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Trust has fast become one of the central questions in every serious conversation about AI. Not capabilities. Not efficiency. Trust.<\/p>\n
If customers don\u2019t trust how companies deploy AI, they\u2019ll walk away. If employees don\u2019t trust it, they\u2019ll disengage. If enterprises don\u2019t trust their AI providers, they won\u2019t adopt. A recent global KPMG study found that while two-thirds of people now use AI regularly, fewer than half say they\u2019re willing to trust it.<\/p>\n
I see this playing out every day in customer experience. Deployed thoughtfully, AI can supercharge a company\u2019s ability to understand customers and build connections that drive loyalty. But when the primary objective is to cut costs and reduce headcount, AI can just as easily alienate customers and destroy the trust that took years to build.<\/p>\n
Trust and understanding build on each other. When customers trust you, they share feedback, engage more deeply, and give you the signals that reveal what they actually need. That understanding helps you build better products and experiences, earn more trust, and generate more insights.<\/p>\n
Think about the last time you tried to get help from a company using AI. Maybe you were bounced between chatbots that couldn\u2019t solve your problem, or you got stuck in a rigid workflow with no way out, desperately hunting for an empathetic human who could actually help.<\/p>\n
You\u2019re not alone. Our research shows nearly one in five consumers who have used AI for customer service saw zero benefit. That\u2019s a failure rate almost four times higher than the AI failure rate in general. Half of consumers worry AI will prevent them from ever reaching a human. Concern about how companies use personal data for automation is up 10% from last year.<\/p>\n
Every frustrating interaction customers and employees have with businesses hurts trust.<\/p>\n
The stakes are enormous. It\u2019s estimated that bad customer experience places $3 trillion in global revenue at risk every year. Roughly half of consumers cut spending with a brand after a single bad interaction.<\/p>\n
When AI conversations in boardrooms start and end with cost reduction, failure is likely.<\/p>\n
I see two kinds of AI innovation in the market: science projects and pragmatic AI. Pragmatic AI solves real problems, makes people\u2019s lives easier, and builds connections. Science projects impress in demos but frustrate in deployment.<\/p>\n
The cost-cutting obsession is a trap, and the savings may prove illusory. Gartner predicts that by 2030, the cost per resolution for generative AI in customer service will exceed that of offshore human agents.<\/p>\n
Every competitor has access to the same models, cloud infrastructure, and automation playbooks. When efficiency is the only goal, companies build a commodity.<\/p>\n
Worse, an AI strategy obsessed with cutting costs often produces impersonal, frustrating experiences that drive customers away. You save money on the front end and lose it, along with the customer relationship, on the back end.<\/p>\n
Companies that get this right stop thinking of AI as only a cost play and start seeing it as a way to better understand their customers, build deeper connections, and deliver business outcomes.<\/p>\n
Take customer feedback programs, which are the bedrock of customer experience. When AI is used to make surveys smarter, more conversational, and respond to vague and unactionable feedback, something remarkable happens. When customers share more feedback, quality improves, and the business can take more meaningful action. Organizations are seeing more than 80% of customers engage, and the feedback coming through is twice as good as before.<\/p>\n
The real prize for companies is when they act on this feedback. We\u2019ve integrated agentic AI into surveys powered by an organization\u2019s policies and runbooks. When a customer provides feedback, the agent can take action to close the loop immediately. For companies, this is translating into huge jumps in customer satisfaction and tens of millions in returns.<\/p>\n
In healthcare, we have seen systems deploy AI programming that does an excellent job of remembering who patients are \u2013 recording their history and special concerns. This doesn\u2019t replace doctors and nurses. It informs them and frees them from administrative busywork so they can focus on the human relationship that patients value.<\/p>\n
In market research, companies are using AI, including synthetic market research, to test ideas, understand demographics in hours instead of months, and consolidate platforms. The increased speed is great, but what really matters is what\u2019s being done with the insights: launching products that respond to what customers want while competitors are still working to understand their customers\u2019 needs.<\/p>\n
In each case, the technology is almost beside the point. What matters is that these companies understand their customers better. And that understanding compounds into trust and outcomes.<\/p>\n
Trust is one of the greatest and enduring differentiators in business.<\/p>\n
Companies that earn trust get better data. Better data means better AI interactions. Better AI means better experiences. Better experiences mean more trust. It\u2019s a flywheel, and with every cycle, the leaders pull further ahead.<\/p>\n
Meanwhile, companies that deploy AI without adequately considering its impact on people find themselves stuck. Their AI doesn\u2019t improve because customers won\u2019t engage with it. Their customer relationships erode because every interaction feels like talking to a machine that neither knows nor cares about them.<\/p>\n
Think about where we\u2019re heading. Five years from now, there\u2019s a legitimate question about how often we\u2019ll interact with websites through browsers versus having conversations with agents.<\/p>\n
In that agentic world, the experience delivered to the user will differentiate every provider.<\/p>\n
The organizations that understand human connection \u2013 personalization and the ability to make customers feel heard and seen \u2013 will win. Because they are the companies that figured out that AI works best when it helps you understand, respond, and build connections with people, not just process them.<\/p>\n<\/div>\n
#success #avoid #efficiency #trap #focus #trust<\/p>\n","protected":false},"excerpt":{"rendered":"
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