Key Takeaways
- 78% of executives reported using AI tools in 2025, up from 51% in 2023 - a 53% increase in two years - yet only 26% fully trust the output (Prialto 2025 Executive Productivity Report, n=508 business leaders)
- AI users save an average of 7.5 hours per week - equivalent to one full workday - worth roughly £14,000 per employee annually in recovered productivity (LSE / Protiviti, survey of ~3,000 workers and 240 executives)
- Executives spend 20-30% of their time on administrative tasks, and less than 10% on long-term strategy; a trusted EA can recover 10+ hours per week and boost executive output by 15-20% (McKinsey; Boldly EA benchmarks)
- Early AI adopters report $3.70 in value for every $1 invested; top performers achieve $10.30 per dollar - yet fewer than 30% of AI leaders say their CEOs are satisfied with ROI despite average enterprise spend of $1.9 million in 2024 (Larridin; Gartner)
- 66% of organizations reported achieving productivity and efficiency gains from enterprise AI in 2026, up from 25% reporting a transformative effect - double the prior year's rate (Deloitte, State of AI in the Enterprise 2026, n=3,235 leaders)
Executive productivity tools statistics matter more right now than they did even two years ago because the tooling landscape changed faster than most organizations could absorb. AI assistants, scheduling automation, and delegation platforms moved from pilot programs to mainstream use between 2023 and 2025, and the adoption data now show real divergence between companies that integrated these tools deliberately and those that did not.
This article draws from primary research published between 2022 and 2026, including the Prialto 2025 Executive Productivity Report (n=508 business leaders), Microsoft's 2024 and 2025 Work Trend Index (n=31,000 workers across 31 countries), Deloitte's State of AI in the Enterprise 2026 (n=3,235 leaders), McKinsey time management research, Harvard Business Review CEO time studies, the LSE/Protiviti AI productivity report, Gartner CIO and technology surveys, and Asana's State of AI at Work 2025. Where vendor-commissioned surveys are cited, that context is noted.
Executive adoption of productivity and AI tools
The headline number from the Prialto 2025 Executive Productivity Report is striking: 78% of executives reported using AI tools in 2025, up from 51% in 2023. That 27-percentage-point jump happened in two years and represents a structural shift, not incremental adoption. The same report found that only 26% of those executives fully trust the output of AI tools - a trust gap that shapes how deeply these tools are embedded in actual decision-making versus lower-stakes tasks like drafting emails or summarizing documents.
Formal productivity system usage followed a volatile path. In 2022, 67% of executives reported using a formal productivity system. That figure dropped to 35% in 2023, then rebounded to 64% in 2025. The Prialto researchers attribute the 2023 dip to pandemic-era disruption and productivity theater finally burning itself out, with the recovery reflecting genuine adoption of more structured systems as workloads stabilized.
Microsoft and LinkedIn's 2024 Work Trend Index, drawing on data from 31,000 respondents across 31 countries plus Microsoft 365 productivity signals, found that 75% of knowledge workers now use AI at work. What stands out in the executive segment is that leaders use AI at a 33% rate - double the 16% rate of individual contributors, according to St. Louis Federal Reserve workforce data from 2025. That pattern reverses the typical technology adoption curve, where adoption usually starts at the individual contributor level and spreads upward.
Executive and knowledge worker AI tool adoption rates (2023-2025)
| Group | Adoption rate | Year | Source |
|---|---|---|---|
| Executives using AI tools | 78% | 2025 | Prialto |
| Executives using AI tools | 51% | 2023 | Prialto |
| Knowledge workers using AI at work | 75% | 2024 | Microsoft / LinkedIn WTI |
| Leaders vs. individual contributors (AI use rate) | 33% vs. 16% | 2025 | St. Louis Federal Reserve |
| C-suite executives reporting high AI comfort | 65% | 2025 | Salesforce |
| Executives reporting AI benefit | 97% | 2025 | Salesforce / Writer |
| CIOs planning increased AI/GenAI investment | 80%+ | 2025 | Gartner CIO Survey |
Gartner's 2025 CIO and Technology Executive Survey found that more than 80% of CIOs polled expect to increase AI and GenAI investments in 2025. Separately, Salesforce's C-Suite Agentic AI Perspectives report found that 75% of executives expect AI agents will be part of their company's C-suite within five years, and 95% say AI is already changing roles and team structures at their organizations.
