From long diagnostic cycles to frequent site visits, customer support for companies with complex products is not easy. 

Whether you’re a company offering medical imaging devices, additive manufacturing tools, or industrial machinery, customers expect faster resolution and minimum downtime. 

However, with increasing product complexity, traditional service models are falling short. 

That’s where AI steps in. 

From intelligent triage to smarter resolution planning and even post-visit engagement, AI is transforming field service operations. 

In this blog post, we’ll see how to use AI for field support and improve customer satisfaction. 

What is field support for complex products?

Field support for complex products is not just limited to technical assistance for complex, high-value systems, but goes beyond it. 

It includes training the customers on how to use the products efficiently, conduct regular maintenance check-ups for the optimum functioning of the product, and offer recommendations to the customer for any upgrades and improvements. 

Some of the common industries that extensively use field support include healthcare (MRI, CT), additive manufacturing (3D printers), aerospace systems, heavy industrial machinery, lab automation, etc. 

What makes field support challenging in such complex industries is high variability, multiple configurations, limited expertise, long diagnostic and resolution cycles. Here, even a small issue can lead to significant downtime affecting the company’s revenue. 

Effective field support ensures minimal disruption, maximizes uptime, and provides the expert care these sophisticated systems demand to function without any hiccups.

The challenges of traditional field support models

With the growing customer demands for faster resolution, the traditional field support models are no longer efficient enough to meet the desired service quality, resolution time, or customer satisfaction. 

Manual ticket triage slows first response

In the traditional model, the support tickets are routed manually, which delays the resolution time. For example, a ticket might be routed to the wrong team or misprioritized, thus delaying the response time.

High dependency on SMEs (subject matter experts) and superusers

Traditional models heavily rely on subject matter experts for resolution. This means that when these SMEs are unavailable, resolution becomes delayed, risking customer dissatisfaction. 

Technicians often arrive with incomplete context

Many times, the technicians arrive on the field site with incomplete context, like previous resolution attempts or the machine’s configuration history.

Lack of context means the technicians need to spend time gathering the basic inputs before they can actually begin troubleshooting. 

Documentation is scattered, leading to longer diagnosis/resolution

In manual support models, documentation like technical manuals, troubleshooting guides, or past service records is often stored in a scattered way. This means that the technician has to scout through paper files and storage to find the relevant document, leading to longer resolution time. 

Feedback from field visits rarely closes the loop

The manual support model lacks a structured feedback system. As a result, the feedback from the field visits does not reach the product team or the service playbooks. So the organization misses the opportunity to learn and improve its products/services. 

Scheduling inefficiencies, especially with limited engineer availability

Scheduling engineers can also be challenging, especially for companies with limited engineer availability. Such scheduling delays can further add to customer dissatisfaction.

However, you can turn the table and change this narrative with the help of technology and AI. From optimizing technician workflow to improving customer experience, AI brings productivity, accuracy, and efficiency in field support for complex products. 

How AI transforms the field support workflow

Let’s understand how you can use solutions like Auralis AI at every step in field support: 

Pre-Visit

AI algorithms can analyze support tickets, past data, and equipment telemetry and predict the need for an on-site visit.

AI can also recommend targeted diagnostic steps remotely before dispatching an engineer. For example, remote resets or software updates can be conducted for complex systems like CT/MRI scanners and reduce the resolution time. 

Technicians can be well-prepared with AI-curated probable issue paths and relevant documentation before arriving in the field.

During Visit

AI guides field engineers with contextual KBs, step-by-step guidance, and interactive troubleshooting flows in real-time based on the inputs captured during diagnosis. 

Conversational AI can support engineers by answering technical questions, retrieving circuit diagrams, and initiating escalations. 

As the technicians carry on their job, a smart documentation system logs all the actions taken along with customer feedback. All these notes can be auto-captured and fed into the system, eliminating the need for any manual documentation. 

Post-Visit

Post the engineer visit, AI logs insights from service notes into structured formats, updates the knowledge base with resolution details, and triggers follow-up support or client feedback surveys as necessary. 

