We are entering a new reality—one in which AI can reason and solve problems in remarkable ways. This intelligence on tap will rewrite the rules of business and transform knowledge work as we know it. Organizations today must navigate the challenge of preparing for an AI-enhanced future, where AI agents will gain increasing levels of capability over time that humans will need to harness as they redesign their business. Human ambition, creativity, and ingenuity will continue to create new economic value and opportunity as we redefine work and workflows.
As a result, a new organizational blueprint is emerging, one that blends machine intelligence with human judgment, building systems that are AI-operated but human-led. Like the Industrial Revolution and the internet era, this transformation will take decades to reach its full promise and involve broad technological, societal, and economic change.
To help leaders understand how knowledge work will evolve, Microsoft analyzed survey data from 31,000 workers across 31 countries, LinkedIn labor market trends, and trillions of Microsoft 365 productivity signals. We also spoke with AI-native startups, academics, economists, scientists, and thought leaders to explore what work could become. The data and insights point to the emergence of an entirely new organization, a Frontier Firm that looks markedly different from those we know today. Structured around on-demand intelligence and powered by “hybrid” teams of humans + agents, these companies scale rapidly, operate with agility, and generate value faster.
Frontier Firms are already taking shape, and within the next 2–5 years we expect that every organization will be on their journey to becoming one. 82% of leaders say this is a pivotal year to rethink key aspects of strategy and operations, and 81% say they expect agents to be moderately or extensively integrated into their company’s AI strategy in the next 12–18 months. Adoption is accelerating: 24% of leaders say their companies have already deployed AI organization-wide, while just 12% remain in pilot mode.
The time to act is now. The question for every leader and employee is: how will you adapt?
Journey to the Frontier Firm
Every organization’s AI transformation will look different, but here’s how we see it playing out over time.
We see the journey to the Frontier Firm playing out in three phases. First, AI acts as an assistant, removing the drudgery of work and helping people do the same work better and faster. In phase 2, agents join teams as “digital colleagues,” taking on specific tasks at human direction—for instance, a researcher agent creating a go-to-market plan. These agents equip employees with new skills that help scale their impact—freeing them to do new and more valuable work. In phase 3, humans set direction for agents that run entire business processes and workflows, checking in as needed. Just as we’ve seen the role of AI in software development evolve over the past three years from coding assistance to chat to—now—agents, the same pattern will apply to knowledge work. Picture how a supply chain role may change: agents handle end-to-end logistics, while humans guide the agent system, resolve exceptions, and manage supplier relationships. The journey to the Frontier Firm is not a strictly linear progression—in many cases organizations will be in all three phases simultaneously.
The Frontier Firm, a glossary
New terms to know for a new world of work.
1
You can buy intelligence on tap
For decades, intelligence was one of the most valuable—and limited—assets in business, bound by human time, energy, and cost. That’s changing. Intelligence is becoming an essential durable good: abundant, affordable, and available on demand. With the rise of AI and agents that can reason, plan, and act as digital labor, companies can scale capacity as needed. Already, 82% of leaders say they’re confident that they’ll use digital labor to expand workforce capacity in the next 12–18 months.
As economic and shareholder pressure mounts for businesses, digital labor offers a new lever for growth—one that helps close the widening gap between what businesses demand and what humans can sustainably deliver.
Our data reveals a capacity gap: 53% of leaders say productivity must increase, but 80% of the global workforce—both employees and leaders—say they’re lacking enough time or energy to do their work.
Intelligence on tap fills the capacity gap
Both leaders and employees are maxed out, but business demands continue to rise. Many see agents as the way forward.