For broader context on how AI tools adoption tracks across the workforce, the companion data at AI productivity tools adoption statistics covers the full adoption curve.
Hours saved: what the time data shows
The practical case for executive productivity tools rests on time recovery, and the research on hours saved is more consistent than most adoption studies. The LSE/Protiviti report - "Bridging the Generational AI Gap," based on a survey of approximately 3,000 workers and 240 executives globally - found that AI users save an average of 7.5 hours per week, equivalent to one full workday per week, worth roughly £14,000 per employee per year in recovered productivity.
That figure applies broadly, not just to executives. For the executive population specifically, the St. Louis Federal Reserve's 2025 generative AI workforce data found that executives use AI for about 1.5 hours per week on average - less intensive than the general workforce. The implication is that the productivity gains for executives come more from leverage (AI doing work on their behalf) than from the executives themselves spending hours prompting tools.
Microsoft's own user data for 365 Copilot found that users saved approximately 9 hours per month across email drafting, meeting summaries, and report generation - roughly 2.25 hours per week. The top 5% of Microsoft Teams users saved a full workday in a single month by using AI to summarize meetings alone. A separate UK government trial involving 20,000 civil servants using Copilot over three months found a saving of 26 minutes per day, or about 2.2 hours per week.
Hours saved per week by productivity tool type (2024-2025)
| Tool / intervention | Hours saved per week | Basis | Source |
|---|---|---|---|
| AI tools (average across all users) | 7.5 hrs | LSE / Protiviti study (~3,000 workers) | LSE / Protiviti, 2025 |
| Microsoft 365 Copilot users | ~2.25 hrs | 9 hrs/month across email, meetings, reports | Forrester / Microsoft, 2025 |
| Government workers (Copilot trial) | ~2.2 hrs | 26 min/day, 20,000-person trial | UK Government / Microsoft, 2025 |
| Meeting summarization (top 5% Teams users) | ~8 hrs/month | Best-case AI meeting summary usage | Microsoft WTI, 2024 |
| Executive assistant support | 10+ hrs | Calendar, inbox, prep, travel, coordination | Workmate analysis |
Microsoft's 2024 Work Trend Index found that 90% of AI users say AI helps them save time and 85% say it helps them focus on more important work. Those self-reported figures should be read alongside the harder time-saving data rather than as substitutes for it.
Where executive time actually goes
McKinsey's research on executive time management found that only 9% of executives are "very satisfied" with how they allocate their time. Fewer than half are "somewhat satisfied." Roughly one-third are "actively dissatisfied." Only 52% of executives say how they spend their time largely matches their organization's strategic priorities - meaning nearly half spend the majority of their time on work that is not their highest contribution.
The McKinsey finding that receives the most citation: CEOs spend less than 10% of their time on long-term strategy. The Asana Anatomy of Work Index puts the workforce-wide version of this problem in sharper relief: workers spend 60% of their day on coordination work (meetings, status updates, approvals), leaving only 13% for strategic planning and 27% for skill-based execution. McKinsey separately estimates that 57% of U.S. work hours could be automated with technologies that already exist.
Porter and Nohria's landmark HBR study tracking 27 CEOs over 13 weeks each - representing more than 60,000 hours of time data - found that CEOs in the highest-satisfaction group spend 34% of time with external stakeholders, 39% in internal meetings, and 24% working alone. The study found that unplanned time and reactive work were the chief destroyers of strategic output.