Key AI capabilities that improve field support

Here’s what makes AI an enabler: 

Intelligent ticket triage and routing

AI helps to tag tickets accurately by analyzing the priority of the issue, product category, and even customer sentiments. 

AI-powered knowledge retrieval

AI helps engineers to retrieve useful information easily by analyzing the ticket query. Not just that, it continuously evolves itself through ongoing learning, becoming more accurate and efficient over time.. 

On-site technician assistants (Chat/Voice)

Voice and chat-enabled assistants allow engineers in accurate diagnosis and resolutions. 

Predictive maintenance and failure detection

One of the biggest capabilities of AI is to predict future problems. This helps to address issues on time, avoiding the risk of failure and system downtime. 

Automated documentation and feedback capture

AI helps in real-time note capturing and gathering customer feedback, which is then shared back with the key team members. It helps to close the feedback loop so no data gets misplaced. 

Benefits of AI-Enhanced Field Support

Some of the significant benefits of AI-powered field support include:

Faster first-time resolution rates

AI enables efficient scheduling and routing of technicians based on the real-time data available. Since technicians have immediate access to all the relevant documents/data, customers can expect faster resolutions with minimum downtime. 

Reduction in time-to-dispatch and visit preparation

AI plays a significant role in reducing dispatching and visit preparation. Using smart scheduling and optimization algorithms, AI can check for technician availability, skills, location, and job urgency to build the most efficient schedules in real time. 

Lower repeat visit rates and escalations

From forecasting potential failures to assisting engineers with instant access to technical manuals and past service records, AI allows engineers to work more efficiently without the need for escalations. 

Improved field engineer productivity and satisfaction

With AI-powered mobile apps, driven by machine learning and Natural Language Processing (NLP), technicians no longer need to enter data manually on spreadsheets. 

AI can automatically pull key information from equipment sensors, customer databases, and past service records to populate real-time apps. 

With NLP and voice recognition, technicians can easily access critical data, update job statuses, and manage tasks hands-free. 

All these result in better efficiency, fewer errors, productive engineers, and happier customers. In fact, a study found that integrating AI with mobile tools boosts field service productivity by 30% to 40%, proving just how transformative this technology can be.

Reduced support costs and downtime

AI and machine learning work great in asset service management through predictive analytics. With different statistical modeling and data mining techniques along with sensor readings and past data, AI can predict equipment failure and schedule proactive maintenance. This helps to minimize downtime and reduce support costs. 

Continuous improvement through feedback loop automation

Through AI-powered tools, engineers can enter all the valuable customer feedback that can then be sent to the product team and customer success team. Automating this process helps the company to work on customer feedback proactively to improve its process and offer better customer care. 

Example of use cases across industries

AI can help field support across various industries, including:

• Medical Devices: AI comes in handy for triages of CT/MRI scanner tickets and recommends if remote resets can solve the issue, or it dispatches for escalation.
• 3D Printing: In the 3D printing industry, AI guides engineers in recalibration, nozzle replacements, and post-processing troubleshooting, etc. 
• Industrial Automation: AI is largely used in the industrial automation industry to pre-load service histories and wiring diagrams before dispatch.
• Lab Equipment: For lab equipment, technicians can use voice-guided AI support to handle in-situ repairs in regulated environments.

What to look for in an AI field support solution

If you’re ready to explore AI-powered support solutions for your complex and regulated product/service, here are some breakdown of capabilities for you to consider. 

Choose an AI  solution that seamlessly integrates with your ERP, ticketing, and knowledge systems. This will ensure that the field engineers can have real-time access to parts inventory, job histories, and customer data from a single solution. 

Go for a solution that offers offline support or caching. This comes in handy, especially in remote locations or infrastructure-heavy locations. This way, technicians can still access crucial documents even without the internet. 

Enterprise-grade security and compliance (SOC 2, HIPAA, etc.) is non-negotiable, especially in regulated industries. So choose an AI solution that offers encryption, audit logs, and role-based access control while adhering to industry regulatory guidelines. 