Survey Questions:
In the last year, to what extent do you agree or disagree that you have struggled with the following at work? (share of respondents who said they agree)
To what extent are your employees’ productivity levels meeting the needs of the business? (share of respondents who said employees must at least moderately increase their productivity)
Now, let’s explore how AI agents will impact your workforce and business processes in the next 12–18 months. To what extent are you confident your organization will leverage agents to expand workforce capacity with AI agents acting as digital team members? (share of respondents who selected at least medium confidence)
The telemetry is telling: During the 9–5, employees are interrupted every 2 minutes by meetings, emails, or pings. Factor in activity outside of core work hours, and it adds up to 275 interruptions a day. 60% of meetings are ad hoc versus scheduled. Edits in PowerPoint spike 122% in the final 10 minutes before a meeting. Chats outside the 9-to-5 workday are up 15% YOY, with 58 messages now arriving before or after work hours. And meetings after 8 p.m. are also up 16% YOY, driven by an increase in cross–time zone work. It’s no surprise that nearly half of employees (48%)—and more than half of leaders (52%)—say their work feels chaotic and fragmented.1
AI is delivering real productivity gains, but it’s not enough. The speed of business is still outpacing the way we work today. To keep up, companies must do more than add AI to existing workflows—they must rethink the very nature of knowledge work. This starts with separating knowledge workers from knowledge work. Humans—uniquely capable of creativity, judgment, and connection-building—were not meant to just answer emails all day. Just as Word and Excel reshaped how we work, agents will too. Where we once said, “I send emails,” “I write documents,” “I create pivot tables,” we’ll soon say, “I create and manage agents.” It’s a shift as profound as the web and mobile eras—one that fundamentally redefines the work we do and removes the drudgery that weighs us down.
Business demands outpace human capacity
Today’s work is pushing the limits of humans alone, keeping employees from high-value tasks that drive growth and innovation.
Frontier Firms2 are proving what’s possible—defined by five traits that set them apart: org-wide AI deployment, advanced AI maturity, current agent use, projected agent use, and a belief that agents are key to realizing ROI on AI. Among our 31,000-person sample, 844 employees work at companies that meet this bar. While these are the earliest adopters, they point to where things are headed.
71% of Frontier Firm workers say their company is thriving, compared to just 37% of workers globally.
55% say they’re able to take on more work (vs. 20% globally)—and they’re also more likely to report having opportunities to do meaningful work (90% vs. 73% globally).
Frontier Firm workers say they’re more optimistic about future work opportunities (93% vs. 77% globally) and less likely to fear that AI will take their jobs (21% vs. 38% globally).
From global enterprises to small businesses, AI is the engine for scale. One solo founder we spoke with is on track to earn $2 million this year with an AI-powered staffing firm. Dow is projected to save millions in the first year with a supply chain agent that flags misapplied fees. And ICG, a five-person startup, uses AI for everything from construction simulations to market research—boosting margins by 20%. One entrepreneur even told us they run core functions like budgeting and forecasting without a CFO, thanks to a single AI tool.
AI skilling and digital labor are top workforce strategies
Retaining top talent while reducing headcount is also being considered.
Survey Question:
As you consider the role of AI and agents in workforce and talent management, which strategies are your team or organization considering over the next 12–18 months?
The shift is multifaceted—every industry and role will evolve differently as the technology diffuses across business and society. Just as the internet era created billions of new knowledge jobs—from social media managers to UX designers—the AI era is already giving rise to new roles, with many more to come.
Nearly half of leaders (45%) say expanding team capacity with digital labor is a top priority in the next 12–18 months—second only to upskilling their existing workforce (47%). In some functions, the next new hire may not be a person, but a digital colleague. And while a third of leaders (33%) are considering headcount reductions, we’re also seeing new roles emerge. 3
78% of leaders are considering hiring for AI-specific roles to prepare for the future—and that jumps to 95% for Frontier Firms. Top roles under consideration include AI trainers, data specialists, security specialists, AI agent specialists, ROI analysts, and AI strategists in marketing, finance, customer support, and consulting.4
On LinkedIn, the most prominent startups have grown headcount by 20.6% YOY—nearly twice the pace of Big Tech (+10.6%).5 Much of that talent is flowing out of Big Tech and staying in the startup world, pointing to a deeper shift where innovation—and opportunity—is rising. As incumbents adapt and challengers scale, like we saw in the dot-com boom, the rules of talent and competition are being rewritten in real time. The message is clear: adapt or risk being left behind.
The Frontier Firm emerges
These forward-thinking companies are already tapping AI and agents to gain an edge.
2
Human-agent teams will upend the org chart
Until now, companies have been built around domain expertise siloed in functions like finance, marketing, and engineering. But with expertise on demand, the traditional org chart may be replaced by a Work Chart—a dynamic, outcome-driven model where teams form around goals, not functions, powered by agents that expand employee scope and enable faster, more impactful ways of working.
