Only 13% of Professionals Are Confident Using AI as Companies Struggle With Training Gap

Just 13% of professionals are confident using AI - how top companies are solving this skills gap - ZDNET

* High-quality AI training is often lacking. * Employers should help workers develop broad capabilities. * Job-specific training and constant updates are key. AI tools might be common in businesses, but high-quality training is not. Research from technology training and talent provider QA found that 32% of employees have received no formal training, and only 15% receive ongoing or advanced support. This lack of learning and development has a big impact. Only 9% of employees consider themselves advanced or expert users, and just 13% of professionals are confident in using AI for basic tasks. Also: 91% of professionals say their firm still falls short on AI - how to fix that Jo Bishenden, chief learning officer at QA, told ZDNET that her firm's research highlights a big gap between implementation and education. "AI is already reshaping how work gets done," she said. "Yet while organizations continue to invest heavily in AI tools and platforms, most businesses are making the same mistake: they're spending on AI tools and neglecting the people expected to use them." Other research points to a similar issue. The Harvey Nash Tech Talent Salary Report found that while three-quarters of IT staff have access to AI tools, one in five technologists are expected to self-learn, and 23% are waiting for formal training. Also: Why replacing staff with AI backfires - and 5 ways smart leaders generate real value instead So what exactly should employers be doing? Bishenden said the best AI training programs get three things right: they ensure AI literacy is for everyone and provide a shared baseline understanding of AI; they provide role-specific learning and development opportunities; and they support behavioral change that allows people to exploit emerging technologies. Here's what those three areas look like in practice and what those approaches might mean for your professional development. Broad AI literacy Bishenden said it's important to recognize AI isn't a plug-and-play service. Emerging technology only works when people know how to use it well, and that reality means employers should develop cross-organization literacy. "Employees must know how to ask the right questions, interpret outputs critically, apply judgment, and redesign everyday workflows around new capabilities," she said. Also: 'Specialists aren't required' anymore: How to stay valuable in an AI agent workplace today To develop higher levels of literacy, Bishenden said companies should provide a shared baseline understanding of what AI can and cannot do, where risks sit, and what responsible use looks like: "This approach builds confidence, reduces fear, and creates a common language across the business." Ankur Anand, global CIO at recruiter Harvey Nash, agreed that broad-based AI learning and development is about developing core capabilities. "It's about the security and ethics that must be built in from day one," he told ZDNET. "People need to understand what responsibility they need to shoulder for the effective use of AI." To develop this awareness, the best organizations take best-practice approaches that have worked with a small group of employees and spread them across the wider organization. Also: Companies embracing AI the most are hiring more people - including entry-level That's an approach Emmanuel Frenehard, chief digital officer at biopharmaceutical giant Sanofi, has pioneered within his firm. Sanofi's executives completed Drive Digital, a program designed with the ESSEC business school in Paris that focused on key areas, such as use cases and value generation. More than 100 managers passed through the program before it was extended to more than 1,500 other professionals across the organization. Frenehard told ZDNET that Sanofi continues to look for fresh ways to develop everyone's AI literacy. "We do a lot of workshops. Once a month, we have these AI hacks where somebody will come and teach a lesson on great prompting," he said. "I learned something from the latest AI hack, where someone had a different approach. So, we're training people in a way that's like gaming. We make it playful." Role‑specific education Bishenden said a common mistake she sees