It’s encouraging to see large enterprises like Dell Technologies investing in conversational AI for customer support. Done well, these systems can dramatically reduce friction, shorten resolution times, and free human agents to focus on complex issues.

However, effectiveness depends on how well the AI is integrated with existing telemetry and support workflows.

In my case, SupportAssist already knew exactly which device I was using. Yet it could not provide a direct link to the specific firmware update it recommended. Even more puzzling, the system did not recognize that the firmware was already up to date, resulting in repeated troubleshooting steps that added time without adding value.

After roughly 20 minutes of guided interactions, the process reached the stage where a repair dispatch would normally be created — only for the system to fail to complete that action. The next outreach came not from standard support channels, but from a “social media” team. Whether coincidental or not, it creates the impression that public complaints may be a more reliable escalation path than the official workflow.

Eventually, the root cause identified was a swollen battery — outside warranty — with guidance to contact sales to purchase a replacement.

None of these individual steps are unreasonable on their own. The friction comes from the lack of continuity between them. When AI, diagnostics, escalation paths, and fulfillment processes are not tightly integrated, customers experience the journey as disjointed rather than seamless.

Conversational AI has enormous potential in support environments, particularly when paired with device telemetry and historical data. The opportunity is not just to automate conversations, but to orchestrate outcomes — guiding customers efficiently from problem identification to resolution with minimal repetition or dead ends.

As organizations adopt these tools, success will hinge less on the sophistication of the chatbot itself and more on the depth of integration across backend systems. Automation that cannot act on the data it already has risks becoming another layer of friction rather than a solution.