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Forbes
6 days ago
- Business
- Forbes
Workforce Reskilling Is The Competitive Edge In The Agentic AI Era
Agentic AI AdobeStock_1157006091 From Generative to Agentic — A New Chapter in Enterprise AI Generative AI brought along tools like chatbots and auto-generated content, but the next frontier is Agentic AI – systems that can plan, decide, and act across processes. Agentic AI is designed to handle ambiguity and equipped to make autonomous decisions, and companies are excited about its potential, with the Agentic AI market expected to be worth $196B by 2034, reaching an impressive CAGR of nearly 44%. However, scaling agentic solutions requires a multi-disciplinary delivery model—combining deep industry, data, technology, and process expertise with specialized talent. Furthermore, agent orchestration is the emerging backbone of enterprise architecture: a way to coordinate multiple specialized AI agents as an intelligent network. In practice, this means bridging data, processes, and customer engagement through AI-driven workflows instead of point-to-point integrations. Enterprises will increasingly run AI-infused processes with agents handling data flows and humans supervising outcomes. 'Agentic AI demands more than smart algorithms—it demands smart organizations,' says Sanjeev Vohra, Chief Technology and Innovation Officer at Genpact. 'Enterprises need to reimagine how their people and processes interact with technology. That starts with deeply reskilling the workforce for a future where AI is embedded in every decision.' The Workforce Wake-Up Call — Why Talent, Not Tech, Will Decide Agentic AI Success Despite the hype, the real bottleneck is talent. According to a recent Prosper Insights & Analytics survey, 43.5% of executives already use Gen AI tools, but only 26.5% of employees say the same. This data highlights an 'unforeseen talent gap' between executives and employees – suggesting that there is not necessarily a lack of interest in AI, but a shortage of skilled people to implement it. Prosper - Heard of Generative AI Prosper Insights & Analytics Globally, employees are eager to learn. In Genpact's research, nearly 80% of workers said they want new AI-related skills and 59% said they'd be more comfortable with AI if they understood it better. Yet few companies have scaled training. The research also revealed that only around one in three employees are offered AI training, and just 21% have participated. Enterprises are already taking action by segmenting their workforce into AI builders and consumers. Builders (data scientists, engineers, domain experts) create and refine AI tools, while the broader workforce is made 'AI-fluent' – trained to use AI outputs and embed them in decision-making. This dual investment in specialized talent and broad AI literacy is now viewed as essential for thriving in the agentic era. Beyond Automation — Rethinking Roles, Skills, and Human-Machine Collaboration AI will transform legacy roles, with some fading, but many new ones are emerging. We're already seeing this shift in action, with 'prompt engineers' who craft inputs for AI models, 'AI translators' who turn machine outputs into strategic advice, and 'agent overseers' who manage fleets of AI tools. The survivors will have blended skillsets combining domain expertise, technical savvy, and human judgment. Even as AI handles more tasks, human collaboration remains crucial as humans will be responsible for oversight, creative decisions, and ethical judgment while offloading repetitive or data-intensive steps to agents. As a result, organizations must encourage 'learning by doing' and engage experts to create micro-projects so employees can practice new skills on real problems. Embedding Responsible Innovation — Ethics, Upskilling, and Culture at the Core As Agentic AI grows, so does the need for controls and conscience. According to a recent Prosper Insights & Analytics survey, employees have several concerns with the use of AI, specifically in terms of them agreeing it requires human oversight (33.6), more transparency on the data it uses (29.6%), and that can cause job loss (27.9%). Prosper-Concerns About Recent Developments in AI Prosper Insights & Analytics Every AI deployment must include robust oversight, including operating within controlled parameters and following responsible AI guidelines. This means using role-based access controls, audit logs, and clear human-in-the-loop checkpoints from day one. Establishing guardrails early builds trust and avoids the mistakes of 'blind' automation. 'The future belongs to companies that scale curiosity, not just code—by building human-centered upskilling programs and by fostering a culture of shared learning and responsible innovation, where experts share knowledge across networks. In this way, organizations instill a sense of collective responsibility. And the result is a virtuous cycle: a more skilled and diverse workforce that innovates both rapidly and responsibly,' Vohra says. A Playbook for Change — How to Start Building an Agentic-Ready Workforce Today To build a workforce that can thrive in the Agentic AI era, organizations must first map their future organization and reimagine roles by identifying which jobs will evolve, such as prompt engineers or AI ethicists, as well as which may no longer be needed. Determining which employees are AI builders or users will enable an organization to launch targeted training that reflects any needed shifts. With a clear view of the future roles it will need, organizations must then pair investments in core AI talent with efforts to achieve widespread AI fluency. This can be done by incorporating continuous learning into daily workflows and encouraging hands-on learning through micro-projects, hackathons, internal training, and peer mentorship. Celebrating these efforts during regular reviews and building cross-functional pods that combine business, IT, and data talent can reinforce a collaborative culture where learning, experimentation, and AI adoption compound to address all facets of a problem. Lastly, organizations cannot build an agentic-ready workforce unless they are prioritizing responsible AI. To address concerns, organizations must ensure clear oversight, offer human-in-the-loop systems, and implement guardrails to manage risks from day one of their AI implementation journey. Innovation can never outpace oversight, and that may require organizations to start with small proofs-of-concept to ensure oversight and gauge talent and infrastructure readiness. Reskilling is no longer optional—it's a survival imperative. Enterprises that embrace these shifts and build blended skillsets (domain + tech + human judgment) will gain the decisive edge in the Agentic AI era.
Forbes
12-05-2025
- Business
- Forbes
Amazon Web Services Says 77% Of Women Want To Build With AI
AWS research reveals a growing demand for generative AI fluency, especially among women ready to ... More lead in the next era of work. Artificial Intelligence has gone from being a big, scary monster taking over the world to a powerful tool that assists people in building companies. Leaders are now understanding how AI streamlines workflows. As with any emerging sector, how do women create a space where they thrive over the 'bro code?' According to new research commissioned by Amazon Web Services, 77% of U.S. women in professional roles are interested in learning generative AI skills. Additionally, 80% would apply to jobs that involve generative AI. Yet only 6% consider themselves AI experts, and 42% say their companies fail to offer meaningful AI skill development. 'These challenges could have long-term consequences,' says Jenni Troutman, director of products and services at AWS training and certification. 'The interest is clearly there, but interest without access leads to missed opportunities. And in an industry where women only make up about 22% of the AI workforce, we can't afford that kind of gap.' Although AI is becoming easier to learn, 33% of women don't know where to begin. The AWS study found that women's top challenges when building AI fluency include being unsure how AI applies to their current role and having limited access to training. 'I was shocked that so many women felt like they didn't have access to resources,' Troutman says. 'There's so much out there, but it made me realize we must do a better job of helping people find and trust the right tools.' Fear isn't holding women back. It's the sheer speed of change. 'Generative AI isn't new in theory, but what's new is the pace and scale of what's possible,' she continues. 'And that's overwhelming for anyone, not just women.' Over the past few years, females have become more confident in the office. However, there are still areas of improvement that need to be addressed. For instance, the Harvard Business Review reported that during a study, a main self-evaluation question revealed that 80% of women believe they have a 'poor performance.' In comparison, only 56% of men do. Regarding AI, the World Economic Forum reported key findings from Randstad's Workmonitor 2025 study, which found AI is the top-three skilling priority for 40% of global talent. While 44% of men were more likely to say so than 36% of women, the gap was less pronounced when it came to their belief in their qualifications in the technology and AI skills they already had (73% of men vs. 69% of women). Now, with new AI skill sets required by companies, women often underestimate their qualifications. 'Women tend to look at a job's requirement and think, 'If I don't meet every single one, I'm not ready,'' states Troutman. 'Meanwhile, others might meet just a portion and still go for it.' Women across industries are eager to build AI skills, but access to training and employer support ... More still lags behind. Closing the gender gap in AI is about shifting the mindset from perfection to progress. That's where foundational learning matters. AWS Skill Builder and AWS Educate offer more than 135 free, low-cost AI and machine learning courses, from Generative AI Essentials to Amazon's Nova models training. One key entry point? Prompt engineering. 'It sounds technical, but it's just about asking the right questions,' she explains. 'If you're in HR or marketing and using a tool to generate content or analyze data, your prompts determine how useful the results are. That's a skill anyone can build.' Troutman began her career in consulting at Accenture, working in business intelligence and strategy. Though she didn't set out to work in training, her consulting mindset proved invaluable when she joined VMware to build out a global sales enablement practice. 'I didn't know anything about training from the delivery side,' she says. 'But I treated it like a project. I figured out the infrastructure and the programs and how to make them effective.' That same problem-solving approach led her to AWS, where she's helped scale training and certification from thousands of learners to millions. For women ready to validate their knowledge, AWS offers two key certifications: 'Certifications aren't just about career changes,' Troutman notes. 'They help people feel more confident using AI in their current role, and that's just as important.' Organizations can better support women's conviction in pursuing AI by: 'If you don't understand how AI tools can help you innovate, now's the time to learn,' Troutman concludes. 'Because soon, AI fluency won't be a bonus. It'll be a baseline.' The future of work is already taking shape, and women are poised to play a defining role in its direction. To participate fully, they must have access to opportunity and the confidence to chart the path in an AI-driven world.
