Inside the Corporate AI “Use Case Desert” — and the New Agent Trying to Fix Enterprise AI Adoption
By the time the enterprise AI boom reached full pitch last year, corporate leaders had convinced themselves they were charging into an intelligent future. Many now have the licences, the copilots, even the internal taskforces. What they don’t have — in most cases — is ROI from AI.
The gap between expectation and outcomes is so wide that Section, an AI transformation company serving more than 150 enterprise organisations, has given it a name: the use case desert. Companies may be flush with large language models and ambition, but most employees still have no idea how to turn AI into meaningful productivity gains.
This week, Section launched a tool it believes could shift that dynamic. ProfAI’s Use Case Coach, a personalised AI agent designed to help employees identify and implement high-value AI use cases, aims to turn vague interest into business impact. Behind the launch is a revealing diagnosis of why enterprise AI adoption remains slow — and how organisations might finally move beyond surface-level experimentation.
To understand the problem and the promise, MoveTheNeedle.news interviewed Taylor Malmsheimer, Section’s Head of Product. Her written answers offer a candid view into what’s holding enterprises back, and why employees continue to struggle with AI workflow redesign.
The corporate AI boom built on… vacation planning?
Ask Malmsheimer for an example of the use case desert, and she reaches for a story that’s equal parts amusing and alarming.
“We recently heard a CEO brag about being all-in on AI — then say he mostly uses it for vacation planning,” she says. “That exemplifies the issue we’re talking about.”
Enterprises love to proclaim they’re “AI-ready.” Many run workshops, appoint AI champions, and push staff toward generative AI tools. But according to Section’s research, fewer than 10% of AI users are working on anything that produces measurable business return.
Most everyday use cases? Meeting summaries. Email drafts. Light rewrites. Tasks that save minutes, not hours — and rarely improve organisational KPIs.
Why? Employees are left to figure out AI use case discovery entirely on their own.
“AI use cases are highly specific to the individual, and the Head of AI doesn’t have time to sit down with thousands of employees one-on-one and coach them through use case discovery,” Malmsheimer explains. Traditional corporate learning approaches fall flat: “Workshops and lunch and learns don’t work for this purpose — they’re too one-size-fits-all.”
The result is predictable. “Employees are left to come up with their own use cases,” she says, “and in the vast majority of cases they’re failing to do so.”
Can an AI coach succeed where copilots don’t?
The Use Case Coach attempts to solve this structural problem — not by offering yet another chatbot, but by acting as a personalised AI productivity consultant.
“The Use Case Coach learns about each user’s role, company, AI proficiency, and priorities, and recommends use cases that fit their specific profile,” Malmsheimer explains.
The tool then provides guided implementation:
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clearly defined outcomes
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personalised workflow design
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guidance on reducing bias and hallucinations
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an action plan and ready-to-use prompt
Users can circulate their use cases internally, helping teams avoid duplicated effort and build institutional AI knowledge — a capability many enterprises still lack.
For leaders, the real value is visibility into how AI is being used, not just how often.
“The Head of AI then gets metrics on the percentage of employees with a use case, most popular use cases, and more,” she says. This goes beyond today’s LLM dashboards, which typically measure engagement, not impact.
Malmsheimer is direct about what differentiates their new tool from existing copilots.
“It’s highly personalized, gives step-by-step implementation guidance, and works across LLMs,” she says. “The employee doesn’t have to be incredibly self-motivated to do AI discovery.”
In other words: it lowers the barrier to meaningful AI workflow adoption, something most generative AI tools still struggle to achieve.
What counts as “high-value work” in enterprise AI?
Defining ROI remains one of the great unresolved debates in enterprise AI transformation. Section has chosen a simple benchmark:
“We define high-value use cases as those that save the employee meaningful time (4+ hours / week) or drive business metrics such as revenue growth and margins.”
It’s a pragmatic approach — anchoring AI experimentation directly to business outcomes.
“ProfAI’s recommended use cases are designed to ladder up to the KPIs that drive business returns,” Malmsheimer says.
For organisations frustrated by experimentation without impact, that framing matters.
Early adopters reveal a deeper AI adoption problem
Several enterprise clients have already piloted the Use Case Coach. The feedback shows that the biggest breakthrough isn’t at the employee level — it’s with leadership visibility.
“The biggest ‘unlock’ for the Head of AI is being able to understand what people are using AI for — not just that they’re using it,” Malmsheimer says.
Many organisations simply lack this insight.
“Most LLM dashboards are quite limited in what they report,” she notes. “The Head of AI needs insight into whether AI use is driving ROI or just saving people a few minutes here and there.”
In effect, the use case desert isn’t just a skills gap — it’s an analytics gap.
Who benefits most from a Use Case Coach?
While the tool adapts to thousands of employee personas, Malmsheimer is clear about who gains the most: not the early adopters, but the hesitant mainstream.
“We think the person who stands to benefit the most is the average-to-lagging employee who knows they should use AI, but hasn’t been able to figure out what to do with it,” she says.
This is the silent majority in every organisation.
“So many of us are still retraining our brains to default to AI — making it an innate habit like going to Google.”
Early adopters explore AI instinctively. Everyone else needs structure — and the Use Case Coach provides it.
“That’s most of the employees at every enterprise organization,” Malmsheimer says.
A tool designed for enterprise AI transformation
Section describes itself as an AI transformation company, and the Use Case Coach fits squarely into that mission.
“Our mission at Section is to help 1 million people thrive in the age of AI,” Malmsheimer says. That requires guiding employees through a staged journey: from scepticism, to weekly time savings, to fully AI-powered workflows.
Section already offers AI maturity diagnostic tools, strategy development, workforce upskilling and change management. The Use Case Coach fills the remaining gap: personalised workflow-level adoption.
The roadmap: building an operating system for enterprise AI
If the Use Case Coach is a first step, Section’s ambitions go much further.
“ProfAI will be the head of AI’s one-stop AI enablement platform — the place they go to track organizational AI proficiency, prioritize interventions, redesign workflows, and much more,” Malmsheimer says.
The next wave of enterprise AI will put unprecedented pressure on AI leadership, she argues.
“The Head of AI is facing enormous pressure over the next 5 years. They need a platform designed to drive organizational AI adoption.”
The Use Case Coach is just the beginning, she adds: “There’s much more ahead.”
The real bottleneck in enterprise AI isn’t the model — it’s the map
Enterprises have spent 18 months assuming that once powerful models existed, employees would naturally figure out high-value use cases. They haven’t. Not because they lack skill, but because they lack guidance.
Section’s Use Case Coach argues that successful enterprise AI adoption depends not on intelligence, but on structure — on clear maps, shared patterns and guided discovery.
If Section is right, the companies that escape the use case desert won’t be the ones with the most advanced models, but the ones with the clearest path to using them.