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Fast Company
08-05-2025
- Business
- Fast Company
The deskless workforce will benefit from digital training
There is a nationwide talent war for frontline, skilled workers, and unfortunately, too many companies are losing. Turnover among deskless workers, who account for about 80% of the workforce globally, is high, and they are notoriously difficult to train through traditional training programs. Corporate training solutions that work for someone sitting behind a desk rarely work for someone on a job site or factory floor. HR professionals cited employee engagement, retention, and recruitment as the top management challenges within the deskless workforce, according to a Society for Human Resource Management study. Unlike office workers with predictable schedules and easy access to digital tools, deskless employees are mobile and harder to reach. As a result, 79% of HR leaders cite learning and development as the biggest talent challenge for deskless teams, followed by retention and onboarding cited by 75%. Training can address each of those issues, but even when available, it's often disconnected from actual business outcomes and lacks measurable value. Why? Because training frontline workers is fundamentally different from training office-based employees. Training and onboarding in-the-field workers is complicated and complex, so many companies are slower to invest in it. Recruit, Ramp, and Retain And yet, the frontline workforce is a business-critical system. Executives love to say, 'People are our most important asset.' However, when asked what systems they use to recruit, ramp, and retain employees, most stumble, which tells you everything. The workforce isn't always treated like the strategic system it is. To connect training to business value, we need to view the entire employee journey—recruit, ramp, retain—as an integrated pipeline. Of those three stages, ramp is the most important. It's the anchor. Companies that invest heavily in ramping programs find it easier to recruit and are more successful at retaining. When you invest in frontline workers early, they stay longer. This is especially true for skilled and industrial workers. Studies show that the majority of employees say training programs positively affect their engagement, and 94% say training encourages them to stay at a company longer. In contrast, lack of career progression is one of the top reasons employees leave. So what does ramp look like for most frontline workers today? Most often it is job shadowing. There's value in that, especially when mentorship is involved, but the challenge is that it doesn't scale. Not every employee is a good trainer. As experienced workers retire, mentorship will become harder to deliver consistently, especially in industries facing labor and skills gaps. Digital Training Allows For Customization The goal, then, is to build a digital training system that can act as a mentor but can scale. Simulations have already been proven in aviation, medicine, and the military. They offer the closest thing to hands-on training and will become even more accessible as spending on technology for deskless workers increases. When digital learning is done well, it mimics great teachers by not just showing people how to do their jobs but also challenging them to understand why it's done that way. It also provides assessments, which is critical in ramping programs. A strong system meets new workers where they are, quickly understanding their current capabilities and tailoring training accordingly. Digital training also supports personalized learning plans, delivering key lessons in short, targeted bursts that can teach what's needed to improve job performance and support career advancement. Too often, training is treated as a one-size-fits-all solution without alignment to the business strategy. AI will bring even more customization to learning, making it more relevant. But to tie it back to business outcomes, companies must use data to track progress and impact and then align it to company goals. Retain Frontline Talent Companies that see real results are those that define success, design training programs that build the skills to get there, and actively measure how training improves operations. We're already seeing this investment mindset emerge in places like private equity-backed roll-ups of skilled trades companies. These firms are building standardized, scalable training systems across dozens of operating companies to drive profitability. In doing so, they're setting a model that others can follow. Winning the war for frontline talent requires a shift in thinking. Leaders need to ask themselves: Do we treat workforce development like other critical business systems? Can the knowledge gained translate to measurable business outcomes? Do we have a learning and development foundation that is connected to the business? Can our existing training system leverage the power of AI to deliver personalized, engaging training that derives even more value for employees and the company? Those who can answer yes to these questions are creating a system that recruits faster, ramps better, and retains longer, all of which help transform workforce development from a cost center into a competitive advantage.
