If AI could do one thing to improve my workday, it would be to give me confidence that I am using the right tools for the right job at the right time…and proactively suggest the right tool to use for the task that I am working on.
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The Human + Technology Experience Index
How cognitive load is shaping our experiences at workGood morning. You’re on your first cup of coffee, but six windows are already open on your laptop. And all the tabs you didn’t close the day before are right back with you. Your work is spread across all of them. Unread message bubbles greet you on Gmail, Slack, Jira. It’s a lot to keep track of, but professionals everywhere have adapted to this. It’s a regular day.
Our data show that this modern setup, our wide palette of tools, is effective. And people like using their tools. Workers who use more tools report higher productivity, stronger impact, and a greater sense of accomplishment.
But there’s a tax to this setup too. With so many technology options available, the transition points between people and their tools have multiplied. People are increasingly expected to serve as the integration layer across many tools, while keeping up with regular, person-to-person collaboration. Productivity is increasing, but so is the cognitive load required to sustain it.
The Human + Technology Experience Index is our way of measuring that tradeoff.
THE DATA
01
People Love Their Tools
The biggest surprise in our data was that it didn’t support the usual “tool overload” complaint. People who use more tools actually feel more productive, even under heavy workloads or tight deadlines.
This suggests that modern tools are doing their job: helping people get work done.
People say more tools means more success
Professionals who reported using more tools in their day-to-day were more likely to say that those tools were helpful across key metrics of success at work.
For the large majority of professionals, AI now sits alongside their tools as a regular source of day-to-day support.
83of professionals say AI helps me feel more accomplished at the end of the day
People who use the most tools at work also report the greatest help from AI. Here we get an early picture of what a stronger human-technology partnership looks like.
People believe AI helps across work tasks
The more tools people use during the week, the more they say AI helps across tasks.
| AI helps me… | All respondents | 3–5 tools | 6–10 tools | 11–15 tools | |||
|---|---|---|---|---|---|---|---|
| % based on tool use | % based on tool use | Change from baseline | % based on tool use | Change from baseline | % based on tool use | Change from baseline | |
| Manage project plans and timelines | 70% | 66% | -4pp | 71% | +1pp | 81% | +11pp |
| Analyze information or data | 79% | 75% | -4pp | 79% | +1pp | 89% | +11pp |
| Prioritize work and set deadlines | 69% | 66% | -3pp | 69% | 0pp | 75% | +6pp |
| Collaborate with coworkers | 70% | 64% | -6pp | 72% | +2pp | 79% | +10pp |
| Track progress of tasks/projects | 70% | 65% | -5pp | 72% | +2pp | 81% | +10pp |
| Write and reply to emails | 71% | 65% | -6pp | 75% | +3pp | 78% | +7pp |
| Search across documents/tools/messages | 78% | 73% | -5pp | 79% | +1pp | 89% | +11pp |
| Brainstorm ideas | 73% | 69% | -4pp | 74% | +2pp | 78% | +5pp |
| Document notes/updates/decisions | 76% | 71% | -5pp | 78% | +2pp | 81% | +5pp |
02
Figuring Out How to Work is Exhausting
Cognitive load, not tool count, appears to be the real challenge of modern work. Cognitive load shows up the moment “how to work” starts to feel like its own job: choosing tools, hunting for information, and stitching everything together before the real work can begin. It’s not the core tasks that slow people down; it’s navigating the seams in between.
The data here makes that burden visible.
How we’re defining cognitive load in the workplace
Cognitive load isn’t driven by how many tools someone uses. It’s driven by how many tools they must navigate to complete a task and how well those tools work together. The more systems a person has to move between, and the more manual effort required to connect them, the higher the cognitive load. In the following section, we compare workers in low- and high-cognitive-load environments to understand how these differences shape work experiences and outcomes.
Low cognitive load
For these workers, their digital work environments are relatively straightforward. Most tasks have only one appropriate tool.
High cognitive load
For these workers, their digital environments are complex, with a great deal of fragmentation between tools and more ambiguity on the appropriate tool for each task.
Tool integration, not volume, is the challenge
When tools don’t work together, people bear the burden of integration.