AI solutions that offer multi-language and multi-modal access via web, mobile, and voice ensure a consistent user experience irrespective of location, device, or language. 

Field service workflow varies from industry to industry. So, go for an AI solution that lets you do customized workflow to support specific operational standards. 

Conclusion

Be it intelligent triage or real-time guidance, AI enables companies to streamline their field support for complex products while improving their efficiency.  

If you’re seeking one such solution that could build out custom workflows tailored to your business, book a demo of Auralis AI today. 

What’s the secret that’s helping companies ace their IT service management? Competitive and modern businesses are increasingly incorporating AI-based ITSM systems to meet the needs of their end customers. 

Today, customers expect quick responses, real-time support, and human-like support to complex IT issues. Therefore, traditional ITSM is not enough. The solution? AI-based IT service management.

If you’re struggling to keep up with your ITSM, looking to transform it, or curious about whether AI can help you, this blog is for you.

What Is ITSM? 

IT Service Management (ITSM) is the strategic approach businesses use to design, deliver, and manage the IT services they provide to end users. For instance, providing IT support to customers is a core process. Think incident management that requires quick resolutions, and planned changes or upgrades required to IT systems.

ITSM includes processes and procedures that ensure customers’ IT needs are met. Let’s look at some core factors of ITSM:

• Incident management, for example, service disruptions
• Routine service requests, such as those that are periodical
• Upgrade requirements to IT systems
• Problem management to address root causes

Effective ITSM ensures that businesses are able to provide technology support and keep customers’ work going. Providing reliable and accessible ITSM keeps customers satisfied. It also optimizes operational efficiency. 

The lack of ITSM can lead to customer dissatisfaction, service outages, and security issues, among other problems.

Challenges of traditional ITSM

Let’s face the truth. Traditional ITSM is not efficient. Long waiting lists, piling tickets, slow resolution times, and unhappy customers, leading to churn. Traditional ITSM has several challenges. Here are some: 

1. Slow resolution times and ticket backlogs

Traditional ITSM systems often create bottlenecks that leave users waiting for days or weeks for resolution. For instance, manual ticketing process, manual resolutions, and teams overloaded with service requests are some of the common issues. 

Even simple password resets or software upgrades can take a long time to get resolved. This can frustrate customers and have a negative impact on their work. Besides, it leads to bad customer experience and damaged brand reputation. 

AI-based ITSM can reduce resolution times and ticket pile-ups. For example, a quick review of Auralis AI-based ITSM revealed the average ticket handle time for customers to be two minutes, which is almost unthinkable via traditional methods.

2. Inconsistent workflows and manual triage 

Traditional ITSM processes that are dependent on human intervention have a higher chance of inconsistency. For instance, different agents may categorize the same issues differently, apply varying priority levels, or follow different resolution methods. Such manual triage decisions can lead to unpredictable outcomes. Customers might not receive the best solution to their issues. Auralis AI-based ITSM has led to 57% reduction in human errors for customers.

3. High operational costs and agent burnout 

ITSM done the traditional way involves many expenses, such as hiring human agents, training the agents, office space, equipment, and other overheads. Moreover, with traditional ITSM methods, support agents might end up spending hours in fixing small issues, such as password resets. 

This leads to increased costs for your business. Moreover, it can also lead to agent burnout. Conversely, 90% of businesses that use AI-based customer support systems report time and cost savings.

4. Poor SLA adherence and employee satisfaction 

Meeting Service Level Agreements (SLA) with manual ITSM processes can be a struggle. That’s because companies often miss their committed response and resolution times. This can lead to penalties and negatively impact customer relationships. Moreover, customers may lose confidence in your IT services. Auralis customers have reported a 21% decrease in negative support experiences.

Why AI is reshaping the future of ITSM 

Artificial intelligence (AI) is changing how businesses conduct service management, including ITSM. Tasks that take days and weeks with the traditional or manual methods can be completed within hours with AI. 

AI not only digitizes manual processes, but also adds a layer or multiple layers of intelligence that can easily understand patterns, contexts, and make informed decisions based on data. This adds proactive capabilities to IT service teams. While AI does not replace ITSM workflows, it definitely enhances processes and performance. 

