Latest news with #2025WorkTrendIndex
Forbes
18-05-2025
- Business
- Forbes
The Skills We Used To Teach Managers? Now Everyone Needs Them
If Every Employee Is an Agent Boss, Everyone Needs Management Skills For decades, we treated management as a milestone. You got promoted, and then, maybe, someone taught you how to delegate, give feedback, manage performance, align tasks to strategy, and handle conflict. These were leadership skills. And we handed them out selectively. But AI just blew that timeline wide open. The moment an employee starts working with AI agents, they're not just executing. They're managing. They're assigning tasks, defining expectations, reviewing output, course-correcting, deciding what to trust and what to override. In its 2025 Work Trend Index, Microsoft introduced a new archetype for the AI era: the Agent Boss: employees who don't just use AI, but lead it. And that changes everything we know about employee development. For years, we taught new managers how to lead people: how to give direction, motivate teams, resolve conflict, and build trust. These were considered advanced skills - something you earned the right to learn. But today, anyone managing AI agents is performing those same functions. The difference? Their 'team' isn't made up of people. It's made up of technology. And yet the fundamentals remain strikingly familiar. A team lead would learn to assign the right work to the right person, balancing skill, capacity, and ownership and then align team activity to business goals. Today's Agent Boss does the same with systems. They must now ask: what should be automated, what should remain human, and how do both sides work toward the same objective? They need to learn to break work into components, identify which tasks can be offloaded to AI, and direct them to the right tools, while integrating the results into a final outcome. Example: A marketing associate planning a campaign uses one tool to generate copy, another to analyze audience data, and a third to design visuals. They orchestrate across agents like a creative director would with a human team. Managers were trained to conduct regular reviews and give constructive feedback, help people grow, and adjust direction when results didn't land. Agent Bosses do that with models. They monitor real-time output, review AI results for quality, spot inconsistencies, and fine-tune workflows - rephrasing prompts, adjusting parameters, or choosing better tools when the first one falls short. Example: A recruiter using AI to screen resumes doesn't just accept the ranking. They notice inconsistencies, review false negatives, adjust criteria, and retrain the model to better reflect hiring priorities. Traditionally, managers built trust through clarity, consistency, and follow-through. With AI, the trust equation shifts: When do you trust a model? When do you override it? How do you stay accountable for results you didn't fully produce? Example: A financial advisor uses AI to draft investment scenarios but manually reviews and tailors recommendations. Trust isn't default - it's managed. What we once reserved for managers is now the daily reality for anyone working alongside AI - in marketing decks, hiring processes, supply chains, and customer service scripts. And if employees are making these calls, they deserve the training that used to come with a management title. Managers were once trained to set expectations, align people, and resolve misunderstandings. Agent Bosses still need those skills, but now they apply them across humans and machines. Communication becomes a systems skill: clear, structured for AI, collaborative for humans. The conflict isn't just interpersonal anymore - it's architectural. Who owns the task? What gets automated? What needs a human touch? Example: A customer service team lead notices tickets falling through the cracks - not because someone failed, but because agents and humans both assumed the other had it covered. The fix isn't a feedback session - it's a workflow redesign. If every employee is now managing intelligence, then every employee needs leadership training. But most organizations aren't set up for that. We still treat management development as an optional add-on - a promotion perk you get once you've proven yourself as an individual contributor. That mindset no longer works. Because in the age of AI, the moment you sit down at your desk, you're not just doing the work. You're directing it. And that makes you accountable for quality, impact, and alignment, even if you've never managed a person. So the training once reserved for new managers - how to delegate, how to evaluate, how to intervene when something goes wrong, how to coach through ambiguity, how to align decisions with strategy - those can't wait anymore. They need to be part of onboarding. Part of employee development tracks. Part of how we prepare interns, entry-level hires, even students. This isn't a soft skill shift. It's a structural one. And it calls for a new approach to talent development, one that assumes every employee is a leader of systems, even if they never manage a person. This shift isn't just about capability. It's about expectation. Employees will soon be expected to show up with more than functional expertise. They'll be expected to show judgment. Ownership. The ability to scale themselves through technology. That's not just productivity. And it's not just about reskilling. It's about reframing leadership for a world where technology is part of the team and every employee is expected to lead it. If we want people to thrive in this new world of work, we need to stop asking whether they're ready to be managers. We need to start preparing them to be Agent Bosses.
