8 min read AI has been a game-changer in device support. Powered by AI, devices can now offer instant, efficient, and personalized assistance. From automating diagnostics to enabling self-service, AI helps minimize downtime while improving resolution speed.
Whether you’re supporting complex industrial machinery or smart devices, AI supports operations at every step.
In this guide, we’ll explore how to harness AI for seamless device support and superior customer experiences.
The evolution of device support: Why AI is essential
Traditional device support has been a slow and reactive process where technicians overly rely on manual troubleshooting, mostly in a siloed system where finding a document is hard. As a result, customers often receive delayed support, inconsistencies in services, and repeated handoffs.
This is especially true for complex products.
On the other hand, customer expectations are constantly rising. Today’s customers demand instant support in their preferred language, via their preferred mode, and at their preferred time.
A delayed and generic response is no longer acceptable to a customer.
That’s where AI comes in to bridge the gap through automation, real-time responses, and actionable insights.
Benefits of AI-powered device support
AI-powered device support brings in multiple benefits, including:
- 24/7 availability via voice and text, across 100+ languages, making customer service more inclusive and globally accessible.
- AI helps deliver instant, accurate, and consistent answers every time for both users and partners, thus leading to higher customer satisfaction and trust.
- AI and automation come in handy for responding to repetitive queries, thus freeing up human agents who can focus on more complex issues. This can help improve operational efficiencies while also cutting down costs.
- AI can personalize the user journey by proactively reminding users about their device maintenance, tracking usage patterns, and prompting refills or reorders.
- With every user interaction, AI systems become efficient in understanding context while delivering faster and accurate resolutions.
- AI has the capability to identify upsell opportunities, recommend complementary products, and guide users in making informed purchase decisions through product differentiation.
Key features to seek in AI device support solutions
While there are several AI device support solutions available, look for a solution that has these key features.
Seamless integration
Go for a solution that offers seamless integrations with other platforms, CRMs, and your ticketing systems.
For example, Auralis AI offers integrations with over 150 platforms into your workflow. Be it Zendesk, Freshdesk, or any other enterprise solution, your AI device support solution must ensure smooth data flow across platforms.
This ensures faster resolution, more context for the agents, and a unified view of the customer journey.
Multimodal support
Reach your users wherever they are in whatever mode they prefer. Choose AI support that offers voice, chat, and real-time agent training.
For example, Auralis AI offers all three to ensure users and agents get consistent, intelligent assistance across channels, reducing friction and improving accessibility.
Security-first, cloud-optimized, and on-premises options
Opt for a solution that offers flexible deployment models, like cloud, hybrid, or on-premises, to meet your organization’s compliance and data security needs.
Auralis AI, for instance, supports industry standards like HIPAA, GDPR, and ISO.
Robust analytics
Look for AI platforms with built-in sentiment analysis, CSAT tracking, trend reporting, and audit trails.
These features help identify support gaps, improve agent performance, and drive better product decisions.
Transforming the patient and partner journey
AI has completely reshaped the way patients and partners interact with devices and support systems.
Before AI, users often struggled to locate manuals or troubleshoot issues, faced delays in reordering essential supplies, and were frustrated by fragmented support with no clear feedback channels.
These pain points led to dissatisfaction and poor engagement.
After AI, the experience is faster, smarter, and more personalised.
Users get real-time answers in their preferred language, enjoy automated refills and usage tracking, and can provide instant feedback that fuels product innovation.
AI also helps partners demonstrate device value more clearly through data-driven insights.
Real-world impact: Metrics and case studies
This is how we have seen numbers improve for clients of Auralis AI across different industries and use cases:
Operational cost reductions
By automating routine support tasks and reducing the need for manual intervention, Auralis AI clients have reported a significant reduction in operational costs by as much as 28 – 33%.
Decrease in repetitive tasks
AI takes over the bulk of recurring and low-complexity queries, such as device setup, common troubleshooting, or supply reorders.
This has led to a 30% drop in repetitive tasks, freeing teams to focus on other tasks.
Boost in first-contact resolution
Clients using Auralis AI have seen first-contact resolution rates increase by up to 45-65%. With AI offering real-time, accurate, and context-aware responses, many issues get resolved instantly.