How executives spend their time (current benchmarks)
| Activity | Share of workweek | Notes | Source |
|---|---|---|---|
| Administrative tasks | 20-30% | Could be delegated | Prialto, 2025 |
| Meetings (exec level) | 35-45% | 19-23 hrs/week | HBR / Flowtrace, 2025 |
| Long-term strategy | Under 10% | McKinsey benchmark | McKinsey |
| Work that matches strategic priorities | 52% say "yes" | 48% say allocation is misaligned | McKinsey |
| Coordination / status work (all workers) | 60% | Leaves 13% for strategic work | Asana Anatomy of Work |
| Hours on admin tasks (SME owners/execs) | 16 hrs/week | Close to half the working week | Time Etc research |
For more on how CEO time allocation compares to best-practice models, the detailed breakdown is at CEO time management statistics and calendar pattern data at CEO calendar management statistics.
Top productivity tool categories for executives
The Prialto 2025 research found that 60.6% of executives say they are more likely to choose tools with advertised AI functionality. But the category breakdown matters: not all productivity tools carry equal weight in the executive time recovery calculation.
Meeting management tools address the single largest time drain for most executives. Executives spend 19-23 hours per week in meetings, and nearly half of that time is judged unproductive by HBR's senior manager surveys. Fellow.ai's State of Meetings 2024 report found that 67% of meetings are considered failures by executives. A Harvard Business Review case study found that a single weekly executive meeting cost one large organization 300,000 person-hours per year across everyone who prepared for, attended, and followed up on it.
AI writing and summarization tools have the clearest measurable ROI at the executive level. Meeting summaries, email drafting, and document generation are high frequency, low strategic value tasks that consume disproportionate executive attention. Harvard Business School's 2023-2024 study found that AI users completed comparable tasks 25.1% faster with 40%+ higher quality output - the combination of speed and quality improvement being more unusual than either metric alone.
Top productivity tool categories and executive impact
| Tool category | Primary time saved | Adoption signal | Source |
|---|---|---|---|
| AI writing / meeting summarization | 2-9 hrs/week depending on intensity | 78% exec AI use (Prialto) | Prialto; Microsoft |
| Calendar / scheduling automation | 1-3 hrs/week | Part of EA-equivalent savings | Workmate analysis |
| Project management platforms | Varies | 87% report productivity link | Asana ROI Report, 2025 |
| Executive assistant (human or AI-augmented) | 10+ hrs/week | EA saves 15-20% of exec output | Boldly benchmarks |
| AI agents (workflow automation) | Early stage | 50% orgs already using agents | Microsoft WTI, 2025 |
| Work management platforms | Cost savings | 29% report cost reduction; 39% at 5+ years use | Asana ROI Report, 2025 |
Microsoft's 2025 Work Trend Index found that 50% of organizations are already using AI agents to automate workstreams for entire teams, and 82% plan to expand workforce capacity through agents within 12-18 months. Meetings, email, and chat still consume 57% of work time for the average knowledge worker, interrupted every two minutes during core hours, which explains why the tools with the clearest productivity ROI are those that compress or eliminate high-frequency communication overhead.
Delegation and executive assistant productivity impact
Prialto's 2025 research found that executives spend 20-30% of their time on administrative tasks - often 2 or more hours per day, equivalent to 40 hours per month - on work that falls below their decision-making threshold. A dedicated executive assistant, whether human or AI-augmented, addresses that drain directly. The itemized savings break down across calendar management (approximately 3 hours per week), inbox triage (approximately 2 hours), meeting preparation and notes (approximately 2 hours), travel and logistics (approximately 1 hour), and project coordination (approximately 1-2 hours) - totaling more than 10 hours per week in conservative estimates, according to Workmate's EA productivity analysis.
Boldly's executive assistant industry benchmarks put the headline impact at 15-20% increase in executive productivity when a high-trust EA relationship is in place. That figure captures both the direct time recovery and the cognitive load reduction from not having to track lower-priority items personally.
