A calm breath before a big shift: Our Interview with American Staffing Association CEO Stephen Dwyer
Stephen Dwyer was waiting in a hospital for a double lung transplant when he made a quiet promise to himself. If he received another chance at life, he would lead by investing in people. Today, as president and CEO of the American Staffing Association (ASA), he keeps that promise. He tells people, I invest in the success of others. In a world racing to adopt AI and robots, his story reminds us that work is still about people, purpose, and smart choices.
A leader’s pivot from legal to why
Stephen did not simply move from chief legal officer to CEO. He reframed the entire role. He asked three core questions: Why do we exist? How do we work? What do we do? He used Simon Sinek’s Golden Circle to help his team and board align around purpose. He also created a simple test for any new tool: will it help people do meaningful work? In Stephen’s view, leadership is about investing in the success of others. That compass now shapes ASA’s approach to AI and automation across a broad and complex industry.
What the data says about AI right now
Across sectors, AI adoption is rising rapidly. In early 2024, 72 percent of organizations reported using AI in at least one function, up from 56 percent in 2021. Generative AI use rose to 65 percent of organizations, with strong adoption in professional services such as HR and training, which directly touch the world of staffing.
At the same time, the staffing industry has been shifting. In the fourth quarter of 2024, U.S. staffing firms employed about 2.2 million temporary and contract workers per week, while generating 124 billion dollars in annual sales. These figures illustrate a large, essential market adapting to economic cycles and new technology.
Beyond tasks: remove friction first
Stephen encourages leaders to begin AI work with two grounded questions:
What friction slows you down each day?
What friction do our clients feel when they work with us?
This approach is practical. When teams map real workflows before automating, they avoid accelerating broken steps. Removing friction frees people to focus on higher value work, which boosts morale and outcomes. It also prevents leaders from automating silos or bottlenecks that already frustrate staff and customers.
Staffing’s new tools: AI and robots, used thoughtfully
Stephen describes agencies using AI to screen resumes, conduct early stage interviews, and better understand client needs. He also points to the rise of robotics in light industrial and logistics settings, including models where agencies lease robots to clients. The broader robots as a service market continues to grow, driven by demand for flexible automation and lower upfront investment. Analysts note rapid adoption of autonomous mobile robots and AI enabled fleet management as firms seek to increase throughput without major capital spending.
Information is not enough. Insight wins.
One of Stephen’s most important shifts is how ASA defines value. The organization once aimed to be the epicenter of information. With AI making information easy to access, he refocused ASA on something harder to replicate: knowledge, expertise, and insight. This parallels what top AI adopters consistently report. Tools reduce costs, but real advantage shows up when teams use AI to improve decisions and create new value, not simply to speed through tasks.
The labor signal: disruption and discipline
Leaders are feeling competing pressures. Employers expect churn as roles evolve with new technology. Companies estimate that machines now perform roughly one third of tasks and may handle more data work by 2027. Yet progress is uneven, and many firms are still determining what to automate and when. The World Economic Forum reports that employers anticipate significant shifts in job roles over the next five years, with some positions declining and others expanding. This requires reskilling, smarter staffing, and clear communication.
Headlines versus on the ground choices
Recent layoff announcements create a perception that cost cutting and AI always move together. In October 2025, U.S. employers announced 153,074 job cuts, the highest October total in more than twenty years, citing cost controls first and AI second. However, headlines do not automatically reflect what will happen inside a single firm. Many organizations are still early in scaling AI. Leaders should read these signals as a nudge to plan. Clarify where AI helps, where human judgment shines, and how to transition talent toward higher value work.
A simple playbook you can use this quarter
Map friction before you automate. Interview teams about daily blockers and client pain points, then select two or three fixes that create visible wins. This mirrors Stephen’s two questions and builds early momentum.
Keep humans in the loop. Use AI for screening and first round assessments, then center recruiters and account managers on judgment calls, candidate experience, and client insight.
Pilot where impact is visible. Start with repeatable, document heavy tasks such as resume screening, interview scheduling, and job description drafting. Measure time saved and reinvest it into relationship work.
Shift from data dumps to decisions. Do not simply provide information. Build dashboards and briefings that offer next step recommendations. ASA’s shift from information to insight is a strong model.
Tie robotics to real constraints. If clients cannot afford automation outright, explore service models or short term leases so they can increase throughput without major purchases. Track safety, uptime, and workforce roles as operations expand.
A final thought worth sitting with
On one of the most difficult days of his life, Stephen found calm because he loved his work and knew where he added value. That level of clarity, the why, matters even more as AI spreads. Tools will evolve. Headlines will rise and fall. But leaders who remove friction, elevate people, and trade raw information for real insight will continue to breathe easier and will keep building organizations worth working in.