Consider these statistics:

• 93% of AI users believe it enables them to focus on higher-level tasks
• 83% of AI users say AI amplifies human creativity
• 87% of service decision makers say technology helps them better serve customers

Here’s a graph that shows how AI will reshape customer service and how it covers all aspects of ITSM:

Source

AI capabilities for ITSM

Whether you’re looking to save costs or struggling to provide more accurate IT support, AI capabilities are increasingly promising to help address every ITSM challenge. Here are some AI capabilities specifically useful for IT support management.

1. Automated ticket triage and classification

AI-based systems can analyse tickets and requests in no time, understand and easily categorize issues with higher accuracy compared to human agents. Machine learning (ML) algorithms recognise patterns from data and identify incident types, priority levels, and correct solutions. This reduces delays and inconsistencies of manual triage. This way, critical issues can get attended to immediately. 

2. Smart response suggestions and knowledge retrieval

AI-based systems can easily search vast data within seconds. It can assess ticket histories and documentation repositories, and provide human agents with relevant and helpful information as well as responses. AI systems have the ability to differentiate between issues and suggest relevant and tailored solutions. For instance, it can make suggestions based on the user’s location, previous history, etc. 

3. Predictive insights and proactive service

With AI systems, you can predict future problems based on past patterns. For instance, AI systems can analyse system logs, user behaviour, and historical data and flag potential issues, such as hardware failures, or security gaps. This way, IT teams can schedule preventive maintenance.

4. 24/7 multilingual support

Another notable capability of AI-based virtual ITSM agents is the ability to provide assistance and support 24/7. Moreover, AI ITSM tools are designed to understand multiple languages. The tools manage all kinds of requests, routine and escalate complex issues to human agents. These systems provide support regardless of timezones or languages. 

With AI ITSM systems, you can ensure proactive service, adding value to your customers. Rather than waiting for problems to occur and then reactive, with AI, you can identify, predict future issues, and provide personalised solutions. 

How Auralis enables ITSM

Many businesses are turning to AI-powered IT service management for their customers. Customers who use Auralis have noted its ability to provide proactive support, personalized service based on location and language, and timely services whenever customers need it. Here are some Auralis features that enhance ITSM.

1. Helpdesk Assistant

Auralis’s Helpdesk Assistant feature helps with drafting responses to queries, suggesting solutions, and sharing relevant information. Agents have to simply send the pre-written responses. This reduces response time. It also reduces the need for agents to be trained thoroughly. 

2. Quality Auditor

With the Quality Auditor feature, you can automate ticket reviewing for compliance, accuracy, and completeness. The feature checks if the responses adhere to organizational policies, regulations, and best practices. It also flags any issue with these factors. With this feature, you can avoid compliance violations and maintain high quality standards.

3. CX Coach

Another effective way in which Auralis helps with ITSM is via its feature, CX Coach. This feature provides support in real-time. For instance, it provides suggestions during customer interactions, helps human agents during complex scenarios, and provides comprehensive onboarding support. It provides coaching as well as feedback to new hires.

4. Live Chat AI Agent

Human touch is the cornerstone of customer support. Even with digitalization and AI, more than 70% of customers want to interact with human agents. That’s where Auralis Live Chat AI Agent helps. The feature provides human-like support across channels, such as chat, voice, and email. This AI agent can handle queries just like human agents, maintaining conversations and ensuring users receive support on all channels.

5. Insights Analyst

Auralis Insights Analyst feature provides dashboards that track SLA performance, CSAT scores, and other metrics. With predictive analytics, this system helps businesses identify upcoming trends, predict needs, and make data-driven decisions. Insights Analyst provides actionable insights that helps with service improvements. 