This mirrors the model we see in movie production, where tailored teams assemble for a project and disband once the job is done. With agents acting as research assistants, analysts, or creative partners, companies can spin up lean, high-impact teams on demand, accessing the right talent and expertise at the right time—no reorg required.
Supergood is an AI-first advertising agency where teams are flatter, faster, and more fluid—thanks to a platform that puts decades of strategic ad research at every employee’s fingertips.6 Co-founder and Chief Strategy Officer Mike Barrett says, “We don’t need a strategist on every brief. Everyone at Supergood has access to that expertise via our platform.” A recent Harvard study bears out that experience, finding that AI helped break down silos: R&D teams produced more commercially viable work, while business teams developed more technical solutions.
Nearly half of leaders (46%) say their companies are using agents to fully automate workflows or processes, but not every function will evolve at the same pace—or to the same degree. In some functions, agents will be able to handle most tasks end-to-end, requiring oversight only for high-stakes or nuanced decisions. Other functions—especially those rooted in judgment, empathy, or creative thinking—may rely more heavily on humans. As one example, a consumer goods company we spoke with is prioritizing AI investment in the functions farthest from its competitive edge, automating routine operations while preserving human value where it matters most.
In our survey, global leaders listed customer service, marketing, and product development as the top three areas for accelerated AI investment in the next 12–18 months. And workers at Frontier Firms are far more likely than non-frontier workers to use AI for tasks related to marketing (73% vs. 55% globally), customer success (66% vs. 44% globally), internal comms (68% vs. 46% globally), and data science (72% vs. 54% globally). These are the functions in which scalable intelligence is gaining ground the fastest—and where the Work Chart is quietly taking root.
To maximize the impact of these human-agent teams, organizations need a new metric: the human-agent ratio. Leaders must ask two critical questions: How many agents are needed for which roles and tasks? And how many humans are needed to guide them? For instance, the Harvard study7 found that an individual with AI outperforms a team without it, but when it comes to the highest-quality work, a team with AI outperforms them all. In a world where AI unlocks new expertise, it will also take bravery from leaders to trust people to grow beyond traditional roles.
Dialing in the human-agent ratio
As leaders assemble human-agent teams, they’ll need to get the balance right for each role, function, or project to ensure optimal performance on both sides of the equation.
Infographic by Anthony Calvert
Getting that ratio right will be critical—and task-specific. Just as HR manages human performance and IT manages systems, organizations will need new models to allocate and manage intelligence resources. Some may blend HR and IT or create new leadership roles—like a chief resources officer—that focus on managing the optimal balance of human and digital labor.
As AI democratizes access to expertise and intelligence, we’ll see the rise of Intelligence Resources departments—much like how HR and IT evolved into core functions. These new divisions will be essential for managing the interplay between humans and AI agents, emerging as a critical source of competitive advantage in the AI-enabled enterprise.
So when is it essential to keep humans in the loop? Economist and AI expert Daniel Susskind hypothesizes8 that human work will persist even as AI capabilities expand because of three limits: it can be more efficient to have AI and humans working in tandem, human preference, and moral judgment. In logistics, for instance, AI can optimize delivery routes, but human dispatchers still manage real-world disruptions—allowing AI to focus resources on scale, not exceptions. In finance, AI can model risk, but clients may still prefer a trusted advisor to guide major decisions. Lawyers may use AI to summarize case law, but high-stakes negotiations often require human judgment—not just for their complexity, but because society expects people to be responsible for the consequences.
Our data reflects some of these human preferences. When asked why they turned to AI instead of a colleague, employees cited 24/7 availability (42%), machine speed and quality (30%), and unlimited ideas on demand (28%) as the top reasons—all things humans cannot provide. Notably, using AI to avoid human traits—like impatience, the need for explanation, or reliance on judgment—ranked lowest. This suggests people prefer using AI not to replace the value humans provide, but to enhance it.
Employees turn to AI for things that humans can’t provide
Responses show that people use AI more for its singular capabilities than for its benefits over colleagues.
Survey Question:
What is your primary reason for choosing to turn to AI over a colleague or manager?
Employee mindset will also be important. Digital colleagues aren’t just tools—they’re teammates, capable of initiating action, managing projects, and adapting in real time. Today, the workforce is split. When asked how they see AI, 52% of respondents said they see it as a command-based tool—giving direct, simple commands to get the job done. 46% said they see AI as a thought partner—having conversational exchanges to challenge their thinking, brainstorm ideas, or spark creativity. The remaining 2% didn’t know.