Mint
03-05-2025
- Business
- Mint
When AI gets a manager, you know the game has changed
When you need to hire a person just to manage your artificial intelligence (AI), something fundamental has changed. Not in the future. Not in theory. Right now. I recently met a startup founder who told me—half-laughing, half-serious—that he was hiring an 'agent manager." 'Prompts are all over the place," he said. 'Tone is off. The output needs babysitting. I need someone to train and track our AI agents so the team can just get on with their work." We both laughed. But later, I realised: this isn't absurd. It's inevitable. Read this | India must forge its own AI path amid a foundational tug of war For the last year, we've debated whether AI will replace human workers. But we're missing the real shift unfolding right under our noses: humans are now managing AI—not just building it, not just using it, but structuring teams around it, delegating to it, and in many cases, becoming dependent on it. Microsoft's 2025 Work Trend Index quantifies the shift: 82% of global leaders say AI agents will be deeply embedded in their organisations within the next 12–18 months. One in four companies has already deployed them at scale. But what matters more than adoption is how unevenly that change is playing out. At one of India's top five global capability centres (GCCs), a pilot team recently tested a 'human-to-agent ratio"—assigning one agent per employee. The results were revealing. Not just productivity gains, but deep friction. Some employees hesitated to delegate. Others over-delegated. Most weren't confident about what the agent was doing behind the scenes. The tech wasn't the problem. Trust was. This is the invisible divide emerging across workplaces—not between humans and machines, but between those who know how to collaborate with AI and those still figuring it out. Microsoft calls the leading companies 'Frontier Firms." I see something slightly different: agent-literate organizations. Places where managing digital teammates is just part of the job. Where people are learning that prompting isn't about clever phrasing—it's about structure, tone, and cultural nuance. Where performance reviews might soon include a line item for 'AI fluency." It sounds ridiculous. Until you realise it's already happening. One founder in Pune runs an ops team of five, supported by seven agents. The agents draft emails, generate reports, and chase vendors. The humans supervise, escalate, and course-correct. 'We're not hiring another ops exec anytime soon," he said. 'We're hiring someone to train the agents." It sounds efficient. But here's the part we don't talk about: not everyone on that team has the same voice in how those agents behave—the person who knows how to speak as the agent sets the tone. The rest follow. Or worse—stay silent. That's what this moment is really about. Not 'Will AI take my job?" But: Who gets to shape how AI shows up at work? Who trains it, manages it, critiques it—and who is left trying to work around it? We're not heading towards a divide between white-collar and blue-collar anymore. That line is already fading. The real split now is between the agent-native and the agent-blind. The people who know how to talk to AI , shape it, and make it work for them—and the ones who don't, or can't. It's not just a skill gap. It's a confidence gap. A permission gap. And it's growing fast. In every room I've been in lately, it's the same thing: a few people steering the conversation with AI, and the rest quietly adapting around it. Read this | Mint Primer | Clicks & growls: Why AI's hearing the call of the wild Fluency is becoming power. Silence is becoming costly. Microsoft's data shows the power gap widening: Leaders are 25–30% more likely than employees to use AI regularly, trust it with critical work, and see it as a career accelerator. That's not a skills gap. It's a shift in agency, a quiet realignment of power and confidence. And like every transition in work, it's happening unevenly, with the loudest people learning fastest, and the rest adapting in the margins. This is why I believe the most urgent challenge of this moment isn't just upskilling. It's building AI fluency with psychological safety and creating cultures where people can experiment, fumble, question the output, and push back when the machine gets it wrong. Because this isn't about becoming prompt engineers, it's about becoming context designers. It's about knowing when to hand over—and when to hold on. When to trust, and when to intervene. Knowing that yes, AI can finish your sentence—but it's still your voice on the line. The founder hiring an agent manager? He may sound like a punchline. But he's probably ahead of the curve. Because within five years, every role will have an AI layer—and not every team will have the space, safety, or support to adapt in time. Access is not enough. Adoption is not enough. What we need is fluency. And the cultural permission to build it. Also read | AI hallucination spooks law firms, halts adoption Because the real risk isn't that AI takes your job. It's that you're still in the room, but no longer part of the conversation. And by the time you notice, the decisions might already be made—without your voice, and without your kind of thinking.
