rapid Feature Replication: AI tools can analyze existing software, understand user interfaces, and even generate functional code. Features that once took months or years to develop can potentially be replicated much faster, eroding the advantage of having a feature-rich product.
Hyper-Personalization: AI enables personalization at an unprecedented scale. This challenges brand loyalty built on generalized messaging or standardized experiences, as competitors can use AI to create deeply tailored interactions that resonate more strongly with individual users.
Content & Code Generation: Generative AI can create marketing copy, designs, software code, and more, diminishing the unique value proposition previously held by proprietary content or complex internal codebases.
Lowered Barriers & Switching Costs: AI can significantly lower the cost and complexity of developing sophisticated solutions. New entrants, leveraging AI, might offer alternatives that are not just cheaper but fundamentally better at getting a job done, drastically reducing a customer's perceived cost of switching.
This leads to a pressing question keeping executives awake at night: How do we build a lasting competitive advantage when technology itself offers diminishing returns as a differentiator? How do we compete when AI enables faster, cheaper replication of the very things we thought made us unique?
The Unseen Fortress: Anchoring Defense in the Customer's Job-to-be-Done
The answer doesn't lie in building better algorithms alone. It lies in shifting focus from the solution (your product, your features, your tech) to the problem – the fundamental progress a customer is trying to make. This is the core idea behind Jobs-to-be-Done (JTBD) theory.
JTBD isn't just another business acronym; it's a lens through which to view your market. It posits that customers don't simply buy products or services; they hire them to get a specific "job" done in various situations, or combinations of situations. They are trying to achieve desired outcomes and improve their ability to accomplish goals, tasks, or objectives.
Why is this different? Traditional approaches often focus on customer demographics ("Who are they?") or product attributes ("What features do they want?"). JTBD focuses on the "why": What outcome is the customer striving for? What struggles are preventing them from achieving it reliably and efficiently?
The Core Principle: A customer facing a struggling moment looks for a solution to hire that will lead to a successful outcome. Understanding this "job" in excruciating detail provides a stable target for innovation, unlike fleeting technological trends or feature requests.
AI's Limitation (For Now): AI excels at optimization and execution – the how. It can analyze data, generate options, and automate tasks with incredible speed and efficiency. However, AI fundamentally lacks the ability to independently understand the nuanced, often unarticulated, context-rich "why" behind a customer's actions. It cannot conduct empathetic interviews, synthesize conflicting needs, or prioritize the unstated emotional outcomes that often drive purchasing decisions without significant human-led research and strategic direction.
This is where the opportunity lies. A deep, proprietary understanding of the customer's Job-to-be-Done becomes a strategic asset that AI alone cannot replicate.
A Novel Moat Strategy: JTBD-Powered Innovation in the AI Era
Building a durable moat in the age of AI requires anchoring your strategy in this deep customer understanding. It’s a four-pillar approach:
Pillar 1: Deep Outcome Discovery – Your Unique Blueprint.
The first step is rigorous research to define the core functional job(s) your customers are trying to get done and, critically, all the desired outcomes they use to measure success. This involves:
Qualitative Research: Conducting specific types of customer interviews designed to uncover the "job" and the struggles encountered. More recently, this approach has been disrupted with implementations of an AI architecture to interview the corpus of human knowledge instead of relying on a handful of potentially biased, or limiting, interviews.
Defining Outcome Statements: Translating customer needs into precise, measurable, solution-agnostic "desired outcome statements" (e.g., "Minimize the time it takes to identify the root cause of a production error," "Reduce the likelihood of misinterpreting the client's requirements").
Quantitative Prioritization: Surveying a larger customer base to quantify which outcomes are most important and least satisfied.
This granular, structured understanding of what success means to your customer becomes your unique innovation blueprint – a proprietary asset that competitors (AI-driven or otherwise) cannot easily obtain without undertaking the same rigorous process.
Pillar 2: Innovate to Get the Entire Job Done Better – Elevating the Level of Abstraction.
Armed with prioritized outcome insights, the focus shifts from incremental feature improvements to holistic job completion. How can you help the customer achieve their entire objective more successfully, with less effort, fewer trade-offs, and reduced need for compensating solutions?
