AI can help businesses work faster, analyze more information, and reach answers in seconds. But could removing too much friction from the way people work also remove something valuable?
Writing in Psychology Today, John Nosta argues that the struggle involved in solving difficult problems can itself contribute to innovation. Uncertainty, failed attempts, and the process of working toward an answer can generate ideas and insights that might never emerge if AI simply provides the destination.
For MSPs helping customers adopt AI, that raises an important consideration: efficiency matters, but so does preserving the human thinking that drives discovery.
1. Don’t Measure AI Success Only by Speed
AI’s ability to accelerate work is valuable, but completing a task faster doesn’t necessarily mean producing a better business outcome.
For MSPs, the conversation should extend beyond how many hours AI can save to whether it improves quality, productivity, customer experience, and decision-making.
MSP Action: Help customers measure AI initiatives against quality, business outcomes, and innovation—not simply time saved.
2. Know Which Friction Is Worth Removing
Nosta describes “productive cognitive friction” as the uncertainty and struggle that can generate new thinking during problem-solving.
Automation should eliminate unnecessary repetitive work without automatically removing every opportunity for employees to think through difficult problems.
MSP Action: Identify repetitive processes that benefit from automation while preserving human involvement where judgment and exploration create value.
3. Use AI to Support Thinking, Not Replace It
AI can help employees research, analyze information, brainstorm ideas, and evaluate possibilities. But people still need to understand how those outputs relate to business goals, customers, and real-world decisions.
That distinction can help organizations capture AI’s efficiency without becoming overly dependent on its answers.
MSP Action: Encourage workflows where AI supports research, analysis, and ideation while people remain responsible for interpretation and decisions.
4. Keep Human Expertise in the Loop
As organizations become more dependent on AI-generated output, maintaining internal knowledge becomes increasingly important.
Nosta raises the concern that organizations could accumulate results without developing the deeper understanding that traditionally emerges through the process of reaching them.
MSP Action: Design AI-enabled workflows that preserve opportunities for employees to develop expertise, validate results, and challenge AI-generated conclusions.
5. Make AI Strategy About More Than Automation
The greatest value of AI may not come from automating as much work as possible. It may come from combining machine speed with human creativity, context, experience, and judgment.
MSPs can help customers determine where automation makes sense and where human participation remains essential.
MSP Action: Build customer AI roadmaps around augmentation as well as automation, identifying where technology and human expertise work best together.
The MSP Opportunity
As AI becomes embedded across the workplace, MSPs are increasingly helping customers decide not only which technologies to adopt, but how those technologies should change the way people work.
That creates an opportunity to guide customers toward a more deliberate approach: use AI to remove low-value friction and create capacity while preserving the curiosity, judgment, expertise, and problem-solving that can turn greater efficiency into genuine innovation.