in companies is that managers focus on exploiting tools rather than delivering outcomes. "If people don't know how to use AI well, the technology won't matter," she said. "Teaching people about AI is not the same as enabling them to solve real business problems with it." Also: AI is getting better at your job, but you have time to adjust, according to MIT When training isn't clearly connected with day‑to‑day work activities, said Bishenden, it quickly becomes disconnected and forgotten. "Training must move quickly into practical use, showing how AI supports real tasks in real roles, from analysis and decision‑making to communication and leadership." Harvey Nash's Anand also recognized the importance of role-specific AI training. "You can't just have arbitrary, standard training for, say, Copilot," he said. "If it's a finance, HR, or marketing professional, the training has to be specific to how these employees use AI." Also: The new enterprise AI expert every company needs - and why Companies also need to recognize that some people will need more help to make the most of AI in their roles than others. Freshworks CTO Murali Swaminathan told ZDNET that a professional in a line-of-business area, such as finance, might not have the awareness of a software engineer who's been using agents for months. "That means you must bring them up to speed on how to use AI, the best practices, what to do, what not to do, and then give them the right tools to make them successful in their jobs," he said. "We have been talking internally about how to bring everybody on board. So, everybody has access to Claude and other technologies, but they need to do it the right way. That's where we're trying to guide them." Also: How Workday and other software providers plan to survive AI His Freshworks colleague, CIO Ashwin Ballal, told ZDNET that these role-specific training programs should be bolstered by certifications that prove on-the-job credentials. "With AI, it's often like we're trying to give people a Formula One car, and say, 'Drive,' But F1 drivers must get used to the track and get certified," he said. "That's the level of certification we need for AI. We need multiple layers -- a consumer level, a pro level, and then an advanced level." Continuous learning Bishenden said companies should also recognize that effective AI training is a constant work in progress. "Learning must be continuous, she said. "AI evolves rapidly, and capability needs to keep pace." New models emerge almost every week. Training programs that look good today could be outdated tomorrow. Also: AI agents are your new colleagues - how to get the best results "AI training is often treated as a one‑off awareness session, a compliance requirement, or something reserved for technical specialists. However, AI capability is not an IT project; it's an organizational mindset shift," said Bishenden. "Emerging technology changes how work gets done, how decisions are made, and how accountability works. Learning programs must encourage experimentation, critical thinking, and ethical judgement if AI is to scale successfully." Stephen Wood, chief operating officer at Rathbones Asset Management, said his organization aims to educate its staff about AI as regularly as possible. "We want to develop their skills. We create structures, like digital champions, but with an AI focus. We want to be in a scenario where AI is on people's minds 24/7, so they fully embrace it," he told ZDNET. "We're in a very fortunate position that everyone in our business is engaged in AI. They're excited; they want to learn. I've got people knocking on the door, saying they want more training." Also: The 3 types of people who will excel in the AI agent era, according to tech leaders Louise Newbury-Smith, head of UK&I at technology specialist Zoom, said her organization also focuses on helping people develop their skills on an ongoing basis. Her organization has AI enablement teams at the local and global levels that showcase individual successes and spread best practices. "Having people who understand enablement, rather than pushing training, is one of the keys to success, and that means really bringing AI to life and making it real," she told ZDNET. "Our approach is about repeating those best practices and sharing knowledge, and if you create that kind of environment, then you can't go far wrong."

ADP CEO: the real conversation on jobs and AI is how do we prepare for what comes next? | Fortune

In every room, at every table, I hear predictions about what AI means for the workforce and the future of work. The talk is mostly about jobs: which roles are changing, which ones are growing, and which ones may be replaced over time. But what if we're missing the crux of the conversation? AI isn't just changing jobs; it's changing the nature of work itself. It is shifting how people will conceptualize work for - quite possibly - the rest of human history. This is a defining moment, and we must respond with urgency. Business leaders need complete clarity on how AI is affecting employees and their work at the most granular levels so they can make critical decisions on hiring, organizational structure, technology investment, and workforce management. Achieving that clarity requires access to the right data and information - and the leaders who understand this are the ones who will come out stronger. What the Data Tells Us Broadly speaking, we don't see AI eliminating jobs at scale. What we do see - what our data shows - is that the world of work is evolving. At ADP, we process payroll for one in six U.S. workers and serve over 1.1 million businesses globally, paying 42 million workers worldwide. From this unique vantage point, we observe the labor market as broadly stable. When we look more deeply, we see that AI is reshaping work at the task level. It is changing the workforce, not shrinking it. And while AI's impact is certainly real, it varies significantly by sector, company size, career stage, and geography. Our work with the Stanford Digital Economy Lab provides a real-time view of AI's impact on occupations through the lens of ADP's payroll data. Recent findings show that early-career workers - ages 22 to 25 - in occupations most vulnerable to AI automation, such as software development and customer service, have experienced employment declines. However, employment of more experienced workers in those same occupations, and for workers of all ages in roles less exposed to AI like home healthcare aides, have remained stable or continued to grow. But this is just scratching the surface. As we dig deeper, we're able to see how AI is actually changing individual tasks within jobs. We call this "the great job unbundling." AI is reshaping work at the task level, creating new job categories and transforming others. Through the adoption of AI, the wage premium of specific tasks is shifting in real time. This has profound implications for how business leaders think about workforce planning, skills development, and the employer-employee relationship. AI is also raising the floor on productivity expectations. Employees are increasingly expected to use AI tools as a baseline - not a differentiator - which changes how performance is measured and managed. We see a critical split in this dynamic: entry-level employment has declined where AI is applied to automate work, but employment has grown in occupations where AI is augmentative - where it supports and enhances human decision-making, freeing employees to focus on higher-value, creative, and more strategic work. Given these nuances, the stakes of getting HCM right have never been higher. Importantly, it is clear this is a moment of change that demands a rigorous, data-driven approach to get it right. The Shifts that Actually Matter The workforce is undergoing three key shifts that have direct implications for how leaders should be managing their workers right now. Investment leads to engagement; 53% of workers say they are fully engaged when they strongly agreed their employer was investing in them - compared to just 12% when they don't feel that same level of investment. Employees also expect their employers to provide the AI upskilling they need to thrive. AI increases the value of human judgment. As more "checklist" work is delegated to AI, workers are transitioning toward longer-term, strategic projects where human judgment matters most. The old model of how to measure productivity - task completion, speed, efficiency - is giving way to something harder to quantify but more profound: judgment, creativity, and long-term impact. AI users report greater productivity and performance. Workers who use AI daily are more than twice as likely to be fully engaged at work - 30% versus 14% of non-users - and half as likely to feel overloaded or stressed: 11% versus 23%. Early AI adopters tend to be top performers. Frequent AI users show higher engagement and motivation, both of which are strong retention drivers. From Understanding to Action Leaders who will come out of this moment stronger are not asking what AI will replace; they are asking how to help their people do more with it. AI is a teammate. It takes on the routine work - and what is left are the judgment calls, the hard decisions, the moments that only a real expert can navigate. That is where people become more valuable, not less - and leaders should see their workforce as more than inputs to be optimized. Our people are sources of reasoning, creativity, institutional knowledge, and logic that technology can't replicate. Businesses can help workers embrace their evolving identities - encourage them to examine which tasks make up their roles and see new possibilities for growth and opportunity. Workers who understand how their role is changing are better positioned to grow with it. The fact is: AI is evolving the workforce in ways that are beautifully and fundamentally human. The organizations that have a clear understanding of what the data tells us - that the workforce is shifting, not shrinking - will be the ones that thrive in the future of work. The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