To work effectively with agents, all employees will need to adopt a thought partner mindset and build related skills: learning to iterate with AI, knowing when to delegate to AI, prompting with context and intent, refining outputs instead of accepting first drafts, spotting weak reasoning or gaps, and knowing when to push back or steer the conversation or plan. The biggest gains will come from rethinking workflows, improving decisions, and elevating the quality of work across the board.
It’s a mindset shift. We are hardwired to think about using technology in a certain way—we see a search box and we assume we’re dealing with a search engine. The unlock is when we realize it’s not a tool but a new kind of team member.
3
Every employee becomes an agent boss
As agents increasingly join the workforce, we’ll see the rise of the agent boss: someone who builds, delegates to, and manages agents to amplify their impact—working smarter, scaling faster, and taking control of their career in the age of AI. From the boardroom to the front line, every worker will need to think like the CEO of an agent-powered startup, directing teams of agents with specialized skills like research and data analysis. For those ready to expand their scope, this will be a career accelerator—but the data shows that leaders are ahead of employees. Bridging the gap will take more than access; it will require training, oversight, and a new way of working—one that leaders must help shape.
Already, 28% of managers are considering hiring AI workforce managers to lead hybrid teams of people and agents, and 32% plan to hire AI agent specialists to design, develop, and optimize them within the next 12–18 months.9 Leaders expect their teams will be redesigning business processes with AI (38%), building multi-agent systems to automate complex tasks (42%), training agents (41%), and managing them (36%) within five years.
The race to be an agent boss
We used seven indicators to identify who has an agent boss mindset. Leaders are ahead on every measure.
Survey Questions:
How familiar are you with the concept of AI agents? (share of respondents who selected “at least familiar with agents”)
How often do you use generative artificial intelligence (AI) for your work? (share of respondents who use AI at least several times a week)
“I trust AI to help me with my most important work tasks” (share of respondents who agree with the statement)
Within the next five years, which of the following could you see becoming part of your job scope or your team’s scope? (share of respondents who selected the activity)
When interacting with AI, which of the following best describes your approach most of the time? (share of respondents who selected treating AI as a thought partner)
“AI can help accelerate my career” (share of respondents who agree with the statement)
On a daily basis, please estimate how much time you save using generative artificial intelligence (AI) at work. (share of respondents who selected an hour or more in time savings)
Last year, employees led the AI wave. This year, it’s flipped. We used seven indicators to identify who has an agent boss mindset—from agent familiarity and regular use of AI to time savings, trust, and the belief that AI is a career accelerator. Leaders are ahead on every measure. 67% of leaders are familiar or extremely familiar with agents, compared to just 40% of employees. Leaders are more likely to expect agent management to be part of their role within the next five years and are already seeing returns—nearly a third say AI saves them over an hour a day. Most importantly, 79% of leaders believe AI will accelerate their careers versus 67% of employees.
What explains the gap? We expect it’s because leaders are the first to feel the pressure to have an AI strategy—and the first held accountable for making it work. They see what’s coming and know they can’t afford to wait. Managing agents also plays to their strengths: delegating, guiding, and stepping in when needed. As one Microsoft researcher puts it, “Working with agents is like onboarding a new team member—you don’t micromanage, but you need informed trust.”
This shift won’t stop at the top. As agents become embedded in day-to-day work, roles across every level and function will evolve. Today, more than 10% of people hired on LinkedIn globally hold job titles that didn’t exist in the year 2000. And by 2030, LinkedIn projects that 70% of the skills used in most jobs today will change, with AI emerging as a catalyst.
For early-career employees, the impact could be significant. One startup in our research skipped hiring a CMO and gave a junior marketer AI to run full-stack campaigns. In Frontier Firms, even entry-level employees are managers from day one—because they’re managing AI. And 83% of global leaders say AI will let employees take on more complex, strategic work earlier in their careers.
The organizations and industries that invest in AI skilling today will be the leaders of tomorrow. AI offers not only new tools for people’s work but also new ways to help people learn almost anything. In fact, one of the top reasons people turn to AI over a colleague in our research was to master a new skill. Today, working without a computer feels unimaginable; tomorrow we’ll feel the same about AI—with every employee using it as instinctively as they use laptops, smartphones, or the internet each day.