Most frustrating part of using multiple tools
- 68%say too many tools exist for the same task
- 58%say tools don’t always integrate well with one another
- 56%say deciding how to do my work takes as much effort as doing the work itself
- 55%say important information is spread across too many systems
- 50%say it can be unclear which tool to use for certain work
Fragmented tasks create just as much work as the work itself
When multiple tools exist for a single task, figuring out which to use becomes its own burden.
In fact, the cognitive load brought on by this kind of fragmentation changes both people’s experience of daily tasks and their optimism toward technology.
Cognitive load makes most work harder
Across top workplace productivity challenges, those in high cognitive load environments report greater difficulty.
People working under…
Cognitive load influences people’s perception of AI
People in higher cognitive load work environments are more critical of AI.
People working under…
AI should prioritize tasks intelligently, adjusting schedules dynamically based on deadlines, workload, and real-time changes.
03
How People Make It Work
When tools don’t work the way people do, people don’t stop working. They create workarounds. In scenarios where multiple tools exist for the same job, people will default to the one they are most familiar with. When a company doesn’t provide tools that meet their needs, people will find their own. Especially when it comes to AI.
People go with the tool that's most familiar
Organizations may provide multiple tools for a task, but in practice, people often use only a fraction of them.
61of people prefer a familiar tool even when a better one exists
People build their own tech stacks
When official tools do not fit how work happens, people don’t stop working; they reroute around the friction.
This does not mean workers are rejecting company tools. It means they are trying to make work easier. The reasons most commonly come down to rebalancing their cognitive load.
Survey results
48%
say half of the tools they use are personally selected
65%
of knowledge workers seek unofficial AI tools
72%
of workers who use primarily company tools still seek unofficial AI tools
The tools I use at work are…
- 10.3%All mine
- 13.8%Mostly mine
- 23.0%Even mix
- 27.4%Mostly company
- 25.5%All company
Why people choose to not use company tools
Supporting data
- 35%say “they don’t fit my workflow”
- 28%say “I wasn’t trained on them”
- 25%say “I don’t know how to use them”
- 23%say “I don’t know when to use them”
- 21%say “I don’t know why they exist”
Why people choose their own tools over company tools
Easier to use is the top reason
- 55%say personally selected tools are easier to use
- 51%say personally selected tools have better features
- 45%say personally selected tools work better with other tools
- 26%say company tools don’t meet needs
- 25%say company tools are too complex
04
Where Companies Need to Focus
Everything gets harder when people have to negotiate the decision friction of a fragmented tool stack.
Today, employees are the integration layer: they’re the ones connecting tools, tracking work across apps, and remembering where everything lives. The data suggests AI creates the most value when it takes on that integration work—carrying context, connecting workflows, and reducing tool indecision—rather than adding yet another destination.
If they want to prevent widespread burnout, workplace leaders need to obsess about reducing the cognitive load people experience when navigating work across people and tools.
AI should exist to remove friction from daily work, making the workday calmer, more efficient, and more focused on human strengths rather than repetitive effort.
Use AI to lift the burden of cognitive load for employees
Focus on the biggest workplace productivity challenges and adopt AI that fits what people need.
Where and what AI needs to deliver
Top productivity challenges
What workers need most
Why current tools fall short
What AI needs to do
Coordinating with others
Tools that connect people, tasks, and context
Tools don’t integrate well with each other
Connect across workflows
Gathering information
Faster access to the right information
Information is spread across too many systems
Connect across data sources
Switching between tasks
Consistent context across work
Tools create workflow and information siloes
Preserve context across tasks and tools
Tracking progress
Clear visibility across projects and updates
Unclear which tool to use or view
Create centralized and predictable visibility
Choosing tools / resources
Clarity on where work should happen
Tools compete for each task
Surface the right tool at the right time
Learning new tools
Better onboarding and in-context learning
Learning curve is too steep
Lower barrier to value with intuitive UX
Adopting new tools
Gradual rollout and embedded guidance
Organizations introduce tools faster than people can learn them
Offer proactive assistance at the moment of need
AI is the most flexible technology we’ve ever had. But it’s only as a good as its ability to integrate into how people want to work.
We all have the responsibility to choose thoughtfully and build toward a world where the technology we use doesn’t burn people out, but helps them shine brighter.
See what's possible with Superhuman Go.