Reduction in average handle times
AI-assisted interactions significantly cut down the time it takes to resolve tickets. With quicker access to the right information and contextual prompts, average handle times have decreased by up to 55 – 73%.
Faster onboarding and weekly time savings
New agents trained with Auralis AI tools ramp up nearly five times faster, thanks to on-the-job learning prompts, knowledge base suggestions, and guided workflows.
Existing agents also save more than 15 hours a week as repetitive tasks are handled autonomously.
Improved customer satisfaction and retention
AI support leads to smoother, more personalised user journeys, resulting in measurable improvements in CSAT and NPS scores. Clients have reported fewer complaints, higher user trust, and a notable boost in customer retention.
Step-by-step guide to implementing AI for device support
Implementing AI doesn’t have to be overwhelming. Here’s a structured, step-by-step approach that teams can follow:
Data extraction and cleanup from manuals, tickets, and feedback
Start by collecting key documents like manuals, past tickets, training materials, and customer feedback. Clean and organize this data to ensure it’s structured, consistent, and ready for model training. A well-prepared dataset lies the foundation for reliable AI performance.
Training AI models on your unique data
Train the AI models using your product-specific language, workflows, and support scenarios to ensure optimal performance. Custom training helps the AI understand your domain and deliver accurate, contextual answers that feel human and relevant.
Integrating AI with existing support systems
Integrate your AI with existing CRMs, ticketing tools, and device monitoring platforms. This ensures real-time data access, allowing AI to support seamless customer interactions across systems.
Ongoing monitoring, auditing, and quality assurance
Once live, continuously track AI performance with regular audits and QA checks. Monitor metrics like accuracy, sentiment, and resolution time to fine-tune the system.
Continuous maintenance and model updates as products evolve
Keep the AI up to date by retraining it as your products evolve. This ensures long-term accuracy and adaptability.
Best practices for maximizing AI support success
To make the most of your AI investment, adopt these key best practices:
Prioritise human-centric user experiences
AI should make support feel more human, not less. Focus on natural language interactions, empathetic tone, and a frictionless experience. Offer smooth handovers to human agents when needed, especially for sensitive or high-impact issues.
Maintain continuous feedback loops with users and agents
Feedback from users and agents helps identify blind spots and improve AI performance. Make it easy to collect and incorporate this feedback.
Foster collaboration across product, engineering, and support teams
Involve all key stakeholders. Remember, each team brings in its expertise. For example, the product team brings domain insights, engineering ensures integration, and support teams validate real-world effectiveness.
Ensure scalability and flexibility in your chosen solution
Choose an AI solution that grows with your business. Whether you’re adding new devices, expanding to new regions, or handling larger volumes, your AI must be able to scale, without needing a complete overhaul or additional headcount.
The future of AI in device support
The future looks promising. Here’s what to expect:
Predictive support and hyper-personalization
From reactive support, AI is enabling us to offer predictive and hyper-personalized support. For example, AI can now anticipate issues using real-time data from the device, past records, and usage patterns.
This enables predictive maintenance, thus minimizing downtime. Further, hyper-personalization can customize the support journey based on the individual’s behavior and preference.
AI-driven product innovation
As AI gathers more and more user information, it can then be used in the future for new product development.
For example, brands can analyze the common pain points, look into the new feature requests, analyze the usage patterns, and develop more intuitive solutions. This will help bridge the gap between user expectations and product capabilities.
Sustainable operations and cost reduction
AI will continue to drive sustainable operations that will reduce site visits and improve uptime. Smart automation will enable the utilization of fewer resources and more efficient workflows that will save operational costs while delivering faster results.
Scaling support without scaling headcount
As businesses grow, the support demands will rise too. AI will enable companies to scale support without adding any additional headcount.
Whether it’s resolving tickets or triaging issues, AI can extend support, while human agents can focus on more complex issues.
Conclusion
AI-powered device support is no longer a future trend, it’s a competitive advantage. With the right strategy, tools, and cross-functional alignment, businesses can streamline support, reduce costs, and deliver faster, more personalized experiences.
The result?
Happier users, empowered teams, and long-term growth.
If you’re seeking one such solution that could improve your AI support for your business, book a demo of Auralis AI today.
