For decades, Adobe was the high priest of the creative arts. PostScript, invented in 1982, was a major force in the Desktop Publishing (DTP) revolution. Thanks to Adobe’s technology, designers only needed a humble Apple Macintosh computer and a LaserWriter to produce professional-grade graphic designs.
Its software suite, with Adobe Photoshop, Illustrator, InDesign, and, of course, Adobe Acrobat, was a literacy one that one had to spend years mastering. It created a two-tier graphic designer divide: those who were proficient in using those tools and those who were not.
Generative AI changed this in only three years. The dynamics of this change reflect how this technology will transform markets and the future of work. When GenAI took the world by storm in 2023, the market viewed Adobe as the ultimate beneficiary. If AI could automate the tedious parts of design, surely the “Creative Cloud” would become an unstoppable super-app. By February 2024, Adobe’s stock had surged from $275 (£206) to $630 (£471), fuelled by the launch of Firefly, the AI-powered tool in the Adobe Apps.
But then, the narrative curdled. By early 2026, the share price had cratered by 60% to $255 (£191) in February.
To understand why, we must look past the quarterly earnings and into a framework that will likely be standard MBA curriculum by 2030: the shift from Jobs-to-be-Done (JTBD) to the MOA Framework.
Limits of the Job-to-be-Done
For years, product managers have lived by the gospel of Job-to-be-done (JTBD). The theory, popularised by the American academic and business professional Clayton Christensen, suggests that customers don’t buy products, they hire them to do a job. A marketing manager doesn’t hire Adobe Illustrator to anchor points on a vector path, they hire it to produce a brand-compliant social media asset.
JTBD is excellent at explaining what customers want to get the job done, but it does not indicate what products and services they need. To understand this dynamic, we can use the MOA framework: motivation, opportunity and ability.
In the MOA model, a behaviour – such as using Adobe Illustrator – requires that all three factors are met.
- Motivation: the internal drive to achieve the goal (e.g., ‘I need this ad to look professional’).
- Opportunity: the external factors that make the action possible (e.g., ‘I have the budget and the time’).
- Ability: the individual’s internal skills or resources to execute (e.g., ‘I know how to use the Pen tool’).
Adobe’s ability collapse
Historically, Adobe’s business model was a bet on the ability gap. Professional design was a high-friction activity. Because the ability required was so high, Adobe could charge a premium – only pros had the competence to navigate their complex user interface.
When Adobe integrated Firefly AI, they believed they were simply enhancing their users’ ability. They were wrong. They were actually commoditising it.
By making professional looking design accessible via a text prompt, Adobe inadvertently destroyed the scarcity of the very skill they monetised. This created a causal link that analysts missed in 2023: as the ability requirement for a job drops toward zero, the value of the specialised tool hosting that ability also drops.
Consider the prosumer segment. In 2022, a small business owner had the motivation to create an ad but lacked the ability to use Photoshop. They had to hire an Adobe-equipped freelancer. Today, tools such as Canva, Midjourney and specialised AI video generators provide that skill and ability natively.
The causal chain looks like this:
- Gen AI lowers the ability threshold: tasks that once required 10,000 hours of mastery now require 10 seconds of prompting.
- The job moves to the cheapest ability’provider: If the JTBD (the high-quality ad) can be satisfied by a $20/month AI tool that requires no training, the $60/month Adobe suite (which still carries the baggage of legacy complexity) loses its opportunity (the ‘O’ in MOA) to be the chosen solution.
- The substitution effect: Adobe becomes a luxury that fewer companies can justify when ‘good enough’ is cheaper, faster, and available elsewhere for a fraction of the price.
In the old world, Adobe sold tools that only experts could wield. In the new one, it sells tools that create on their own, but so does everyone else. When creative ability shifts from the human mind to the software itself, the software stops being special and starts becoming a commodity.
The future textbook lesson
In five years, textbooks will point to Adobe Firefly as a case study for the democratisation trap. It is the moment an incumbent solves its customers’ biggest pain point so effectively that it accidentally deletes the reason for its own existence.
Adobe is currently a company in search of a new moat. They still have enterprise workflows and the opportunity to be the industry standard for large corporations. But as the MOA framework teaches us, if the ability to do the work becomes universal, the price you can charge for it eventually trends toward zero.
For leaders, the implication is not to abandon frameworks like Jobs‑to‑be‑Done, but to use them more rigorously and more honestly. JTBD remains invaluable for clarifying what customers are ultimately trying to achieve, today and tomorrow, independent of any particular product or technology.
But that analysis must now be paired with a forward‑looking MOA lens. Executives need to ask not only what job the customer wants done, but how motivation, opportunity, and ability are shifting as AI collapses skills, reduces friction, and redraws cost curves. Where motivation intensifies but ability becomes universal, value will migrate.
Where opportunity is constrained – by regulation, workflow integration, trust or scale – new moats can still be built. Competitive advantage in the AI era will not come from owning the job itself, nor from hoarding expertise that algorithms can replicate, but from deliberately positioning the firm at future intersections of motivation, opportunity and ability where scarcity still exists.
Leaders who fail to map those future MOA configurations may continue to serve the right jobs – only to discover that someone else is being paid for them.
Stefan Michel, professor of management, dean of faculty and research at IMD Business School, Switzerland.
For decades, Adobe was the high priest of the creative arts. PostScript, invented in 1982, was a major force in the Desktop Publishing (DTP) revolution. Thanks to Adobe’s technology, designers only needed a humble Apple Macintosh computer and a LaserWriter to produce professional-grade graphic designs.
Its software suite, with Adobe Photoshop, Illustrator, InDesign, and, of course, Adobe Acrobat, was a literacy one that one had to spend years mastering. It created a two-tier graphic designer divide: those who were proficient in using those tools and those who were not.
Generative AI changed this in only three years. The dynamics of this change reflect how this technology will transform markets and the future of work. When GenAI took the world by storm in 2023, the market viewed Adobe as the ultimate beneficiary. If AI could automate the tedious parts of design, surely the "Creative Cloud" would become an unstoppable super-app. By February 2024, Adobe’s stock had surged from $275 (£206) to $630 (£471), fuelled by the launch of Firefly, the AI-powered tool in the Adobe Apps.