This often involves elevating the level of abstraction. Instead of providing better tools within a complex process, you create solutions that handle more of the underlying process complexity, presenting a simpler, more outcome-focused experience to the user or beneficiary. The goal is often a solution with fewer visible features but which delivers the desired outcome more completely and efficiently.
Working Today Example: Consider specialized B2B SaaS platforms. A company might create a platform for "managing commercial construction projects." Instead of just offering scheduling or document management (like generic tools), it integrates bidding, compliance tracking, subcontractor communication, and financial reporting specifically tailored to that industry's job. It replaces 3-4 separate tools and manual processes with one system focused on the higher-level job: "Successfully deliver commercial construction projects on time, on budget, and to spec." The user interacts with fewer systems, even if the underlying complexity handled is greater. The job performer (e.g., Project Manager) is freed up for higher-value activities.
Novel Concept Example: "Strategic Market Entry as a Service." Today, entering a new market requires market research firms, CRM software, marketing automation tools, sales enablement platforms, etc. And we still experience a high level of failures. Imagine a future service where a business defines the high-level job:
"Successfully enter the German market for widget X and achieve Y% market share within 3 years."
A sophisticated system, powered by AI but guided by deep JTBD insights about the hundreds of desired outcomes involved in market entry (from regulatory navigation to channel partner recruitment to initial lead generation), would orchestrate much of this. It would perform analysis, generate strategic options, manage workflows, automate tasks, and present key decision points to the human strategist. The job performers shift dramatically. The solution gets a massive, complex job done far better, likely faster and cheaper overall, through a radically simplified interface focused on strategic goals, not tool management.
This is coming.
Pillar 3: Build Proprietary Insight, Not Just Proprietary Code.
In this new landscape, your most valuable IP isn't just your software code or algorithms; it's your structured, deep, and evolving understanding of your customer's desired outcomes. This insight – knowing which outcomes matter most, where the biggest struggles lie, and how different customer segments prioritize things differently – is the strategic differentiator.
AI and technology then become powerful enablers to:
Develop products that systematically address the most important, underserved outcomes.
Craft marketing messages that resonate deeply with customer priorities.
Deliver customer service that proactively solves problems related to achieving the job.
Personalize experiences based on outcome priorities, not just behavioral data.
AI can be applied to your proprietary outcome data to create unique value that competitors cannot easily match because they lack the same foundational understanding.
Pillar 4: Create a Moving Target with Continuous JTBD-Driven Innovation.
While the customer's job and their desired outcomes are stable over time, the hierarchy-of-action isn’t static. Market conditions change, technologies evolve, and expectations rise. Context shifts, job executors change. The JTBD framework isn't a one-time project; it's a continuous process. But, it’s not a constant influx of bespoke methods — which is what you experience today.
By regularly refreshing your understanding of the customer's job and identifying new or evolving unmet outcomes, you can:
Proactively identify opportunities for disruptive innovation.
Continuously improve your offering in ways that matter most to customers.
Stay ahead of competitors by focusing on future customer needs.
This creates a moving target. Even if a competitor copies your current features, you are already working on the next evolution, guided by your unique insights into where the customer is struggling next. This relentless focus on outcome-driven improvement becomes a powerful, dynamic moat.
Case Study Sketch: From Feature Arms Race to Outcome-Dominance
Consider "Company Alpha," a provider of project management software. They were caught in a feature arms race, constantly adding new bells and whistles to match competitors, many of whom were using AI to quickly replicate functionalities and offer lower prices. Margins were shrinking, and differentiation was eroding.
Company Alpha decided to pivot, investing heavily in JTBD research. They defined the core job not as "track tasks" but as "Ensure complex projects deliver their intended strategic business value on time and within budget." They uncovered dozens of crucial desired outcomes related to risk mitigation, stakeholder communication, resource allocation, and strategic alignment – many of which were poorly addressed by existing tools focused solely on task management.