The measurable impact of AI in ITSM

We collated how AI is impacting ITSM based on numbers from companies that are using Auralis for IT service management. And the results are promising:

• Businesses have reported 60% cost savings through automated processes that have enhanced manual systems and reduced the need for additional support staff.
• Support agents have reported saving 15 or more hours per week that were previously spent on routine tasks like password resets, basic troubleshooting, and information gathering. 
• Companies have saved an average of 32 hours per new hire through AI-powered training and real-time coaching systems provided by Auralis.
• Automation capabilities have enabled businesses to resolve up to 60% of tickets without human intervention.
• These automated resolutions happen instantly, 24/7, providing users with immediate assistance regardless of time zones or staff availability. 
• Auralis customers have reported a 21% reduction in negative user experiences. 

Why IT leaders are choosing Auralis over traditional ITSM tools

From lower resource requirements to higher accuracy to the ability to make strategic data-based decisions, there are several reasons why IT companies are choosing Auralis and doing away with their traditional ITSM systems. Here’s a comparative table that shows why businesses are choosing Auralis. 

Traditional ITSM	Auralis AI ITSM
Manual and reactive processes that fail to identify issues before they occur	AI-driven, proactive systems that predict problems, making it easy to address them before they occur
Human-based processes that are more error-prone	Intelligent automation processes bringing consistency in resolution compliance
High costs due to resource requirements	Automation scales without additional hiring, reducing costs
Dependent on human resource, hence limited scaling	AI has the ability to handle unlimited simultaneous requests and problems
Static dashboards with historical reporting	Real-time, predictive insights that enable proactive decision-making
Basic security with manual compliance processes	SOC II, HIPAA, GDPR compliant with automated security features

Here’s an infographic that explains why AI-based ITSM is the way forward.

Source

Transform your ITSM with Auralis

ITSM systems are evolving and transforming, from traditional, manual processes to digitized and AI-based. In such a scenario, if you do not change with the times, you might get left behind in the industry.

There are many AI-powered ITSM solutions in the market. Among them, Auralis is leading the change in ITSM. 

Auralis features that can enhance ITSM for you:

Increase ticket resolution speed

Auralis provides AI-powered triage and auto-generated responses that reduce handling and resolution time.

Higher agent efficiency and accuracy

Auralis tools draft responses, suggest macros based on historical data, ensure compliance, provide real-time coaching and automate onboarding, increase productivity and accuracy.

24/7 human-like support

Auralis is designed to meet customer need for human touch with a live chat feature that is available 24/7, supports multiple languages, and learns and improves based on context and intelligence.

Auralis is designed to enhance your ITSM system and help your human agents, not replace them. This is one reason teams using Auralis do not feel threatened by it, but rather, feel more encouraged to use the tools to improve their productivity and quality of work.

If you’re looking for an AI-based ITSM system for your business, Auralis is here to help.

Book a demo of Auralis today!

ERP implementation gets all the attention, but it’s post-go-live support that dictates long-term success.

Most businesses that survived implementation face post-launch challenges like user confusion with workflows, an influx of support tickets, and a spike in costs. Traditional ERP support models fall short of these challenges because they are reactive, inefficient, and difficult to scale.

That’s where AI-powered ERP support stands tall, offering smarter, faster, and more proactive solutions that help teams troubleshoot issues, onboard users, and optimize system performance.

In this guide, we’ll explore how you can build a more effective, future-ready support strategy that boosts ERP adoption, enhances user experience, and cuts down operational costs.

What is ERP support and why it matters after go-live

ERP support process kicks in post-implementation. It is to ensure there’s companywide awareness, adoption, and utilization of the enterprise resource planning (ERP) systems. 

The team responsible for ERP adoption handles everything, like answering user queries, resolving technical issues to maintain system performance, and rolling out feature updates. An effective support strategy ensures the ERP system delivers long-term value, beyond a successful launch.

ERP implementation is not the end goal, it is the post-go-live phase that puts its success to the test. It’s a phase where users face unfamiliar interfaces, new workflows, and steep learning curves, and need support navigating through all these challenges. 

The weight now falls upon the support teams. They get flooded with support tickets, ones that must be solved on priority because any delay in resolution can disrupt business operations. Without the right support strategy, productivity dips, adoption stalls, and costs escalate.

Whatever the choice of your ERP software is, SAP, