No. AI can speed up routine security analysis and threat discovery, but it cannot take responsibility for what a finding means to a particular business or guide a customer through the consequences of an incident. In cybersecurity channels, the strongest model is AI-supported work with a human partner accountable for interpretation, communication, and follow-through.
What AI can do—and what it cannot own
AI and machine-learning tools can help security teams process large datasets, streamline repeatable workflows, and surface possible threats faster. Those capabilities are useful; the case for human involvement is not an argument against automation.
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The boundary is between producing or prioritizing information and owning the decision made from it. A detection is not, by itself, an assessment of how a threat affects a customer’s operations, what response is proportionate, or how much disruption the response may cause. Those judgments require knowledge of the business, its systems, and its tolerance for risk.
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| Question | AI-supported workflow | Human-owned outcome |
|---|---|---|
| Task | Parse data, automate repeatable steps, and surface signals for investigation. | Interpret signals in the customer’s business context and guide incident response. |
| Consequence | Improve speed and efficiency in routine analysis. | Weigh risks to business continuity and decide what action is appropriate. |
| Accountability | Provide an output that informs a decision. | Explain the recommendation and take responsibility for advising the customer. |
| Relationship | Offer self-service access to information. | Communicate before, during, and after an incident, including when the answer is uncertain. |
This is a practical distinction, not a claim that AI can never perform a task involving judgment. Alex Glass, Expel’s vice president of global channel sales and alliances, argues that the human function is changing rather than disappearing. His article, published by ChannelPro/ITPro on 28 August 2026, frames AI as an efficiency tool and human trust as essential to navigating a crisis. Read Glass’s article.
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Why the partner relationship matters in a security incident
A customer may judge the advice as well as the technology when a security platform misses a threat or produces a confusing alert. If a channel partner recommended the platform, the customer may turn to that partner for an explanation and a path forward, even when the partner did not build the product.
That creates a reputational stake for the partner. A tool can surface a signal, but it cannot take the place of someone who can explain what is known, what remains uncertain, what the customer should do next, and who is responsible for helping. Trust is built not by claiming that a product cannot fail, but by being candid about limitations and present when the outcome is difficult.
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What customers still want from human support
A 2025 conference paper by Tampere University authors Tommi Mahlamäki and Johannes Kuoppala surveyed B2B distributors associated with a Finnish company operating globally. More than 80% of respondents agreed that digital self-service tools cannot fully replace human support. At the same time, respondents saw practical value in chatbots: 53% (44 respondents) selected reduced search time as a benefit, 60% said they were happy to interact with AI or chatbot technologies, and 69% agreed chatbots were useful for finding information. These findings describe that study’s distributor sample, not all channel partners or cybersecurity customers. Read the study.
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How cybersecurity vendors and partners can use AI without eroding trust
Automate repeatable work, not accountability
Use AI where it can reduce manual effort or help surface possible threats, while ensuring a person can review consequential outputs and make the customer-facing recommendation. The point is not to put a human in every routine step; it is to preserve a clear human owner for high-stakes interpretation and outcomes.
Explain findings in business terms
A threat briefing should connect technical signals to the systems, operations, and risks the customer cares about. Partners add value when they can translate an alert into a clear account of what may be affected, what the team knows, and what action is being proposed.
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Disclose gaps and uncertainty
Customers need an honest account of what a platform does not cover as well as what it detects. Avoid presenting an AI-enabled system as a guarantee. Clear limits help customers make informed decisions and reduce the damage that overpromising can do to a relationship.
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Stay engaged through remediation
Trust is tested during an incident and in the follow-up. Proactive check-ins, practical guidance during remediation, and an honest post-incident review give customers a human point of contact rather than leaving them alone with an alert or an automated response.
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Build around the customer’s environment
Glass argues that channel programs should favor integration-first security architecture that fits customers’ existing systems and can evolve with them. He also calls for vendors to help partners understand AI-enabled threats. These are proposed directions for vendor programs, not independently measured proof that a particular program model succeeds.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What adjacent channel research can—and cannot—tell us
Other studies offer context for the balance between digital convenience and human relationships, but they concern different populations and should not be treated as direct evidence about cybersecurity channel performance.
- McKinsey reports that 57% of respondents in its 2022 Distribution Practice Supplier Survey ranked digital as their primary purchasing channel. In a separate 2025 survey of 299 suppliers, 86% expected to expand direct-to-consumer investment in 2025, and 72% expected D2C sales to grow by more than 25% over the following two years. These are distribution-sector findings, not measurements of cybersecurity customers’ trust in partners. See McKinsey’s distribution analysis.
- The Channel Company and IPED’s 2025 research, based on an online survey of 151 solution providers and partner interviews, found that almost 90% of surveyed partner respondents considered face-to-face events very important to their marketing strategy. This suggests that in-person relationship-building remains important to those respondents; it does not establish that events alone create trust. Read the report.
- Visa’s 2025 consumer surveys in the United States, Australia, and New Zealand found that roughly two-thirds of surveyed consumers use or would use AI shopping agents to save time and find better prices, while nearly nine in ten wanted transparency into agent decisions. This concerns consumer shopping, not B2B cybersecurity relationships, but it illustrates that interest in automated convenience can coexist with a demand for transparency. See Visa’s findings.
The practical test: who can answer when the system is wrong?
When evaluating an AI-enabled security service or channel program, ask who reviews consequential outputs, who explains platform limits, who contacts the customer during an incident, and who guides remediation. If the answer is only “the system,” the customer may have speed without the support needed to make a difficult decision. AI can strengthen the channel by helping people work faster; a trusted human remains the bridge between a tool’s output and the customer’s real-world outcome.
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