Harnessing Beneficial Friction for AI Adoption

Introduction

Artificial intelligence (AI) is everywhere—powering customer experiences, optimizing operations, and transforming industries. But while it offers speed and efficiency, it also introduces risks that can erode trust and amplify errors.

Here’s the question every business leader should be asking: How can I ensure AI supports smart decisions, not just fast ones?

Enter the concept of beneficial friction—a subtle yet powerful strategy that helps balance AI’s strengths with the wisdom of human oversight. By slowing certain processes just enough, leaders can unlock better decision-making, reduce costly mistakes, and build lasting trust with stakeholders.

Why Beneficial Friction Matters for Leaders

We all love efficiency—who doesn’t? But what happens when speed becomes a liability? Imagine relying on an AI-driven system that processes a loan application in seconds but misses a crucial detail about a customer’s credit history. That’s a recipe for reputational damage.

The key insight from MIT’s Initiative on the Digital Economy (IDE) is that some friction is good for business. Beneficial friction creates deliberate pauses—“speed bumps,” if you will—so teams can validate AI outputs and avoid costly errors.

Think of it this way:

• Accuracy vs. Speed: Beneficial friction allows you to balance precision with efficiency, ensuring the results are both fast and reliable

• Trust Calibration: Pauses build confidence, helping employees and customers trust AI without blindly relying on it.

• Competitive Differentiation: The businesses that integrate friction thoughtfully will stand out by delivering quality outcomes customers can count on.

How to Make Beneficial Friction Work for You

1. Spot the Right Moments for Friction

Not all decisions need speed. The key is identifying the points where slowing down can prevent errors and enhance outcomes. For instance:

• In financial services, AI might flag transactions as potentially fraudulent. Adding a review step ensures critical errors aren’t missed, protecting customer trust.

• In e-commerce, friction during the checkout process—like confirming shipping details—can reduce costly mistakes while reassuring customers.

Ask yourself: Where are the key decision points in my organization’s processes? Which of these could benefit from a slight pause for human oversight?

2. Highlight AI’s Strengths—and Its Flaws

Research from MIT and Accenture reveals an important insight: Transparency about AI’s limitations increases trust. Customers and employees are more likely to trust systems that openly acknowledge their potential for errors than those that present themselves as flawless.

Example:
When generative AI tools like ChatGPT display disclaimers about potential inaccuracies, users proceed more carefully, verifying outputs rather than accepting them at face value. This kind of transparency minimizes risks while fostering confidence in the system.

Actionable Tip: Integrate clear, user-friendly prompts into AI interfaces that explain the system’s strengths and suggest double-checking sensitive outputs.

3. Embrace Human Involvement as a Strength

Here’s a surprising finding: Consumers are willing to pay more for content they know was created or reviewed by a human, even when AI played a role. This “human favouritism” highlights the enduring value of human oversight in AI-driven systems.

Takeaway:
Rather than automating everything, position your business as human-centred. Promote your AI systems as tools that enhance human capabilities—not replacements for them.

What Leaders Need to Do Next

As the AI landscape evolves, the risks associated with speed—like errors, bias, and overreliance—will only grow. Leaders who want to stay ahead should focus on embedding beneficial friction into their AI strategies now. Here's your roadmap:

1. Audit Decision Points: Review where AI is used in your business processes and identify where slight delays could improve outcomes.

2. Train Teams to Collaborate with AI: Equip employees with the skills to spot errors, validate outputs, and calibrate trust in AI systems.

3. Be Transparent About Limitations: Let users know where AI might fall short. Honesty fosters confidence and reduces risks.

Conclusion: Speed Isn’t Everything

Think of beneficial friction as the secret ingredient that turns good AI systems into great ones. By deliberately introducing “speed bumps” at key moments, you can prevent mistakes, improve decision-making, and build trust with both employees and customers.

In the race to adopt AI, the winners won’t be the fastest—they’ll be the smartest. By prioritizing accuracy, accountability, and human-centered design, you’ll position your organization as a leader in the responsible AI era.

Ask Yourself:

• Are my AI systems built to support quality decision-making, or just fast ones?

• How am I positioning human expertise as an asset alongside AI?

• What’s one process in my organization that could benefit from beneficial friction today?

• By answering these questions, you’ll be taking the first steps toward a future where AI works for people—not the other way around.