Time of India
01-05-2025
- Business
- Time of India
AI driven ‘frontier firms' are redefining workforce structures, finds Microsoft's 2025 Work Trend Index
A new breed of organisations, dubbed 'frontier firms', is reshaping the global workforce by embedding artificial intelligence into everyday operations, according to Microsoft's 2025 Work Trend Index , conducted with LinkedIn. These firms rely on dynamic, hybrid teams where humans and AI agents collaborate to meet rising business demands, marking a clear shift from traditional hierarchical models. The report draws insights from over 31,000 professionals in 31 countries, combining LinkedIn labour market data and Microsoft 365 productivity signals. Its key finding: AI has made intelligence abundant and scalable, challenging the assumption that workforce capacity must expand linearly with headcount. Amid economic pressure, 82% of leaders plan to adopt AI solutions within 12–18 months. However, 53% believe productivity still needs to improve, while 80% of employees say they lack the energy and time to meet rising expectations, revealing a gap between business ambition and human bandwidth. Constant workplace interruptions from emails, meetings, and chats further erode employee focus. To close this gap, organisations are automating workflows, and 46% already deploy AI agents in customer service, marketing, and product development. These shifts are ushering in a new organisational model, where ' agent bosses ', employees who train and manage AI tools, become critical workforce actors. Yet, a readiness gap persists: 67% of leaders feel familiar with AI agents, compared to just 40% of employees. Microsoft's Zubin Chagpar notes that success hinges on how well companies empower their human-agent teams. 'Businesses must rethink how they harness AI to unlock their full potential,' he said, emphasising the growing need for AI literacy, training, and human oversight.
Forbes
29-04-2025
- Business
- Forbes
LinkedIn Data Shows Executives Upskilling AI Over Traditional Skills
According to LinkedIn's data, C-suite executives are 1.2 times more likely than the rest of the ... More workforce to add AI-related skills to their profiles. In boardrooms from London to Singapore, the conversation around artificial intelligence has shifted dramatically. No longer a speculative investment or a buzzword tossed around in innovation decks, AI is becoming a core competency for today's leaders. And according to newly released data from LinkedIn, the shift isn't just philosophical—it's tangible. Three times as many C-suite executives are listing AI literacy skills like prompt engineering and generative AI tools on their LinkedIn profiles today compared to two years ago. This trend underscores a critical transformation is underway: AI literacy is moving from the periphery to the core of executive leadership. The impact of AI on jobs, skills and businesses in just a few years means that every executive must now understand what the technology can do to successfully lead their function, and drive productivity and innovation. Microsoft's 2025 Work Trend Index highlights how profoundly AI will transform organizations and the necessity to prepare for change today. Leaders are taking note. According to LinkedIn's data, C-suite executives are 1.2 times more likely than the rest of the workforce to add AI-related skills to their profiles. That's a significant shift and one that reflects a growing understanding that AI adoption starts at the top. This isn't just about optics or résumé padding. An overwhelming 88% of global C-suite leaders say accelerating AI adoption is a top priority for 2025. Early data suggests a positive return on investment: more than half of companies that have already begun integrating AI tools report a revenue boost of at least 10%, finds LinkedIn. But ambition alone doesn't guarantee execution. Four in ten executives admit their own leadership teams are a barrier to AI integration—whether due to a lack of training, skepticism about return on investment or simply being unprepared for the cultural shifts AI demands. In short, while leaders understand the 'why' of AI, many are still grappling with the 