Preparing for what’s next is no longer optional. This shift demands honest conversations, intentional communication, and real investment in reskilling. The most forward-looking leaders see their critical role:
47% of leaders list upskilling existing employees as a top workforce strategy for the next 12–18 months.
51% of managers say AI training or upskilling will become a key responsibility for their teams within five years.
35% of managers are considering hiring AI trainers to guide employee adoption in the next 12–18 months.
This shift is unfolding at a moment when multiple forces—from economic uncertainty to automation—are slowing hiring and intensifying competition. 52% of employees, and 57% of leaders, say job security is no longer a given in their industry. And the market is frozen—81% of employees haven’t changed jobs in the past year.
Amid the uncertainty, one signal is clear: AI literacy is now the most in-demand skill of 2025, according to LinkedIn. Also rising are human strengths like conflict mitigation, adaptability, process automation, and innovative thinking—showing that the future belongs to those who can pair deep AI capabilities with the skills machines can’t replicate.
If you have a people problem, you will have an AI problem. As multi-agent systems redefine the workplace, the challenge will be to integrate and manage them securely and effectively. Companies that already know how to enable their human workforce will succeed—breaking down silos, fostering collaboration, and ensuring the entire organization works toward common goals.
2025 will go down as the year the Frontier Firm was born—the moment when companies moved beyond experimenting with AI and began rebuilding around it. Like the digital-native companies of a generation ago, they understand the power of pairing irreplaceable human insight with AI and agents to unlock outsize value.
This transformation is already underway. Org charts are shifting. Labor markets are evolving. New startups are emerging. Some roles are evolving, while others—not even on the radar just a year ago—are being posted and filled. Imagine knowing what you know today just before the internet changed everything. That’s where we are with AI. Knowledge is power, and having it now gives people the agency to lead this moment. The question isn’t if AI will reshape work—it’s how fast we’re willing to move with it.
4
The path forward
For every leader and employee, now is the time to take decisive action. Here’s how to get started.
1. Hire your first digital employees
AI agents are ready to take on a host of tasks traditionally done by humans—from answering support tickets to drafting reports. Start by defining clear roles for which automation adds value, and treat these digital employees like you would any team member: onboard them, assign ownership responsibilities, and measure their performance. This shift isn’t just about efficiency—it’s about building a workforce that blends human creativity with AI’s unique strengths.
2. Set your human-agent ratio
AI-driven efficiency is only half the story. It’s just as vital to invest in the people who will power what comes next. Identify the processes ripe for full automation—as well as those where human-AI collaboration unlocks outsize value. Consider where customers expect a human touch, and where judgment and high-stakes decisions rely on getting the right mix of humans and agents.
Then make it real: Set the expectation that every employee develops AI literacy, shares learnings, and embeds them into everyday work practices; plan for employees to advance their skills as they learn how to develop and manage agents; and create paths for ongoing learning as human-agent teams reshape roles and priorities.
3. Get to broad scale—fast
The time for pilots alone has passed. Real change requires broad adoption and activation at every level of the organization—from senior leaders in every function to the front line. Target high-need areas like operations, customer service, or finance, and identify where AI can drive measurable impact. That might mean boosting revenue, cutting costs, or automating work far from your competitive edge. When you discover value, reinvest to scale further and faster. Scaling AI isn’t a technical challenge, it’s an organizational challenge. Treat it with the same rigor you would apply to any company-wide transformation.
5
Resource guide
These resources—from Microsoft and others—can help everyone accelerate AI and agent adoption, understand the latest research, and build skills and habits for the shift ahead.