Forbes
07-05-2025
- Business
- Forbes
Be Prepared, Your New Boss May Be AI
AI generated businessman getty Artificial intelligence (AI) is getting infused in most everything. Now it looks like AI may take over corporate leadership. Some companies have already tested AI as bosses , managers, or ultimately CEOs . While it feels uncomfortable, it makes sense. AI works around the clock, no coffee breaks or vacations. AI offers emotionless data-driven decisions, and lacks human emotions when it comes to cut costs and enacting layoffs. The big question is, can an algorithm lead a team, inspire employees, or navigate the complexities of the human workplace? As AI becomes more sophisticated, companies are exploring its potential as a leader. A handful of businesses have already taken the bold step of appointing AI as a CEO or manager. These experiments raise fundamental questions about the future of leadership , the limits of automation, and the evolving partnership between humans and machines. Recent McKinsey surveys show that organizations are increasingly using AI for routine managerial tasks, with adoption rates accelerating in 2024 and 2025, especially for functions like scheduling, analytics, and workflow approvals. Additionally, AI's impartiality appeals to firms aiming to reduce human biases in decisions like hiring or resource allocation, as noted in a 2023 Wall Street Journal report on AI in management. The Society for Human Resource Management and other HR experts emphasize that emotional intelligence (EI) is crucial for effective people management and leadership. Leadership requires navigating ambiguity, fostering trust, and inspiring creativity, areas where AI, even advanced generative models, falls short. In September 2022, Dictador, a Polish rum and spirits company, made headlines by appointing MIKA, an AI-powered humanoid robot, as its CEO. MIKA, developed in collaboration with Hanson Robotics, was tasked with making data-driven decisions, such as selecting bottle designs, approving marketing campaigns, and leading strategic projects. The results of MIKA's tenure are mixed. Dictador's leadership praised MIKA for streamlining decision-making in areas like product design and supply chain management. However, MIKA's role appears largely symbolic, with human executives retaining control over major strategic and financial decisions. Critics argue that MIKA functions more as a high-tech assistant than a true CEO. The nuances of leadership, such as motivating employees or navigating corporate politics, remain beyond AI's capabilities, for the time being. NetDragon Websoft, Ms. Tang Yu, the AI Executive In August 2022, NetDragon Websoft, a Chinese gaming and tech company, appointed an AI-based virtual humanoid named Ms. Tang Yu as a 'rotating CEO' of its subsidiary, Fujian NetDragon Websoft. Ms. Tang Yu was designed to oversee operations, provide real-time data analysis, and support human managers in decision-making. NetDragon reported positive outcomes from Ms. Tang Yu's involvement. A company statement claimed that the AI improved operational efficiency by 10% and reduced decision-making errors in supply chain management. The system's ability to process thousands of data points simultaneously allowed it to identify cost-saving opportunities that human managers might have overlooked. However, employee feedback, as reported in a 2023 TechCrunch article, suggested challenges. Some workers felt disconnected from an AI 'boss' that lacked empathy or the ability to understand workplace dynamics, leading to morale issues in teams requiring creative collaboration. DeepKnowledge: AI as a Managerial Tool DeepKnowledge, a UK-based knowledge-sharing platform, appointed an AI system named Vital to manage certain operational teams in 2022. Vital was not a CEO but acted as a manager, assigning tasks, monitoring project progress, and evaluating employee performance based on predefined metrics. The AI was integrated into the company's workflow to optimize productivity in remote teams, particularly for data analysis and content creation roles. Employees appreciated the clarity of AI-driven instructions, which reduced ambiguity in project goals. However, some workers felt micromanaged by Vital's constant monitoring. Others reported a lack of motivational support. Outcomes and Lessons Learned While a handful of companies have experimented with AI as CEO or manager, these roles remain largely symbolic and experimental. AI has demonstrated clear value in improving operational efficiency and supporting decision-making, but human qualities-such as empathy, and ethical judgment-remain irreplaceable at the highest levels of leadership. The future of management could be a collaborative effort with AI serving as a powerful partner to human leaders. The track record of AI in leadership roles reveals a pattern. AI excels in data-driven, repetitive, or analytical tasks but struggles with the human elements of management. Dictador's MIKA boosted brand buzz but didn't fully replace human executives. NetDragon's Ms. Tang Yu improved efficiency but alienated some workers. DeepKnowledge's Vital enhanced productivity but wasn't able to maintain team morale. A 2023 NPR study on AI in customer service found similar dynamics. AI boosted productivity by 14% but was most effective when augmenting, not replacing, human workers . These cases highlight a key lesson. AI is best suited as a tool to support, not supplant, human leadership. The human touch, empathy, vision, and adaptability, remains irreplaceable in roles requiring inspiration or complex decision-making. A 2024 Aon survey of HR professionals noted that 85% of employers using AI for HR tasks saw it as a time-saver, but only when paired with human oversight to address ethical and emotional gaps. A 2025 TechRepublic article predicted that by 2030, 25% of companies could use AI for middle-management tasks, but only under human supervision . The stories of AI as boss, CEO, or manager reflect both ambition and caution. While AI can optimize operations and reduce costs, its limitations in emotional intelligence and strategic vision mean it's not ready to take the corner office alone. For now, the most successful companies are those that blend AI's precision with human insight, creating a partnership that leverages the strengths of both.