AI's Biggest Efficiency Risk is Training

AI is moving faster than most organizations -- and people -- can absorb. While leaders are focused on adoption and efficiency gains, many employees are still trying to get their hands around the technology itself and how to apply it to real work. That's where many employers are exposed. In our latest State of Workplace Empathy AI Special Report, nearly half of employees say they've been left to "figure out" AI on their own. That should concern every leader pushing an AI agenda. Because speed without readiness leads to lost opportunity and risk. What some leaders might be overlooking, or just beginning to realize, is the critical role they play in shaping whether AI enables business opportunity or fuels employee anxiety -- simply by offering AI training. A divided AI workforce Our nationwide survey of 1,000 U.S. workers reveals uneven access to AI training, a near 50/50 split between employees whose employers are investing in AI upskilling and those with little to no training. This suggests some companies are rushing to adopt and deploy AI without preparing their people with the skills to enable the very efficiencies they seek. For instance, 45 percent of women reported receiving adequate AI training in our study versus 56 percent of men, an 11-point gap. Gen X employees also stand out, reporting significantly less favorable perceptions of AI than other generations. Culture likewise plays a big role in how employees experience AI. In organizations employees describe as toxic, just 33 percent report adequate AI training, compared with 51 percent overall. More than half of employees in cultures worry that they're falling behind on how to use AI effectively in their roles. Why AI upskilling can't be overlooked Employees who received adequate AI training reported up to 1.5 times more career confidence, agency, and progress than workers who had been left to learn AI on their own. That can mean the difference between AI feeling like a career advantage or a career-ender. And the problem is, the workforce is divided on that front: * Sixty-one percent of employees said AI makes them optimistic about their future at their organization, with eight in 10 among this group saying it has accelerated their careers. * Nearly 40 percent, however, say they're concerned about AI's impact on their future, with 64 percent in this cohort experiencing a mental health issue in the past year -- 14 points higher than the optimistic group. To me, this is a clear signal for leaders that employees need to be brought along on the AI journey. Moving too fast can have far-reaching impacts on the employee experience. While boards, investors, and executives focus on efficiency, many employees are still trying to figure out where they fit into the future being built around them. AI creates no value in isolation One of the best decisions we made at Businessolver this year was elevating the importance of AI leadership in our organization through the appointment of a chief AI officer. For a technology company like ours, AI is foundational to how work gets done and how trust is built at scale. So, when we talk about AI, the conversation is about more than technology -- it's about culture and values. AI creates no value in isolation. Its value comes from how effectively people use it to solve problems. If you believe that, then it becomes clear that employees need to be empowered with the skills to solve bigger, more complex problems with AI. And ultimately, that ingenuity will fuel better business outcomes. We've also expanded access to tools like Microsoft Copilot so employees can incorporate AI into their daily work. But access alone is only a starting line. We're also focused on building AI fluency into the rhythm of work through practical courses, peer learning, and role-based use cases that employees can immediately apply to their work. We also talk about AI often. In fact, it's a regular part of our Monday all-hands meetings. We know adoption doesn't happen through a launch announcement, but rather when people experience first-hand how AI can help them solve real problems in their own work. A defining AI leadership moment As leaders, we're at a pivotal moment where we need to broaden the lens on AI transformation and really take a good pulse on how it's impacting the employee experience. Employer-sponsored AI training sends a powerful signal that the organization is investing in employees' futures. In today's environment, that signal matters more than leaders might realize by shaping how employees feel about their cultures, leaders, and careers -- all of which impact wellbeing, motivation, and productivity. AI readiness is first and foremost a people challenge. Leaders who treat it that way can create competitive advantage by preparing their people to use AI with confidence, judgment, and purpose.

In the AI Era, Workforce Transformation Never Ends. Here Are 5 Ways Leaders Can Stay Ahead