Delegation and EA impact on executive productivity (2025)
| Metric | Value | Source |
|---|---|---|
| Hours executives spend on delegable admin per month | ~40 hrs (2+ hrs/day) | Prialto, 2025 |
| Weekly hours recovered by dedicated EA | 10+ hours | Workmate EA analysis |
| Executive productivity increase from trusted EA | 15-20% | Boldly EA benchmarks |
| Executives reporting improved productivity in 2025 | 68% | Prialto, 2025 |
| Executives reporting productivity decline in 2025 | 4% (lowest ever recorded) | Prialto, 2025 |
| Knowledge worker workload delegated to AI today | 27% | Asana State of AI, 2025 |
| Expected AI workload delegation in 3 years | 43% | Asana State of AI, 2025 |
The Asana State of AI at Work 2025 adds a forward-looking dimension: knowledge workers delegate 27% of their workload to AI today, a figure expected to reach 34% within one year and 43% within three years. For executives specifically, 90% of top-tier executive assistants are actively exploring AI integration into their workflows as of 2026, according to Boldly's career update data - meaning the human/AI hybrid model for executive support is already the default trajectory.
Prialto's longitudinal data shows the third consecutive year with stress and administrative work as the top productivity blockers for executives. The 68% who reported improved productivity in 2025, combined with only 4% reporting a decline, suggests that the combination of better delegation structures and AI tooling is producing measurable output at the population level even as individual adoption rates vary.
ROI of executive productivity tools: the financial case
The financial case for executive productivity tools investment is clear in aggregate but mixed in execution. Early AI adopters report $3.70 in value for every $1 invested, with top performers achieving $10.30 per dollar, according to Larridin's State of Enterprise AI 2025 Report. Harvard Business School's controlled study found a 25.1% speed improvement and 40%+ quality improvement for AI-assisted work relative to unassisted work.
The execution gap is significant, though. Gartner's survey of 724 respondents conducted in June through August 2024 found that despite average enterprise AI spend of $1.9 million in 2024, fewer than 30% of AI leaders report their CEOs are satisfied with return on investment. Only 48% of digital initiatives meet or exceed their business outcome targets, per a separate Gartner October 2024 survey. And 42% of companies abandoned most of their AI initiatives in 2024, up from 17% the prior year.
ROI of executive productivity tools and enterprise AI (2024-2025)
| Metric | Value | Source |
|---|---|---|
| ROI for early AI adopters | $3.70 per $1 invested | Larridin, State of Enterprise AI 2025 |
| ROI for top AI performers | $10.30 per $1 invested | Larridin, 2025 |
| Speed improvement (AI-assisted vs. unassisted tasks) | +25.1% | Harvard Business School, 2023-2024 |
| Quality improvement (AI-assisted output) | +40%+ | Harvard Business School, 2023-2024 |
| Average enterprise AI spend | $1.9 million (2024) | Gartner, 2024 |
| CEOs satisfied with AI ROI | Under 30% | Gartner survey (n=724) |
| Digital initiatives meeting business outcome targets | 48% | Gartner, October 2024 |
| Companies that abandoned most AI initiatives in 2024 | 42% | Enterprise AI research |
| Organizations reporting work management platform productivity link | 87% | Asana ROI Report, 2025 |
| Global enterprise AI investment in 2025 | $644 billion | Gartner forecast |
Asana's ROI of Work Management Report 2025 found that 87% of respondents see a direct correlation between using a work management platform and improved productivity. Cost savings follow usage depth: 29% of respondents report cost savings, rising to 39% for those who have used work management platforms for five or more years. That pattern of returns increasing with tenure applies to AI tools as well - organizations still in early adoption stages are drawing returns from the lower end of the distribution.
C-suite AI adoption: the 2025-2026 trajectory
Deloitte's State of AI in the Enterprise 2026, based on 3,235 leaders surveyed in August through September 2025, found that 25% report AI is having a transformative effect on their companies - more than double the prior year. 66% of organizations reported achieving productivity and efficiency gains from enterprise AI. 34% are using AI to deeply transform their business; 37% use it only at a surface level. Worker access to AI rose by 50% in 2025.
The organizational tension is real. Writer's 2025 Enterprise AI Adoption Survey found that 68% of C-suite executives say AI adoption has caused organizational division, and 42% say it is "tearing their companies apart." Full AI implementation jumped from 11% to 42% year-over-year - a 282% increase - while CIO AI budgets nearly doubled. That rapid pace creates integration challenges that slower adoption would not.