Lead
Help your team build the AI habit—and their prompting skills—with The Great Copilot Journey for Copilot Chat (Microsoft)
Track key adoption and deployment milestones with the AI adoption score, a simple and effective way to measure your organization’s adoption of Microsoft 365 Copilot and compare it with like organizations. (Microsoft)
Identify and keep up with the latest technology trends impacting business with Amy Webb’s 2025 Tech Trends Report. (Future Today Strategy Group)
Subscribe to Jared Spataro’s “AI at Work” LinkedIn newsletter, designed to help business leaders decode the latest AI innovation. (Microsoft)
Learn
Check out Conor Grennan’s Generative AI for Professionals course for a helpful overview of the technology, along with a framework for strategically implementing AI at work. (AI Mindset)
Explore Artificial Intelligence for Business courses that help you leverage AI across functions like marketing, finance, operations, and customer service. (LinkedIn)
Review this foundational study of nearly 800 P&G employees to understand the vast opportunity ahead via human-agent teams: The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise (Harvard Business School)
Read Daniel Susskind’s paper What Will Remain for People to Do? for insights on how humans will continue to work alongside AI, even as the technology evolves. (The Knight Institute)
Subscribe to the WorkLab newsletter for actionable AI at Work guidance and the latest Copilot research from Microsoft. (Microsoft)
Do
Take the Career Essentials in Generative AI course for practical, scalable AI skills to lead—not just use—intelligent systems. (Microsoft and LinkedIn)
Follow How to Prompt on LinkedIn to develop your prompting aptitude day by day. (How to Prompt)
Regularly participate in events such as the Microsoft AI Skills Fest to keep abreast of emerging trends and network with AI professionals. (Microsoft)
Stay up to date with Ethan Mollick’s One Useful Thing newsletter—a critical resource for the most important news and research on AI. (One Useful Thing)
1 30% of meetings span multiple time zones and they have been rising steadily with 8-percent point increase since 2021. Full Microsoft 365 telemetry citations are in the methodology section at the end of the report.
2 Frontier Firm employees were defined as those working at companies with org-wide AI deployment, high scores on our six-part AI Maturity Index (covering pace, mindset, investment, adoption, and ROI), active use of agents, plans for moderate or extensive agent integration, and a belief that agents are key to realizing ROI. Results are statistically significant at p < 0.0001.
3 Data reflects the top three workforce strategies leaders say their organization is considering over the next 12–18 months.
4 Top ten roles in consideration include AI Trainer (32%), AI Data Specialist (32%), AI Security Specialist (31%), AI Agent Specialist (30%), AI ROI Analyst (29%), AI Media & Content Manager (29%), AI Finance Strategist (28%), AI Customer Success Lead (28%), AI Business Process Consultant (28%), and Chief AI Officer (27%).
5 Citations are included in the methodology at the end of this report.
6 The company grew out of an agency called Supernatural AI.
7 Fabrizio Dell’Acqua et al., The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise, Harvard Business School Working Paper No. 24-070 (Apr. 4, 2024).
8 Daniel Susskind, What Will Remain for People to Do?, 25-08 Knight First Amend. Inst. (Apr. 7, 2025).
9 The survey question asked, “AI is poised to transform business operations. Over the next 12-18 months, what new roles or responsibilities are your company considering adding to harness AI and prepare for the future?”
AI collaboration
Each step of this report was created in close collaboration with AI. Copilot, along with agents built in Copilot Studio, helped in survey building and data and statistical analysis; narrative building, writing, and editing; the creative development of illustrations and data visuals; and more. All AI-generated work was closely managed, reviewed, and improved upon by humans.
Qualitative Insights
We spoke with economists, futurists, scientists, and academics, and spent time with Microsoft customers to understand their goals, challenges, and current state of AI adoption. We also interviewed 12 AI-native startups across industries and functions—organizations using AI to fundamentally reshape how work gets done, accelerate time to value, and build entirely new company structures. These insights were grounded in and enriched by a broader review of existing literature on AI’s impact on the workplace.
Survey Methodology
The Work Trend Index survey was conducted by an independent research firm, Edelman Data x Intelligence, among 31,000 full-time employed or self-employed knowledge workers across 31 markets between February 6, 2025 and March 24, 2025. This survey was 20 minutes in length and conducted online, in either the English language or translated to local languages across markets. 1,000 full-time workers were surveyed in each market, and global results have been aggregated across all responses to provide an average. In the U.S., an additional sample of 4,500 full-time employed or self-employed knowledge workers was collected across nine sub-regions/metros.
Global markets surveyed include:
Argentina, Australia, Brazil, Canada, China, Colombia, Czech Republic, Finland, France, Germany, Hong Kong, India, Indonesia, Italy, Japan, Malaysia, Mexico, Netherlands, New Zealand, Philippines, Poland, Singapore, South Korea, Spain, Sweden, Switzerland, Taiwan, Thailand, United Kingdom, United States, and Vietnam.
