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AI can speed up routine cybersecurity analysis, but it cannot take responsibility for what a security decision means to a customer. In the channel, vendors and partners still need people who can interpret risk in business context, explain recommendations, and guide customers through incidents and remediation. The practical model is AI-supported work with human-owned outcomes—not a choice between automation and expertise.
What AI can—and cannot—do in cybersecurity operations
AI and machine learning can streamline workflows, parse large datasets, and accelerate threat discovery. Those are valuable capabilities, especially when security teams face more alerts and information than people can review manually.
But surfacing a signal is different from deciding what it means for a particular organization. A finding may need to be weighed against the customer’s systems, business priorities, exposure, and tolerance for disruption. AI can inform that work; the customer still needs an accountable person to interpret the output and explain what to do next.
| Dimension | AI-supported workflow | Human-owned outcome |
|---|---|---|
| Task | Parse information and surface potential threats quickly. | Interpret findings in the customer’s business and technical context. |
| Consequence | Improve the speed of repeatable analysis. | Weigh effects on business continuity and customer risk. |
| Accountability | Produce an output or alert. | Explain the recommendation and take responsibility for guiding the customer. |
| Relationship | Support self-service information gathering. | Provide continuing, transparent support before, during, and after an incident. |
| Integration | Analyze information within the available platform and data. | Help ensure security architecture fits the customer’s existing environment and evolves with it. |
This is a practical distinction, not a claim that AI cannot perform any task involving judgment. Alex Glass, Expel’s vice president of global channel sales and alliances, argues that the human role is changing, not disappearing. In his 28 August 2026 ChannelPro/ITPro article, he frames AI as an efficiency tool while emphasizing the trust needed to navigate a crisis.
Why a channel partner remains important when a decision is difficult
A customer may not distinguish between the company that supplied a security platform and the partner that recommended or implemented it. If a tool misses a threat, the partner can be the person the customer turns to—even when the technology came from a vendor. That makes trust a practical part of security service, not a soft extra.
The partner’s value is clearest when a customer needs more than an alert: someone to assess localized risk, describe likely business impact, disclose relevant platform gaps, and help coordinate response. During remediation, a partner can translate technical findings into actions the customer can understand and prioritize. Afterward, an honest review can explain what happened and what needs to change.
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Glass’s argument is not that vendors or partners should avoid automation. It is that a system’s ability to detect or summarize information does not make it accountable for the consequences of a recommendation. A customer needs to know who will answer questions, help make a high-stakes decision, and stay engaged if the system fails to identify a threat.
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What the available channel evidence says about human and digital support
A 2025 conference paper by Tommi Mahlamäki and Johannes Kuoppala, based on B2B distributors associated with a Finnish company operating globally, found that more than 80% of respondents agreed digital self-service tools cannot fully replace human support. The same respondents saw useful roles for chatbots: 53% (44 respondents) selected reduced search time as a benefit, 60% were happy to interact with AI or chatbot technologies, and 69% agreed chatbots were useful for searching for information. The findings support a hybrid approach in that distributor sample; they are not a benchmark for every cybersecurity partner or channel.
Other research offers context, but it examines different populations and questions rather than cybersecurity relationships. McKinsey reported that 57% of respondents in its 2022 Distribution Practice Supplier Survey ranked digital as their primary purchasing channel. In its 2025 supplier survey of 299 respondents, 86% expected to expand direct-to-consumer investment in 2025, while 72% expected D2C sales to grow by more than 25% over the following two years. These figures describe distribution purchasing and supplier expectations, not proof that human support is or is not needed in cybersecurity.
Similarly, 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. That is consumer-commerce evidence, not a direct test of B2B security channels.
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Relationship-building also persists in partner marketing. In The Channel Company and IPED’s 2025 research—an online survey of 151 solution providers plus partner interviews—almost 90% of partner respondents said face-to-face events were very important to their marketing strategy. The result suggests that digital tools and in-person relationship work can coexist; it does not establish the effect of events on security outcomes.
How vendors and partners can use AI without weakening trust
Automate repeatable work, keep a person responsible for consequential advice
Use AI to help with high-volume parsing and discovery where it fits the workflow. When a finding could affect a customer’s risk or business continuity, make clear who reviews it, interprets it, and communicates the recommendation. Do not imply that an automated output itself owns the decision.
Make the human safety net visible
Customers should know how to reach someone who can explain an alert, discuss uncertainty, and guide remediation. A threat briefing in plain language, proactive check-ins, disclosure of platform gaps, and an honest post-incident review are concrete ways to show that support exists beyond the interface.
Design around the customer’s existing environment
Glass calls for integration-first partner programs: security architecture should fit the systems a customer already uses and evolve with them. Vendors can support partners by helping them understand AI-enabled threats and by making it easier to integrate products into varied customer environments. This is his proposed direction for vendor programs, not independently measured proof that any particular program succeeds.
Be candid about what automation does not establish
Distinguish a tool that can surface a signal from a person who can explain the business implications. If a platform has a relevant gap or a finding is uncertain, communicate that plainly. Trust is easier to preserve when customers know what a system can contribute and who will help when its output is incomplete.
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Where the boundary should sit
For cybersecurity channels, the strongest case for AI is faster, more consistent assistance with analysis and discovery. The strongest case for people is the work that depends on customer context, clear communication, accountable decisions, and sustained incident support. Keeping those responsibilities explicit lets partners gain efficiency without asking customers to trust an automated tool with outcomes it cannot own.
Sources: Mahlamäki and Kuoppala, 2025 conference paper; McKinsey, “Where value is won and lost in distribution”; Visa, “Earning consumer trust in the age of agentic commerce”; The Channel Company/IPED, “The State of Partner Marketing 2025”.
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