Structured AI interviews and human judgment combine to address the global talent shortage
Updated
March 4, 2026 4:46 PM
ManpowerGroup World Headquarters in Milwaukee. PHOTO: ADOBE STOCK
As hiring pressures mount across global markets, ManpowerGroup is turning to technology to strengthen how it connects people to work. The workforce solutions major has announced a global partnership with Hubert, a startup focused on AI-driven structured interviews. The aim is simple: make hiring faster and fairer, without removing the human touch.
ManpowerGroup has spent decades operating at the center of the global labor market. The company works with employers across industries to fill roles, manage workforce planning and build talent pipelines. With millions of placements each year, it has a clear view of how strained hiring has become. A large share of employers today report difficulty finding skilled talent. At the same time, candidates expect more transparency, quicker feedback and flexibility in how they engage with employers.
Hubert enters this picture as a specialist in structured digital interviewing. The startup has built tools that allow candidates to complete interviews online, at any time, while being assessed against consistent criteria. Instead of relying on informal screening calls or resume filters, its system focuses on standardized questions tied directly to job requirements. The idea is to bring more consistency to early-stage hiring.
The partnership brings these capabilities into ManpowerGroup’s global operations. AI-powered interviews will now support the first stage of screening, helping recruiters identify qualified candidates earlier in the process. This does not replace recruiters. Final decisions and contextual judgment remain with experienced hiring professionals. What changes is the speed and structure of the initial assessment.
For employers, this could mean earlier visibility into job-ready talent and less time spent on manual screening. For candidates, it offers more flexibility. A significant portion of interviews on Hubert’s platform are completed outside regular office hours, allowing applicants to engage when it suits them. That flexibility can make a difference in competitive labor markets where timing matters.
The collaboration is also positioned as a step toward reducing bias. By evaluating each candidate against the same transparent standards, the process becomes more consistent. While no system can remove bias entirely, structured assessments can reduce the variability that often comes with unstructured interviews.
At its core, the partnership addresses a gap many large organizations are facing. They need scale and speed, but they cannot afford to lose the human judgment that good hiring depends on. Manual processes are too slow. Fully automated systems can feel impersonal and risky. ManpowerGroup’s approach suggests a middle path, where technology handles repetition and structure and recruiters focus on potential and fit.
The move also reflects a broader shift in the workforce industry. AI is no longer being tested on the sidelines. It is being built into the foundation of hiring operations. For established players like ManpowerGroup, the challenge is not whether to adopt AI, but how to do so responsibly and at scale.
By working with Hubert, the company is signaling that the future of recruitment will likely blend structured digital tools with human expertise. In a market defined by talent shortages and rising expectations, that balance may prove critical.
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A look at how motivation, not metrics, is becoming the real frontier in fitness tech
Updated
February 7, 2026 2:18 PM
A group of people running together. PHOTO: FREEPIK
Most running apps focus on measurement. Distance, pace, heart rate, badges. They record activity well, but struggle to help users maintain consistency over time. As a result, many people track diligently at first, then gradually disengage.
That drop-off has pushed developers to rethink what fitness technology is actually for. Instead of just documenting activity, some platforms are now trying to influence behaviour itself. Paceful, an AI-powered running platform developed by SportsTech startup xCREW, is part of that shift — not by adding more metrics, but by focusing on how people stay consistent. The platform is built on a simple behavioural insight: most people don’t stop exercising because they don’t care about health. They stop because routines are fragile. Miss a few days and the habit collapses. Technology that focuses only on performance metrics doesn’t solve that. Systems that reinforce consistency, belonging and feedback loops might.
Instead of treating running as a solo, data-driven task, Paceful is built around two ideas: behavioural incentives and social alignment. The system turns real-world running activity into tangible rewards and it uses AI to connect runners to people, clubs and challenges that fit how and where they actually run.
At the technical level, Paceful connects with existing fitness ecosystems. Users can import workout data from platforms like Apple Health and Strava rather than starting from scratch. Once inside the system, AI models analyse pace, frequency, location and participation patterns. That data is used to recommend running partners, clubs and group challenges that match each runner’s habits and context.
What makes this approach different is not the tracking itself, but what the platform does with the data it collects. Running distance and consistency become inputs for a reward system that offers physical-world incentives, such as gear, race entries or gift cards. The idea is to link effort to something concrete, rather than abstract. The company also built the system around community logic rather than individual competition. Even solo runners are placed into challenge formats designed to simulate the motivation of a group. In practice, that means users feel part of a shared structure even when running alone.
During a six-month beta phase in the US, xCREW tested Paceful with more than 4,000 running clubs and around 50,000 runners. According to the company, users increased their running frequency significantly and weekly retention remained unusually high for a fitness platform. One beta tester summed it up this way: “Strava just logs records, but Paceful rewards you for every run, which is a completely different motivation”.
The company has raised seed funding and plans to expand the platform beyond running, walking, trekking, cycling and swimming. Instead of asking how accurately technology can measure the body, platforms like Paceful are asking a different question: how technology might influence everyday behaviour. Not by adding more data, but by shaping the conditions around effort, feedback and social connection.
As AI becomes more common in consumer products, its real impact may depend less on how advanced the models are and more on what they are applied to. In this case, the focus isn’t speed or performance — it’s consistency. And whether systems like this can meaningfully support it over time.