Aspen is a place for leaders to lift their sights above the possessions which possess them. To confront their own nature as human beings, to regain control over their own humanity by becoming more self-aware, more self-correcting, and hence more self-fulfilling.
Employee ownership, such as employee stock ownership plans and worker-owned cooperatives, has emerged as a catalyst for fostering successful businesses, advancing racial and gender equity, and tackling the persistent issues of poor job quality and wealth inequity.
Employee-owned firms often create a host of benefits compared to similar, non-employee-owned companies, including improved compensation, enhanced working conditions, reduced turnover, and greater resilience during challenging economic times. However, despite its potential, employee ownership remains a relatively small component of the US economy, and awareness about employee ownership is relatively low. A unique opportunity for expansion is at hand, as six out of 10 business owners across the US intend to sell their business in the next decade as they prepare for retirement.
State centers of employee ownership are emerging to help address these challenges and capitalize on this opportunity for expansion. These centers work to promote employee ownership and educate business owners and workers about the different options available. In this brief, we discuss the strategies and practices implemented by Colorado’s Employee Ownership Office to better understand how employee ownership can be supported and grown. We hope this profile will help inform other state centers’ practices and the government’s role in supporting state centers, particularly as more centers emerge through funding provided by the recently passed Worker Ownership, Readiness, and Knowledge (WORK) Act.
The Aspen Institute Economic Opportunities Program advances strategies, policies, and ideas to help low- and moderate-income people thrive in a changing economy.
Join Our Mailing List
To receive occasional emails about our work — including new publications, commentary, events, fellowships, and more — join our mailing list.
To create a future-ready workforce system, we must move beyond outdated credentials and analog processes to one that is skills-first, transparent, data-driven, and aligned with the evolving needs of workers, educators, and employers.
This publication examines how fragmented skills, credentialing, and workforce data systems limit the potential of skills-based hiring and advancement, and outlines a shared vision for building the interoperable infrastructure needed to create a connected skills ecosystem that benefits workers, employers, educators, and governments.
In this interview, Chelsea Miller of Upskill America speaks with Nick Greif of InStride about how employers can design education benefits that are more accessible, strategic, and aligned with workforce goals.
The future of America’s economic strength depends on immigration. As the US birth rate declines and the median age goes up, fewer US-born workers will enter the labor force.
This is the final event in our Job Quality in Practice series. In this conversation, hosted by the Aspen Institute Economic Opportunities Program on May 7, 2026, we hear from the Institute’s Job Quality Fellows who are embedding job quality into their work across a range of contexts and strategies — from employee ownership models that give workers a direct financial stake in their company’s success, to apprenticeship programs that create structured pathways to higher-wage careers, to worker advisory committees that bring employee voice into business decision-making.
This brief shares key lessons and takeaways that could be used to implement internal job quality practices to strengthen CDFIs and other small business support organizations.
Putting people at the center of the systems we are building means accepting that career paths are rarely linear. It requires us to build infrastructure that accommodates life transitions, recognizes informal learning, and values a worker’s agency over their own data.
