The Networked Customer in 2026

What AI Is Changing (And What It Isn't) About Customer Networks

A decade ago, I argued that customers don’t make decisions in isolation. We live and work in networks, shaped by peers, reinforced by shared experience, and validated by other people like us. The customer journey has always been messy and connected, no matter how much we prefer linear diagrams and neat funnels.

This “networked customer” thesis has held up, but the network itself is evolving.

In the past few years, two changes have altered how customers gather information and make decisions. First, mass social media has stopped functioning as a shared, reliable layer of connection. The platforms that once served as the default network layer have become cacophonous spaces with plummeting engagement. Second, AI tools have entered the decision-making process as new participants. Customers have started using them for their initial research.

The network hasn’t disappeared. It is in the process of fragmenting and reorganizing. Understanding that reorganization is critical.

The AI Paradox: High Adoption, Low Trust

Here is the tension: AI adoption is accelerating while AI output isn’t fully trusted.

The adoption numbers are clear. Sixty-one percent of Americans report using AI in some form, and 37% now start their online searches with an AI tool rather than a traditional search engine.¹ Nearly 60% of consumers have used AI to help them shop.² In the B2B world, generative AI has overtaken Google as the starting point for a quarter of all buyers researching vendors.³

Trust hasn’t kept pace. A major 2025 international study spanning 47 countries found that only 46% of respondents globally are willing to trust AI.⁴ In the United States, the United Kingdom, and Germany, over 40% of the population explicitly resists increased AI adoption.⁵ American respondents are more than twice as likely to say they reject the growing use of AI than they are to embrace it.⁵

That gap produces a predictable behavior: customers use AI for speed and synthesis, then seek out human networks for validation. Eighty-five percent of users cross-check AI answers elsewhere rather than accepting them at face value.⁶ Among B2B buyers who encounter AI-generated summaries, 90% still click through to review sites and citations to verify the claims.⁷

This shows up in both consumer and B2B contexts. AI informs. People decide.

The Customer's Decision Ecosystem

Customers don’t make decisions alone. They draw on an ecosystem of sources, each playing a distinct role in gathering information, forming judgments, and ultimately committing.

That ecosystem has always included peers, colleagues, experts, and vendors. What’s changed is that AI now occupies a role too. Not replacing the others, but handling a specific kind of work.

AI: The Research Assistant

AI has earned a role in the ecosystem for a specific kind of task: fast, functional, information-dense questions where synthesis matters more than nuance.

Seventy-seven percent of consumers say AI helps them cut through information overload.⁸ Sixty percent feel it gives clearer answers than traditional search.⁶ When customers need to compare specifications, summarize options, or get up to speed quickly, they increasingly turn to AI first.

In practice, AI acts like a research assistant. Comprehensive, fast, and tireless. It answers the question: What are my options and how do they compare?

What it cannot (fully) answer is the harder question: Which option is actually right for me?

Peers: Still The Trusted Advisors

For that, customers turn to people.

Fifty-two percent of B2B buyers consult peers first when making purchase decisions. “Someone like me” remains the most trusted source of information.⁷ Edelman’s research found that peers are trusted at twice the rate of executives or officials, even when the topic is AI itself.⁵

The role peers play is trusted advisor. Not comprehensive, but credible. A peer can tell you what the implementation was actually like. Whether the support team is responsive. Whether the product works the way the demo suggested. These are lived experiences no summary can replace.

Fifty-four percent of B2B buyers have conversations with current customers before purchasing, often without the vendor’s knowledge.⁷ They are not looking for more information. They are looking for credible recommendations from “people like me”.

Communities: The Ongoing Context

Beyond individual peers, customers increasingly rely on communities. Private Slack groups, Discord servers, industry forums, subreddits. These spaces accumulate knowledge and context over time.

They work differently from one-off peer conversations. They provide persistent access to collective experience. A buyer can search years of discussions, see how opinions have evolved, and gauge sentiment over time. Communities act as long-term memory.