The only way to use AI responsibly is to get a single, living view of who does what today, how work is shifting, and where humans versus machines add the most value. I've seen the way we work turned on its head before. Way back in the 1990s, I witnessed the boom of client-server computing. Later on, we traded answering machines for emails, on-premises software for SaaS, and computers for cell phones. All of these qualified as business transformations, changing how we work and forcing companies everywhere to adapt. But AI is categorically different. It cuts across sectors, departments, roles and skill levels all at once. Right now, every leader is trying to figure out how AI is threatening or helping their business -- their value proposition, how they make money and their cost structure. This is especially true of white-collar businesses built on human capital. AI represents a fundamental shake-up of what people do, what machines do, and how the two collaborate. I work with thousands of companies that are in the thick of navigating this change. And I see CEOs everywhere wrestling with the same question: not whether to transform their workforce, but how to do it responsibly, quickly, and at scale. But this isn't a single shift. We're at the dawn of a new era: one of constant workforce transformation that will require companies to continuously understand how work is changing, redesign the workforce around strategy, and translate insight into action. The good news is that while AI is the catalyst, it can also be a trusted partner in the process. Here are five steps any business can take to keep pace with the workforce transformations accelerated by AI. 1. Understand your people We're already seeing the first wave of AI boomerang hires -- workers who were cut loose, only to be rehired later... when management discovered that bots alone fell short. Few companies today truly understand their existing workforce. They might have a grasp on headcount, but when it comes to real capacity, they're flying blind. Finance sees cost. HR sees roles. Sales sees pipeline. Few leaders can connect workforce size and cost to the roles, skills and teams that actually drive business results. Real transformation starts with addressing these blind spots. That means breaking down silos and bringing workforce data together in a single platform. So when it comes time to make crucial decisions, everyone has a holistic view of current costs, skills, talent, and gaps. 2. Design tomorrow's workforce Once you understand the workforce, the next step is mapping out where it needs to go. Traditionally, this has been the realm of annual planning exercises. But in the AI era, the pace of change has outrun the old planning calendar. Periodic, consultant-led org design projects don't cut it. Instead, leaders need to embrace an always-on planning approach. That means modeling scenarios continuously -- tweaking span of control, management layers, cost trade-offs and acquisition options as new conditions emerge. This kind of planning also has to extend beyond full-time employees. AI rarely eliminates roles neatly, with gains scattered across pieces of work. So it's key to look past job titles and catalog the tasks inside each role: which require judgment, empathy, creativity or relationships, and which can be automated, augmented or eliminated. As headcounts and business conditions shift, new AI-powered tools allow for on-the-fly plan adjustments, keeping forecasts and budgets in sync. They also bridge the gaps between people and finance teams, enabling collaborative planning using real-time data. 3. Execute with context and confidence So now you've got a roadmap. But how do you get your org from point A to point B? Knowing which initiatives to fund and cut, and how to sequence changes, has traditionally been the domain of analysts and consultants. I've seen months of effort spent winding down a single underperforming division. Complex, multithreaded problems -- like reengineering a 50,000-person org on the fly -- are exactly what AI was built for. Today's tools can wade through endless variables and map out paths in seconds, not months. But this only works if one key condition is in place: context. An off-the-shelf LLM might suffice if you're firing off a quick email or coding a new app. But when it comes to transforming your workforce, context is everything: team history, budget constraints, compliance boundaries, skill gaps, and target business outcomes. 4. Activate your managers Ultimately, any workforce transformation lives or dies with frontline managers. HR may own talent, but managers own performance outcomes. That's why empowering them to drive better people decisions is critical. Getting there means closing the "last-mile" gap that leaves so many managers flying blind. Caught up in the day-to-day, most managers lack a holistic view of their team, let alone how it impacts business performance. The core problem: no access to the data that enables true workforce insights. Fixing this starts with democratizing workforce data and insights. This is a cultural challenge, first and foremost -- too many departments hoard their data, and not enough leaders trust frontline managers enough to share it. But it's also a technical one. Managers are already swamped with dashboards and reporting tools. What's missing is real-time intel they can act on. New AI-powered tools deliver just that, letting managers ask questions in plain language. Who should I have a retention chat with this week? Which of my top performers are showing early signs of burnout? How long has my open role been vacant, and what's it costing us? Pulling together people and business data from across HR systems, CRM and revenue platforms, and everyday employee apps, AI gives managers a clear, reasoned answer. 5. Keep improving With the first four steps in motion, the final one is all about making workforce transformation a habit. AI keeps moving the goalposts, so the cycle never stops. To stay ahead, companies need to build continuous improvement into their operations. Here, too, AI can prove an ally, not merely a challenge. Workforce plans and projections provide a useful baseline. But today's tools ensure progress is continually monitored, with gap-to-plan and opportunity-to-outperform continually flagged for follow-up. Agentic AI can also provide a needed push. Always-on agents keep working in the background, nudging program owners when they're off-track and surfacing the next priority before leaders have to ask. This is what turns workforce transformation from a one-time project into an ongoing discipline. The companies that master it will be in a much stronger position: not just understanding how work is changing, but moving with it.

CEOs Are Training Workers on AI. This Fortune 500 Company Says That's Only Half the Job

CEOs are racing to make their workforces AI-ready. That makes sense. But one Fortune 500 company is asking an equally important question: Are our people becoming human-ready for the age of AI? According to Forbes, Principal Financial Group has trained more than 90 percent of its roughly 19,000 employees in AI fluency and data literacy. That alone is impressive. But CHRO Lisa Coulson sees AI skills as only half the equation. Principal is also investing across the enterprise in distinctly human skills of emotional intelligence: empathy, communication, collaboration, self-awareness, adaptability, curiosity, critical thinking, and trust-building. That's a workforce strategy more CEOs should pay attention to. AI changes what becomes valuable The business case for AI upskilling is obvious. Employees who know how to use AI can work faster, find insights sooner, automate routine tasks, and potentially create more value. But therein lies the opportunity. If AI increasingly handles the routine, transactional, and analytical parts of work, what becomes more valuable? The human parts. The ability to exercise human judgment, collaborate with someone who sees the problem differently, and communicate a difficult message with empathy. How about adapting when a role changes, managing your emotions when uncertainty is high, or building trust with a customer? All important.