Every executive wants the same thing from AI: better results, faster. Two new research studies reveal a truth that challenges everything about current AI deployment.
The findings seem contradictory. One study shows AI's primary value lies in organizational agility—the ability to move and respond quickly. The other reveals that speed means little if customers don't feel satisfied.
This isn't a paradox. It's a warning.
Companies measure the wrong metrics. They optimize for efficiency when satisfaction matters more. They expect direct performance gains when AI works through organizational systems that must be built first.
The research exposes a gap between how AI works and how companies deploy it. What follows examines what happens when organizations get AI adoption right and what breaks when they don't.
AI Assimilation and Customer Performance: What Really Happens
Researchers asked 382 users a simple question: Does AI adoption improve customer performance?
The answer surprised them. AI doesn't directly boost performance. Instead, it makes organizations faster and more responsive and that agility changes everything.
The Discovery
Install AI in your company and something unexpected happens. You don't immediately see better customer outcomes. What you see first is organizational agility. Your company responds to customer needs faster. It adapts more quickly. It moves.
The researchers measured this effect and found it powerful: AI adoption predicted organizational agility better than any other outcome they studied. Once organizations became agile, the benefits cascaded. Agile organizations delivered better customer experiences. Better experiences built stronger relationships. Stronger relationships drove performance.
This matters because most executives expect AI to directly improve results. They're looking in the wrong place.
How the Process Works
Think of AI adoption as pushing the first domino. The researchers tracked what fell next:
First, AI creates agility. Companies that assimilated AI became more responsive to customer needs. This proved to be AI's strongest direct effect.
Second, agility improves experiences. Responsive organizations delivered better customer experiences. The connection was strong and consistent.
Third, experiences build relationships. Customers who had better experiences developed stronger relationships with the companies serving them.
Finally, relationships drive performance. Here's where the researchers found the second-strongest effect in their entire study: relationship quality predicted customer performance better than any other single factor.
The chain runs: AI → agility → experience → relationships → performance.
Break any link and the chain fails.
What This Means for You
If you're planning to adopt AI, three insights matter:
AI amplifies what you already have. Companies with strong business processes gained more from AI than companies with weak ones. The technology didn't fix broken operations, it made existing capabilities more powerful. If your organization already responds poorly to customers, AI will help you respond poorly faster.
Agility is everything. The ability to sense and respond to customer needs proved to be AI's primary value. The researchers found this relationship so strong that they concluded: if AI doesn't make you more agile, it's probably not helping.
Relationships still matter most. Despite AI's power, the human element dominated the results. Customer relationship quality predicted performance better than anything else the researchers measured. AI enables relationships but cannot replace them.
The Bottom Line
AI doesn't work the way most people think it works.
You cannot install AI and expect immediate performance gains. You must develop organizational agility first. You must improve your ability to sense customer needs and respond to them. You must build systems that turn agility into better experiences and stronger relationships.
Only then does AI deliver results.
AI is powerful, but it operates through your organization, not independently of it. Companies that understand this will gain advantage. Companies that treat AI as a direct solution to performance problems will waste their investment.
The researchers proved what many suspected: AI alone solves nothing. How you integrate it into your organization determines everything.
Source: https://www.sciencedirect.com/science/article/pii/S2666764924000018
When Speed Isn't Enough: What AI Customer Service Actually Needs
A customer contacts your company's AI chatbot. The bot responds in three seconds with the correct answer. The customer never returns.
Why?
New research on 378 customers reveals the uncomfortable truth: companies are optimizing AI for the wrong goal.
The Counterintuitive Finding
Speed matters less than you think. A recent study measured how AI-powered customer service affects loyalty through two pathways: efficiency and satisfaction. Efficiency means fast, accurate responses. Satisfaction means customers feel valued and heard.
The impact difference is stark. Customer satisfaction drives loyalty with a coefficient of 1.07. Efficiency? Just 0.23.
Translation: a chatbot that solves problems quickly but leaves customers feeling processed, not served, builds nothing lasting. The interaction itself—how it makes people feel—determines whether they come back.
Why Most AI Implementations Miss This
Walk into any company deploying AI customer service and ask what they measure. Response time. Accuracy rates. Containment how many interactions happen without human intervention.
These metrics track efficiency. They ignore satisfaction.
The researchers found AI strongly affects both factors (coefficients of 0.92 for satisfaction, 0.94 for efficiency). But only satisfaction converts these improvements into loyalty. Efficiency contributes, but satisfaction decides the outcome.
Consider the customer journey. Someone contacts support frustrated about a problem. The AI resolves it in thirty seconds with perfect accuracy. Efficient? Absolutely. But if the interaction felt robotic, if the customer sensed they were talking to a system optimized to minimize company costs rather than maximize their experience, satisfaction plummets.
What Satisfied Customers Experience
The study doesn't specify, but satisfaction signals emerge from predictable sources. Natural language that doesn't sound scripted. Recognition when customers are frustrated. Acknowledgment that their problem matters. Transparency about what the AI can and cannot do. Seamless handoff to humans when needed.
These elements cost nothing computationally. They require deliberate design choices that prioritize how customers feel over how quickly tickets close.
The Trust Barrier
Many customers distrust AI customer service. Privacy concerns and skepticism about AI's capabilities create resistance. This amplifies satisfaction's importance. When AI earns trust through positive experiences, it builds loyalty. When it doesn't, even flawless efficiency fails.
The research model explains over 84% of variation in loyalty, satisfaction, and perceived efficiency. These aren't marginal effects. Companies can predict loyalty gains from service improvements with confidence.
What Changes
Stop asking "How many queries can we automate?" Ask "How satisfied are customers after AI interactions?"
Stop asking "How quickly does our chatbot respond?" Ask "Do customers trust and value the experience?"
Design AI that understands context, not just content. Train systems to recognize when customers need human help. Build in transparency about capabilities and limitations. Measure satisfaction relentlessly.
The Stakes
Companies that prioritize satisfaction over efficiency don't just reduce service costs. They build stronger customer relationships, increase loyalty, and create advantages that raw speed cannot match.
The research settles this: AI can build loyalty, but only when it builds satisfaction first. Everything else is just faster ways to lose customers.
The Hidden Architecture of AI Success
Both studies reveal what executives miss: AI doesn't create value—it reveals whether your organization deserves to create value.
The research shows AI adoption doesn't improve customer performance directly. It makes organizations more agile. But agility only helps if you convert speed into better experiences, experiences into relationships, and relationships into performance. Break any link and the chain fails.
The second study proves this. An AI chatbot resolves problems in 30 seconds with perfect accuracy. The customer never returns. Because efficiency without satisfaction is just faster disappointment.
AI amplifies what you already are. Strong processes become stronger. Weak ones become efficiently weak. If your organization responds poorly to customers, AI helps you respond poorly at scale.
This explains why most AI implementations fail. Companies treat AI as the solution when it's actually the test. They install chatbots hoping to improve loyalty without first building the satisfaction that creates loyalty.
You can't automate capabilities you don't have.
Companies succeeding with AI aren't deploying better technology. They're better organizations that happen to use AI.
Until next time, Matthias