'how.' One reason AI is climbing the leadership agenda is because it's rapidly becoming a business necessity. LinkedIn's research found that AI literacy is now one of the most in-demand skills across all job roles. Among C-suites, it has even overtaken traditional executive traits like operational experience or financial acumen as the most important skillset needed to navigate change. That's not just influencing how leaders view their own development—it's changing how they hire. Eight in ten business leaders say they'd rather hire someone who's comfortable with AI tools than someone with more traditional experience but less AI fluency. Experience still matters but only if it's future-proof. This signals a profound reshaping of executive leadership. AI literacy is no longer optional. It's a defining capability—one that determines whether an executive can lead through the complexity of digital transformation or risks falling behind it. Dan Shapero, LinkedIn's Chief Operating Officer, echoed this urgency, noting that leadership— and not just technology—is often the true gatekeeper for AI transformation. In an interview, he told me, 'AI adoption is fundamentally a leadership challenge as much as a technology one.' Shapero added that while many organizations recognize the need for technological change, 'they underestimate the profound level of change management required to bring AI into the daily habits of their teams.' This is why modeling change is crucial - it's simply not enough for leaders to endorse AI from the sidelines. They have to show up—hands-on and informed. That means not just talking about AI in strategy meetings but actively using it in decision-making, team management and personal productivity. Leaders who model AI literacy signal that it's not a job for a future hire or a specialized department—it's a shared responsibility. Shishir Mehrotra, CEO of Grammarly, has been doing exactly this. He told me in a written statement, 'Personally, AI helps me scale my day-to-day work by handling tasks that would otherwise eat up hours of my time—capturing action items from customer conversations, drafting initial follow-up messages, and quickly locating buried information across docs.' Likewise, Anahita Tafvizi, the chief data analytics officer at Snowflake, said: 'The AI landscape is evolving fast, and leaders who continuously engage, experiment, and sharpen their own skills will be best positioned to guide their teams and drive results.' This behavior shift has real downstream effects. When the C-suite leads with confidence in AI tools, it gives teams permission—and incentive—to do the same. Culture follows example. And right now the example needs to be set from the top. From Classroom to Boardroom: Making AI Learning Accessible To bridge the gap between intention and execution, LinkedIn and Microsoft are offering free access to a suite of AI-focused learning courses and professional certificates through the end of 2025. These aren't generic introductions—they're designed specifically for leadership roles. One program AI for Organizational Leaders includes six targeted courses focused on helping executives make informed decisions about AI strategy, understand the business implications of generative AI and harness these tools for competitive advantage. Another AI for Managers aims to arm mid-level leaders with practical applications—from improving team meetings to building collaborative cultures using AI. Beyond these flagship certificates, LinkedIn and Microsoft have launched over 150 AI Skill Pathways covering various roles and levels within the LinkedIn AI Upskilling Framework. It's a roadmap that reflects the multifaceted nature of AI readiness and the urgency of equipping entire organizations, not just individual departments, with the tools to thrive. The rapid rise of AI-literate executives reflects a broader truth: leadership in the age of AI means knowing what questions to ask, understanding the tools that can help, and being open to continuously learning. As technology continues to evolve at breakneck speed, the ability to adapt, experiment and lead by example will be what separates tomorrow's winners from today's status quo.