Outcome-Oriented Innovation: They re-architected their platform. Using AI, they automated mundane task tracking but surfaced proactive alerts about risks to the project's strategic goals. They integrated tools for clearer stakeholder reporting focused on business value, not just task completion. They simplified resource allocation based on impact on critical outcomes. The new interface was actually simpler in many ways, hiding the low-level complexity and focusing the user on achieving the high-level project job successfully.
Result: Company Alpha shifted from being a tool vendor to a strategic partner. Customers using the new platform reported higher project success rates and felt more in control of delivering value. While competitors could copy individual features, they couldn't replicate the integrated system designed around the complete job and its critical outcomes. Alpha created a durable moat based on superior outcome delivery, not just features.
The Future is Outcome-Centric, AI-Powered
AI is undeniably transforming business, but it's a powerful tool, not the ultimate strategy in itself. The companies that thrive in the coming decades will be those that use AI as an enabler to achieve a deeper, more fundamental goal: relentlessly focusing on helping customers get their jobs done better.
Start the Shift: Begin by asking different questions. Instead of "What features should we add?" ask "What core job is our customer trying to accomplish?" Instead of "How can we use AI?" ask "Where is our customer struggling most to achieve their desired outcomes, and how can AI help us solve that specific struggle?"
Invest in Understanding: True understanding of customer jobs and outcomes requires dedicated research. It’s an investment, but the strategic clarity and innovation potential it unlocks are invaluable.
Integrate JTBD and AI: View AI not as a replacement for strategy, but as a powerful engine to execute a strategy built on deep customer understanding. Use your JTBD insights to guide your AI initiatives.
The most resilient moat of the future won't be built solely on technology, brand, or network effects, although those still matter. It will be built on a superior, continuously improving, and proprietary understanding of your customer's Job-to-be-Done, and your ability to orchestrate resources – including AI – to help them achieve it more successfully and effortlessly than anyone else. This is a human-centered approach, powerfully augmented by technology.
Let's discuss this:
What traditional moats in your industry do you see as most vulnerable to disruption by AI right now (May 2025)?
Can you identify a high-level customer job in your market that is currently underserved? If a solution could get that entire job done perfectly and effortlessly (potentially requiring fewer visible features and changing who performs the job), what would that look like?
Share your thoughts, examples, and challenges in the comments below!
If you’d like to take action, I would love to help. Here’s are some steps you can take to make that a reality for us:
Join my community and get access to more content and tools
Apply for coaching so we can do projects together and build a new business-as-usual with someone who will share the knowledge, and hold you accountable. (I have limited seats so hurry!)
I do project work as well. Use the coaching link and we can discuss.
Why Me?
I often turn down projects that don’t align with my expertise to maintain the quality of my work.
I’ve been trained by the best in Outcome-Driven Innovation. Part of that training involved how to understand what the future should look like. As a result, I’ve taken what I’ve learned and begun innovating so I can get you to the outcomes you’re seeking faster, better, and even more predictably. Anyone preaching innovation should be doing the same; regardless of how disruptive it’ll be.
How am I doing this?
I’ve developed a complete toolset that accelerates qualitative research to mere hours instead of the weeks or months it used to take. It’s been fine-tuned over the past 2+ years and it’s second-to-none (including to humans). That means we can have far more certainty that we’ve properly framed your research before you invest in a basket of road apples. They don’t taste good, even with whipped cream on top.
I’m also working on a completely new concept for prioritizing market dynamics that predict customer needs (and success) without requiring time-consuming and costly surveys with low quality participants. This is far more powerful and cost effective than the point-in-time surveys that I know you don’t want to do!
I believe that an innovation consultant should eat their own dog food. Therefore, we must always strive to:
Get more of the job done for our clients
Get the job done better for our clients
Get the job done faster for our clients
Get the job done with with fewer features for our clients
Get the job done in a completely different and novel way for our clients
Get the job done in a less costly manner for our clients
But more importantly, I strive to deliver high quality and high availability. That's why I also have to be choosy.
All the links you need are a few paragraphs up. Or set up some time to talk … that link is down below. 👇🏻
Mike Boysen - www.pjtbd.com
Why fail fast when you can succeed the first time?
📆 Book an appointment: https://pjtbd.com/book-mike
Update your small business tech stack: https://pjtbd.com/tech-stack