Sub-regions/Metros in the United States surveyed include: Atlanta, Austin, Boston, DC Metro, Houston, New York City, North Carolina, Pittsburgh, and the San Francisco Bay Area.
Audiences mentioned in the report are defined as follows:
Knowledge workers: Those who typically work at a desk (whether in an office or at home). This group includes those who are in person or working remotely in some capacity.
Leaders: Knowledge workers in mid to upper job levels (e.g., SVP, VP, Sr. Director, General Manager, EVP, C-Suite, President, etc.) who have at least some decision-making influence related to hiring, budgeting, employee benefits, internal communications, operations, etc.
Employees: Knowledge workers who are not in mid to upper job levels or have no influence on decision-making related to hiring, budgeting, employee benefits, internal communications, operations, etc.
Managers: Knowledge workers who manage a team or group of employees. Managers can be business decision makers or non-business decision makers.
Frontier Firms: Leaders who say their company has organization-wide deployment of AI and believe their organization is a leader in actively investing in AI, and is measuring ROI on these investments. They say they have seen some ROI from implementation of AI and believe it is critical to their long-term success as an organization. They believe agents will be key to realizing a return on their company’s AI investments. These leaders say they work at organizations that are currently using agents or other AI tools that bring previously outsourced skill sets in-house, or are using multi-agent systems that collaborate to achieve a goal or execute complex workflows. Their company plans to moderately or extensively incorporate agents into its AI strategy over the next 12–18 months.
Microsoft 365 Telemetry
All data is based on aggregated and anonymized Microsoft 365 productivity signals, ending February 15, 2025. Data excludes education (Edu) and European Union (EU) tenants.
Interruptions
Employees are interrupted every two minutes during core work hours—275 times a day—by meetings, emails, or chats.
Calculated as a rolling 28-day sum of pings (meeting invites, emails, chats) per unique user per workday. The two-minute figure reflects the average time between pings during an 8-hour workday. 275 is based on the 24-hour day. Based on the top 20% of users by ping volume received.Last-Minute PowerPoint Edits
Edits in PowerPoint spike 122% in the final 10 minutes before a meeting.
Calculated as a rolling 28-day sum of PowerPoint view and edit actions per meeting participant, measured across fixed time windows before meetings.Ad Hoc Meetings
60% of meetings are unscheduled or ad hoc.
Based on a rolling 28-day volume of unique meetings per user per workday. Represents the top 20% of users by meeting volume.After-Hours Chats
Chats sent outside the standard 9-to-5 workday are up 15% year over year, with an average of 58 messages per user now arriving before or after hours.
Calculated as a rolling 28-day sum of chats sent outside of Monday–Friday, 9 a.m.–5 p.m.Late-Night Meetings & Cross-Time Zone Work
Meetings starting after 8 p.m. are up 16% year over year, driven by an increase in cross–time zone collaboration. 30% of meetings now span multiple time zones—a figure that has risen 8 percentage points since 2021.
Measured as a rolling 28-day sum of meetings starting between 8 p.m. and 11:59 p.m., adjusted for each participant’s local time.
LinkedIn Hiring and Labor Trends
LinkedIn’s AI Startup Talent Trends Analysis explores global workforce and talent trends among AI startups, using a sample of companies identified in the PitchBook AI & ML Ecosystem Map, along with well established companies (“Big Tech”). The metrics are derived from LinkedIn profile data, capturing employee growth, AI talent concentration, and talent flows over the past 12 months.
Metrics
Employee Growth: The percentage change in the number of employees at each company over the last 12 months, as reported on LinkedIn. This metric reflects hiring momentum and company expansion.
AI Talent Ratio: The share of employees at a company classified as AI Talent, defined as individuals with either (a) more than two AI-related skills listed on their LinkedIn profiles, or (b) job titles indicating core AI technical roles (e.g., Machine Learning Engineer, AI Researcher).
Most Departures To / Most Hires From: Based on LinkedIn job transition data over the past 12 months, this metric identifies the most common destination companies for employees who left, and the most common origin companies for new hires. These flows highlight competitive dynamics and talent mobility across the ecosystem.