This is where quiet reference checking takes place. Buyers validate vendor claims in channels that vendors generally cannot see. The community becomes a trust layer that sits outside the vendor’s influence.

Again, the pattern: AI informs, humans decide.

AI as Accelerant, Not Replacement

Many executives are tempted to treat AI as a substitute for employees and to underinvest in, or divest of, the infrastructure (platforms and programs) that supports long-term relationships. Automate support, recommendations, and engagement. Reduce headcount while increasing efficiency.

This is a mistake.

AI earns trust for utility: speed, synthesis, cutting through noise. Human relationships earn trust for credibility: verification, judgment, and the confidence to act. These are not interchangeable.

Companies that use AI to attempt to replace relationship infrastructure risk being present for the research phase but absent for the decision phase. Customers will use AI tools to gather information, then turn to people to decide what to do about it.

The more strategic path is to use AI to make information accessible and reduce friction in discovery. Then invest more heavily in the communities and relationships that determine whether you move from shortlist to selection. And here’s the feedback loop: community investment has become an AI strategy. The companies with strong reputations in the spaces where real users gather will be the companies AI learns to recommend.

Implications for Digital Leaders

Your customers already participate in ecosystems of relationships, whether you realize it or not. They trust AI for some questions and peers for others. They discover communities that serve their needs better than mass platforms ever could. Leaders who understand this know where influence actually comes from. Those who don't will continue wasting money on channels that no longer influence decisions.

The question is whether you will build your strategy around how customers actually behave, or keep broadcasting into an ecosystem that is actively reorganizing, and in some cases, routing around you.

So, where do you start, and what should you do? My advice:

• Map your ecosystems. Where do your customers actually turn when making decisions? Which sources do they trust? Where are you present, and where are you absent? Most companies can draw their org chart and their tech stack. Almost none can draw the ecosystem of relationships that actually determines how their customers decide.

• Differentiate opportunities by utility or credibility: Know what you're competing on. Compete on utility where AI can help you: speed, synthesis, accessibility. Compete on credibility where only relationships can deliver: verification, judgment, and the confidence to act.

• Invest in the ecosystem. Seek out and participate in online and IRL spaces where your customers already gather. In addition to external opportunities, most B2B companies can host spaces, groups, and events to gather customers, prospects, partners, and employees. View community building as a capability. View your community ecosystem as a strategic asset. That's something competitors cannot replicate.

• Measure ecosystem reach, position, and value created. The old metrics measured broadcast: impressions, followers, and share of voice. The new metrics ask harder questions: Are you present where decisions happen? Are you consulted early or late? And are you contributing value to those spaces, or just extracting attention from them?

Treating customers as a passive audience should have ended when the Internet made conversation possible. Most companies never fully absorbed that lesson. They treated social media as another broadcast channel and optimized for attention instead of relationships. But customers were always participants in a system of relationships. The Internet made those relationships possible at a global scale, and AI has made them more visible and more complex, but neither has changed the fundamental reality: trust moves through relationships, and relationships are developed and nurtured by people.

The organizations that understand this will build infrastructure for long-term relationships. The ones that do not will keep making short-term investments for attention, wondering why the conversions never come.

AI informs. People decide.

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Sources & further reading:
1. Search Engine Land, “37% of consumers start searches with AI instead of Google” (2025); Menlo Ventures, “2025: The State of Consumer AI”
2. University of Virginia Darden School of Business / Bloomreach consumer survey (2025)
3. Demand Gen Report, “GenAI Overtakes Search for a Quarter of B2B Buyers” (2025)
4. KPMG / Melbourne Business School, Global AI Trust Study (2025)
5. Edelman Trust Barometer Flash Poll: Trust and Artificial Intelligence at a Crossroads (2025)
6. Search Engine Land / Attest Consumer Adoption of AI Report (2025)
7. TrustRadius, “Bridging the Trust Gap: B2B Tech Buying in the Age of AI” (2025)
8. Darden Report / UVA Darden School of Business (2025)