Forbes
23-04-2025
- Business
- Forbes
Microsoft Just Rewrote Work—Here's The New Language
The future of work has arrived. It's here earlier than anticipated. We've spent years inching toward the future of work, planning for it bit by bit. But it didn't arrive gradually. It snapped into place all at once. That's the feeling Microsoft's 2025 Work Trend Index delivers. It doesn't add tools—it redraws the entire map. And before we can navigate that new terrain, we need to learn the language it's written in. We're not just being asked to work differently. We're being asked to reimagine the structure, purpose, and language of work itself. This year, Microsoft isn't talking about hybrid work or upskilling. It's naming 2025 as the year the Frontier Firm is born—an organization powered not just by human effort, but by intelligence that's scalable, on demand, and ambient. Intelligence on Tap. Let that sink in: Intelligence on Tap. Like electricity. Like cloud storage. Like bandwidth. Expertise becomes a utility—not something you hire, but something you access. When you combine that idea with AI agents capable of planning, reasoning, and taking action, the ripple effects are seismic. For people. For organizations. And this reshapes what it means to build a career, to manage a team, to lead an organization. In other words, regardless of your role in the world of work, your job just shifted. This is where the most radical shift happens. For decades, intelligence was a scarce resource—limited by human time, cost, and capacity. But that constraint is vanishing. With AI and agents that can reason, plan, and execute, intelligence is no longer confined to the people you hire. It's becoming scalable, on-demand, and ambient—a capacity you can access, not just employ. But if your people can build the intelligence they need, then why are you still organizing around job titles and departments? Drawing on global insights from 31,000 workers, real-time LinkedIn data, and trillions of Microsoft 365 signals—alongside conversations with startups, economists, and researchers—Microsoft sketches out the emerging blueprint for what it calls a Frontier Firm. These firms move faster, scale smarter, and create value more dynamically than traditional organizations. Their structures shift from static org charts to what Microsoft calls Work Charts—fluid, outcome-driven formations where teams assemble around tasks, not titles. You don't build teams—you orchestrate them around the work that needs to be done, not fixed roles and responsibilities. That's not just theory. Frontier Firms are already taking shape—and in the next few years, most organizations will be pushed to follow. Microsoft found that 82% of leaders see 2025 as a pivotal year to rethink structure and strategy, with the majority expecting AI agents to play a major role within the next 12 to 18 months. And who manages this new mix of human and AI capacity? Perhaps not Human Resources as we know it, but a blended HR and IT function that manages Intelligence Resources—both types of labor: people and agents. Think of it as the team that designs and staffs hybrid teams, tracks the Human-Agent Ratio, and ensures oversight, trust, and results. If employees were the ones leading AI adoption last year—bringing their own tools and experimenting at the edges—this year marks a sharp turn. Now, it's leaders who are moving faster. 67% of leaders are familiar or extremely familiar with agents compared to just 40% of employees. And 79% of leaders believe AI will accelerate their careers versus 67% of employees. Why are managers ahead? As Colette Stallbaumer, General Manager of Microsoft 365 Copilot and Co-Founder of WorkLab at Microsoft, told me in a recent conversation on The Future of Less Work podcast, 'Leaders recognize they can't afford to sit on the sidelines. They can't afford to wait in order to stay competitive.' Likely because they're the first under pressure to have a clear AI strategy—and the first held accountable if it fails. But more than that, managing AI plays to what great managers already do well: delegate, coach, course-correct. They're used to coaching team members, setting expectations, building trust. And that's exactly what working with AI agents now requires. In other words, we don't need to reinvent management. We just need to redirect it—toward people and machines, to design and orchestrate performance across a hybrid team, many of whose members aren't human. Which brings us to the individual—each one of us. We're not just learning to use AI—we're learning to manage digital peers. To assign work to agents. To onboard them, train them, refine their outputs. To know when to override and when to trust. The report introduces the Agent Boss—a new archetype for the modern worker who leads not just people, but AI agents. Not the solo expert. Not the individual contributor. But the human who knows how to delegate across a hybrid team of people and bots. 'Now everyone can be an agent boss,' said Stallbaumer. 'Think of your work like you're the CEO of your own startup. How are you deploying AI to get things done throughout every part of your workday?' And for those who embrace it, the opportunities are extraordinary. 'A junior person can manage a crew of intelligent agents and perform senior-level work in months instead of years,' she explained. The career ladder? It just got replaced with a launchpad. It's not magic—it's a mindset shift: from 'What can I do?' to 'What can I delegate?' And it starts with learning how to build your first agent. We're not in the planning phase of this transformation. We're in the rollout. And yet, most of us—leaders, employees, HR—are still using the language of the old map. We're measuring people by role, not impact. We're designing orgs for predictability, not adaptability. We're waiting for permission to experiment, when in fact, the only risk now is standing still. That's why this report deserves more than a summary. It demands reflection. What kind of organization do you want to work for—or lead? What kind of manager do you want to be when part of your team isn't human? And what kind of career are you building if success depends not on how much you can do—but on how well you can scale yourself through intelligent agents? Take a breath. The map has changed. And the language we use to describe work is changing with it. We've only begun to explore what that means—and where it might lead.
