What 1,179 Global Professionals Told Us About Culture, Training, and the AI Frontier
Three out of four professionals now reach for AI at least once a week. The question isn't whether AI has entered the workplace. The question is what it's actually doing once it gets there.
AI is already helping people save time and perform better. Across the workforce, employees are using AI to write first drafts, summarize meetings, translate messages, analyze information, prepare presentations, and organize ideas. For many people, these tools are reducing repetitive work and making it easier to move from a blank page to a usable starting point.
That is a real advantage.
In RW3 CultureWizard’s High Performing Teams research, 76% of professionals said they use AI at least weekly. Outside research shows the same broad shift. Glean’s 2026 Work AI Index found that 87% of digital workers use AI at work, and many say it saves them significant time. SHRM’s 2026 workplace AI research found that among workers who use AI, 68% reported improved work efficiency and 63% reported improved work quality.
So the first part of the story is clear. AI can help people work faster and, in many cases, produce stronger work. But that is not the whole story.
Faster Alone, Slower Together
When individual productivity rises, teams still must figure out how that work fits together. They have to decide what needs to be checked, what needs to be disclosed, who owns the final product, and how to handle work that looks polished but may still need human judgment.
That is where friction begins.
By friction, we mean the places where work starts to drag. It can be confusion, rework, mistrust, uneven standards, or unclear expectations. In an AI-enabled workplace, friction may show up when one person uses AI heavily, and another avoids it. It may happen when a manager cannot tell whether an AI-generated answer has been verified. It may happen when a colleague receives a polished draft but has to spend time correcting the logic, tone, or facts.
RW3’s research found that 95% of AI users report at least one form of team friction connected to AI use. That does not mean AI is failing. It means the workforce is moving quickly, while team norms are still catching up. This is one of the biggest leadership challenges in the AI era.
A tool can make one person faster and still create challenges for the group. AI can save time on a first draft, while adding time for review. It can help someone organize ideas, while making it harder for others to know where the thinking came from. It can produce a confident answer, even when the facts or context need checking.
Where the Gains Get Lost
Glean’s 2026 research helps explain this gap. Digital workers reported that AI saves them time, yet only 13% said their organization is performing significantly better because of AI. That finding matters. It shows that individual productivity does not automatically become team performance.
The Rules AI Can't See
For teams, the missing link is often cultural. Every team runs on unwritten rules: how people disagree, build trust, show respect, and read what is left unsaid. Those rules differ from person to person and place to place. AI does not understand any of that. When it smooths communication into one confident, standardized style, it can flatten the nuance that holds a global team together, and small misunderstandings start to add up.
AI can draft the email, but someone still has to decide whether the tone fits the relationship. AI can summarize the meeting, but someone still has to notice what was implied, softened, or left unsaid. AI can generate a recommendation, but someone still has to test the assumptions. AI can move work forward, but it does not remove the need for judgment.
In fact, AI may make judgment more important.
Glean calls some of this hidden effort “botsitting.” It is the time people spend feeding AI the right context, checking its answers, correcting mistakes, and making the output usable. BCG’s 2026 research also found that many workers are spending more time managing and directing AI than doing the work itself.
That is a real workforce issue. It changes how people spend their time and how teams define quality.
More Than Tool Skills
This is where learning and culture intersect.
If we only train people on how to prompt, we miss the larger shift. Teams need more than tool skills. They need shared norms. They need to know when AI use is appropriate, when it should be disclosed, what must be verified, and who is accountable for the final product.
They also need managers who can model responsible use and create space for people to ask questions without embarrassment.
That last point is especially important. Microsoft’s 2026 Work Trend Index found that AI impact is strongly connected to the environment around the worker, including culture, manager modeling, experimentation, and talent practices. In plain terms, AI works better when the team has the trust and structure to use it well.
The organizations that benefit most from AI will not simply be the ones with the most tools. They will be the ones that help people use AI thoughtfully, openly, and together.
AI can help people save time and perform better. Teams determine whether those gains turn into stronger collaboration, better decisions, and higher performance. Learn what makes a High-Performing team with our case study:
