Atheni AI is betting that the future of enterprise AI depends less on better models and more on helping people use them effectively.
Louise Ballard has a simple mission for the AI era: ensure that no one gets left behind.
“As AI becomes embedded across every profession, we don’t want to create a two-tier society where only those who can afford expensive tools or specialist training are able to benefit,” she says. “Everyone should have access to the knowledge and confidence they need to use AI well.”
That philosophy has shaped Atheni AI, the UK startup Ballard co-founded with Mackenzie Howe. Rather than building another AI model, Atheni focuses on a different challenge: helping organizations ensure employees actually use AI tools effectively.
It’s an increasingly important distinction. While businesses continue investing heavily in platforms such as ChatGPT, Claude, and Microsoft Copilot, many struggle to move beyond isolated experimentation.
The Real AI Problem Isn’t Access
“Anyone can open ChatGPT and ask it a question,” Ballard says. “The real question is whether they know if the answer is good. Can they provide the right context? Can they challenge the output? Can they connect different tools together?”
Those questions emerged repeatedly as Ballard spoke with former clients. Organizations had purchased AI licenses, rolled them out company-wide, and expected productivity gains to follow. Instead, adoption remained uneven.
Some employees barely used the tools. Others relied on them inconsistently or ineffectively before reverting to familiar ways of working.
The experience reflects a broader industry trend.
A recent CambrianEdge.ai study of 775 AI users across 104 organizations found that 55% of professionals believe fragmented individual AI usage and the absence of structured human-AI workflows are the biggest barriers to adoption. Separate research from BCG found that although 96% of global CMOs believe AI is transforming business, almost half still use it only for isolated tasks rather than embedding it into day-to-day workflows.
“We quickly realized that real transformation doesn’t happen because you have one or two AI champions,” Ballard says. “You need the whole team developing confidence together.”
Why Traditional AI Training Falls Short
Ballard believes the biggest barriers to adoption aren’t technical.
They’re behavioral.
Employees worry about being replaced. Many are reluctant to change workflows they’ve relied on for years. Others simply don’t see how AI fits into their specific role.
Traditional workshops rarely solve those problems.
“We’d run workshops, everyone would leave enthusiastic, and six weeks later, clients would tell us very little had actually changed,” she says.
“That’s when we realized this wasn’t primarily a training problem—it was a coaching problem.”
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Coaching AI in Context
Atheni approaches AI adoption differently.
Rather than delivering generic courses, the platform coaches employees as they work, analyzing how they use AI, identifying opportunities for improvement, and providing personalized guidance tailored to their role.
Through a browser assistant and analytics dashboard, organizations can track capability across teams while employees progress from basic experimentation to more advanced AI workflows.
For one client, the results were significant. After three months of coaching, around 90% of employees were actively using AI, with roughly one-third reaching Atheni’s highest capability tier.
“What changed wasn’t simply that they were using AI more often,” Ballard says. “They understood what good usage looked like.”
Access Doesn’t Equal Adoption
Ballard argues that many organizations still assume AI transformation begins once licenses are distributed.
“The biggest misconception is thinking that access equals adoption,” she says.
Real transformation requires redesigning work itself.
She points to a corporate finance client that didn’t simply automate an existing spreadsheet process but fundamentally rethought how the work should be done.
“It’s not just efficiency,” she says. “It’s redesigning work.”
Preparing for an Agentic Future
As AI systems evolve, Ballard believes the skills employees need will evolve alongside them.
Today’s emphasis on prompt writing will likely give way to designing AI agents, orchestrating workflows, and managing multiple AI systems.
The need for continuous learning, however, will remain.
“The underlying challenge doesn’t disappear,” she says. “It simply changes.”
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Building Credibility
Atheni raised £350,000 earlier this year, but fundraising proved one of the company’s biggest hurdles.
“As a female founder in my fifties, I realized we weren’t just facing a funding gap—we were facing a credibility gap,” Ballard says.
Finding investors who understood the problem transformed the process, allowing the company to close its funding round within six weeks.
Today, Atheni combines consulting with software development—a model Ballard believes reflects the future of enterprise AI.
“If you’re solving complex human problems, you need deep domain expertise,” she says. “That expertise often comes from working directly with customers before it’s embedded into software.”
Keeping Humans at the Center
As AI becomes embedded across every profession, Ballard believes organizations risk focusing too heavily on the technology itself.
For her, the bigger challenge is ensuring people develop the confidence to use it effectively.
“We have an opportunity to shape what the future of work looks like,” she says. “I’d like that future to be one where humans remain firmly at the center.”