C-suite AI adoption trajectory (2024-2026)
| Metric | Value | Source |
|---|---|---|
| C-suite executives reporting high AI comfort | 65% | Salesforce, 2025 |
| Organizations achieving productivity gains from enterprise AI | 66% | Deloitte, 2026 |
| Organizations using AI transformatively | 34% | Deloitte, 2026 |
| Full AI implementation rate (year-over-year change) | 11% to 42% (+282%) | Writer, 2025 |
| C-suite executives saying AI is causing organizational division | 68% | Writer, 2025 |
| Executives expecting AI agents in the C-suite within 5 years | 75% | Salesforce, 2026 |
| Executives saying AI is changing roles and team structures | 95% | Salesforce, 2026 |
| Work decisions made autonomously by agentic AI by 2028 (Gartner prediction) | 15% | Gartner, October 2024 |
Gartner predicts that by 2028, at least 15% of day-to-day work decisions will be made autonomously by agentic AI, up from 0% in 2024. That forecast contextualizes why 75% of executives expect AI agents in their C-suite within five years - the threshold for AI making genuine operational decisions rather than just generating drafts is moving faster than most organizations are planning for.
What the data means for executive teams
The time recovery case holds up across multiple independent sources. AI tools save roughly 7.5 hours per week for the average user. A dedicated EA recovers 10 or more hours. AI writing and meeting summarization add 2-9 hours on top, depending on usage intensity. The gap between all of that and what most executives actually experience comes down to how deeply those tools are embedded in daily workflows versus how many are still sitting in a pilot or onboarding stage.
The ROI gap is not a tool quality problem. Early adopters return $3.70 per dollar invested while 42% of organizations abandoned most AI initiatives in 2024 - same tools, different outcomes. The Asana cost savings data shows returns increasing with years of platform use, and the Gartner finding that fewer than 30% of CEOs are satisfied with AI ROI despite average spend of $1.9 million says the same thing: the implementation work determines the outcome, not the subscription.
The administrative time problem is worth naming directly. McKinsey found that only 52% of executives say their time allocation matches organizational priorities. That 48% gap is not a technology problem. It is a delegation and structure problem. The EA and AI tools data are the solution set, but only if they are actually assigned to that problem rather than used for low-stakes tasks while the executive continues handling scheduling and inbox management personally.
Sources
- Prialto 2025 Executive Productivity Report (n=508 business leaders)
- Microsoft / LinkedIn 2024 Work Trend Index (n=31,000, 31 countries)
- Microsoft 2025 Work Trend Index
- Deloitte State of AI in the Enterprise 2026 (n=3,235 leaders, Aug-Sep 2025)
- McKinsey, "Making Time Management the Organization's Priority"
- McKinsey CEO Priorities Research, 2023-2024
- Porter and Nohria, "How CEOs Manage Time," Harvard Business Review, July-August 2018
- Harvard Business School AI task performance study, 2023-2024
- LSE / Protiviti, "Bridging the Generational AI Gap" (~3,000 workers, 240 executives)
- Gartner 2025 CIO and Technology Executive Survey
- Gartner ROI and digital initiatives survey (n=724, Jun-Aug 2024)
- Gartner strategic technology trends, October 2024
- Asana ROI of Work Management Report 2025
- Asana State of AI at Work 2025
- Asana Anatomy of Work Index
- Larridin State of Enterprise AI 2025 Report
- Writer 2025 Enterprise AI Adoption Survey
- Salesforce C-Suite Agentic AI Perspectives 2025/2026
- St. Louis Federal Reserve, State of Generative AI Adoption 2025
- Fellow.ai State of Meetings 2024
- Forrester Research Microsoft 365 Copilot usage study, 2025
- UK Government / Microsoft Copilot 20,000-person trial, 2025
- Boldly Executive Assistant Industry Benchmarks 2025/2026
- Workmate EA Productivity Analysis