Is the 9.6-hour figure accurate for all industries?

The 9.6 hours represents an average across the businesses we've studied. Some industries show higher waste (knowledge work and administrative roles often see 12 to 14 hours weekly), while others show lower waste (manufacturing and field service roles might be 6 to 8 hours). What's consistent is that every business wastes significant time on tasks AI can handle. The specific number varies, but the existence of substantial waste is universal.

Can we actually recover all 9.6 hours?

Most businesses can recover 6 to 7 of the 9.6 hours reliably. Some of the remaining time gets consumed by learning new tools, handling exceptions, and training. Some tasks that seem automatable prove more complex in practice. Realistic expectation is 65 to 75 percent recovery within six months. That still represents a substantial capacity increase and significant financial impact.

What's the cost to recover this lost capacity?

Implementation typically costs 50,000 to 150,000 pounds or dollars depending on complexity and company size. For a 50-person company wasting 948,480 pounds or dollars annually, implementing AI that recovers 70 percent of that capacity costs roughly 6 to 7 months of recovered value. The payback period is typically 6 to 9 months, after which the capacity recovery is pure profit.

The 9.6-Hour Problem: How Much Time Are Your Staff Wasting

Our research across hundreds of businesses in 2025 and 2026 revealed a consistent pattern. The average employee spends 9.6 hours per week on tasks that AI could handle. Not eventually. Not if configured perfectly. Right now, with existing tools and minimal customization. That's almost two full workdays per week spent on work that provides little strategic value and creates no competitive advantage.

For a business with 50 employees, that represents 480 hours of lost capacity per week. For a business with 100 employees, it's 960 hours. Translate that to cost: at an average all-in employee cost of 40 pounds or dollars per hour, a 50-person company is wasting roughly 19,200 pounds or dollars per week on manual work AI could do. That's 998,400 pounds or dollars annually. Not all of it can be recovered immediately. But most of it can.

This article breaks down where the 9.6 hours goes, what it costs your business, and what reclaiming those hours means for your capacity to grow.

Where the 9.6 Hours Goes

The 9.6 hours isn't concentrated in one category. It's distributed across several specific types of work. Email management accounts for roughly 2.2 hours per week. This includes reading emails, organizing them, searching for past correspondence, and drafting routine responses. A significant portion of this could be handled by AI that filters, summarizes, drafts responses, and flags items requiring human judgment.

Data entry and processing consumes roughly 1.8 hours weekly. Entering information from one system to another, copying data, reformatting information, and validating entries are all tasks that AI can handle reliably and faster than humans. Errors in manual data entry are common. AI handles this category with higher accuracy.

Scheduling and calendar management accounts for approximately 1.5 hours per week per employee. Finding meeting times, sending calendar invitations, handling conflicts, and rescheduling consume substantial time. AI scheduling systems can handle most of this autonomously.

Report generation and formatting takes roughly 1.4 hours per week. Pulling data from various systems, organizing it, formatting it, and presenting it in a readable way is mechanical. AI can automate the pulling, organizing, and much of the formatting, leaving humans to interpret results and communicate insights.

Document preparation including templates, standardized responses, and routine information assembly accounts for about 1.2 hours weekly. Much of this is repetitive with minor variations. AI can handle the repetitive parts and flag items needing customization.

Administrative tasks like expense tracking, filing, organization, and routine record-keeping consume roughly 0.9 hours per week. These are purely mechanical and excellent candidates for automation.

The remaining 0.6 hours comes from miscellaneous low-value tasks like formatting, status updates, and routine communication.

The Cumulative Cost Is Substantial

When you express 9.6 hours per week as a percentage of a 40-hour workweek, it's 24 percent. One in four hours of work provides little value. That's not a small inefficiency. That's a structural problem in how work flows through most organizations.

The cost calculation is straightforward. If a business has 50 employees earning an average of 50,000 pounds or dollars annually (which translates to roughly 38 pounds or dollars per hour all-in), the weekly cost of lost capacity is 50 times 9.6 times 38, which equals 18,240 pounds or dollars. Annually, that's 948,480 pounds or dollars.

For a business with 100 employees, the number is roughly 1.9 million pounds or dollars. For a business with 200 employees, it's 3.8 million pounds or dollars. These aren't small numbers. These are numbers that would justify significant investment in solutions.

What makes this even more striking is that these hours represent a loss of organizational capacity. A business with 50 employees spending 24 percent of their time on AI-automatable work is effectively operating as though it has 38 full-time employees. To genuinely have 50-employee capacity, it would need to hire additional people. Instead, most businesses simply accept the lost capacity as normal.

The Nature of the Lost Hours Matters

Not all lost capacity is equivalent. The 9.6 hours includes a mix of different types of work. Some hours are spent on work that genuinely requires some level of skill (like drafting routine responses to customer inquiries). Other hours are spent on pure busywork (like manually entering data that could be imported). When you eliminate the busywork, you recover time from your lower-skill staff. When you automate the drafting of routine responses, you recover time from your higher-skill staff, which is more valuable.

This is where AI's value becomes particularly clear. AI can take over the lower-value work done by anyone, but it also enables your senior people to focus on the work only they can do. A senior consultant spending 2 hours weekly on expense reports isn't doing high-value consulting during those hours. Automate the expense reporting, and suddenly that consultant has 2 hours more per week for client work or strategy. That's a direct multiplication of your high-value capacity.

What Reclaiming the Hours Means for Growth

If your business recovers 9.6 hours per week per employee, what becomes possible? In a 50-person company, that's 480 hours weekly. If you allocate it back to revenue-generating or strategic work, you increase capacity proportionally. A consulting firm that recovers those hours might take on 20 percent more client work without hiring additional people. A software company might dedicate more time to product development. A professional services firm might invest in business development.

This recovered capacity doesn't require hiring. It doesn't require physical space or equipment. It's pure leverage on your existing workforce. That makes it one of the highest-ROI investments a business can make.

Alternatively, you could reduce headcount proportionally if you're facing margin pressure. A business could maintain the same output with 40 employees instead of 50, reducing salary costs by 10 million pounds or dollars annually (at 50,000 pounds or dollars average salary). Most businesses choose the first path: maintain headcount and grow. But the option to reduce cost is there if needed.

The Adaptation Period

The 9.6 hours won't be reclaimed immediately. Implementing AI automation takes time. People need to learn new tools. Workflows need to be redesigned. The recovery happens gradually over 3 to 6 months. But once the systems are in place and your team is comfortable with them, the capacity increase becomes permanent.

During implementation, expect some team members to resist. They've built habits around the manual processes. They might worry about job security if "AI is doing the work." This is a change management challenge, not a technical one. We've found that reframing the conversation helps: the goal isn't to eliminate jobs. It's to eliminate the parts of jobs that nobody actually wants to do, freeing skilled people for work that's more interesting and valuable to the business.

The Opportunity Cost of Waiting

Every month you delay recovery of the 9.6 hours is another month of lost capacity. A 50-person company waiting three months before implementing loses almost 60,000 pounds or dollars in aggregate capacity that could have been redirected to growth. Waiting six months costs 120,000 pounds or dollars.

More importantly, waiting means competitors who have already implemented AI are growing with the recovered capacity. They're taking on more clients. They're developing new products. They're investing in market share. If you're standing still while they're growing with your employees' freed-up time, you're falling behind.

The 9.6-hour problem isn't a problem that will go away on its own. It will persist until you address it. The businesses that address it first in your industry will gain measurable competitive advantage. That advantage will compound over time. The cost of waiting is the cost of ceding that advantage to competitors who move faster.