Two Executives for Human and AI Workers Is Already Obsolete

01 /The Concept

r.Potential describes its mission as "unlocking the full potential of human-AI collaboration." To do that, the startup is building what it calls the world's first corporate platform for optimizing workforce configurations that blend human employees and AI agents.

The urgency behind the concept: today's generation of managers is the last that will supervise only human teams. Going forward, they'll manage people and digital workers simultaneously.

Making that transition isn't straightforward. Companies face questions like: "What if we tried to automate everything?" "What if this is just hype and we should wait and see?" "What if competitors get there before us?"

r.Potential's platform will help executives model different AI adoption scenarios, forecast the risks and expected outcomes of each, and choose the most appropriate path – then plan a phased rollout.

The company's website offers little concrete product description beyond the core conceptual framework it's building around: "Units of Potential." The basic idea is that every job gets broken down into discrete units, each carrying a different performance potential depending on whether it's done by a human or an AI agent. The platform then builds recommendations, scenario projections, and risk assessments from those differential potentials and their associated costs.

r.Potential was founded only this past spring and currently has nothing to show beyond a newsletter signup. That hasn't stopped it from closing a first funding round of $5.5 million.

02 /Why It Matters

The most notable thing about r.Potential isn't its product – it's its origin. This is a corporate startup, created by Adecco Group, a publicly traded HR services company valued at $4.5 billion. The $5.5 million came from Adecco itself and from Salesforce, which signed on as the project's first commercial partner.

Adecco is one of the world's leading workforce management players, with more than 100,000 corporate clients. Until now, Adecco helped companies manage human workforces. Now it's applying that institutional expertise to help clients manage a combination of human and digital employees.

The insight behind this, as r.Potential's CEO frames it, is that AI adoption inside a company isn't a purely IT problem – it's not just the CTO deciding which agents to deploy where. And it's not purely an operations problem – it's not just the COO rolling out robots in the warehouse. It's a more complex challenge: finding the right balance between what human employees do and what AI does.

That balance isn't universal. It's fundamentally context-dependent. A company in France and a company in San Francisco may approach AI adoption very differently based on local labor law and regulatory requirements. A mass-market consumer goods company might comfortably hand off all customer service to AI agents; a luxury goods company almost certainly can't.

In other words, "if an AI agent can do it, an AI agent should do it" is a dangerous dogma born in Silicon Valley. It's not a strategy that every company in every context should follow. Chasing scale and cost reduction at all costs can hollow out a company's culture and lose the human talent that drives genuine development.

"AI agents first, always" is ideology, not strategy. Ideology eventually becomes dogma, and dogma blocks growth. Strategy, by definition, should enable it.

That's r.Potential's stated purpose: helping companies build an actual AI integration strategy. Let AI do what it does better than people – but calibrated to the company's specific context. Let people do what only they can do in that same context.

And the unit of analysis shouldn't be job titles or whole roles – that's too blunt. The right level is the "unit of potential" inside each role: individual tasks that can be intelligently distributed between humans and AI.

Workhelix ([related review](/review/jeto-ne-gemorroj-a-vozmozhnost-eshhjo-bolshe-zarabotat)) is taking a similar approach. Launched last spring and already through two $15 million funding rounds, Workhelix analyzed more than 200,000 individual job tasks across professions, assigning each one an automation feasibility score along with associated risks and relevant AI tooling. Armed with that knowledge base, it goes into companies and shows leadership exactly which tasks can be automated, what the efficiency gain looks like, and then helps build and monitor rollout plans.

A rough version of that same calculator also lives inside JobForAgent's AI agent marketplace ([related review](/review/milliard-dollarov-budet-stoit-ne-jeto-a-vot-jeto)) – where employees can input a job description and get an estimate of what percentage of their work AI agents could handle.

03 /Opportunities

The CEO of r.Potential made the point clearly: AI adoption isn't a technology implementation. It's about finding the right balance between what humans do and what AI does.

And that balance is impossible to strike when the head of HR and the CTO are in a constant tug-of-war for influence.

Biotech giant Moderna offered a striking example of how to resolve this last month: it merged its HR and technology functions into a single department responsible for both human resources and digital technology. One person now governs how work is distributed between AI and people. Their primary KPI is overall organizational performance – it doesn't matter whether that performance is delivered by natural or artificial intelligence.

This looks like the first sign of a new trend that other organizations will follow. But new types of leaders require new platforms to support them. Platforms that can measure productivity, calculate resource costs, recommend task allocation between humans and AI, build plans, track execution, and handle the many other management functions that running a hybrid human-AI workforce demands.

This is an enormous market – too large for any single platform to serve alone, no matter how ambitious. Which makes this a genuinely rich area for new entrants: building platforms purpose-built for simultaneous human and AI workforce management.

Vertical specialization may be the smartest entry point – platforms designed for specific industries or functions will likely be more precise, simpler to deploy, and more valued within their target domain. Which sectors might need these platforms first?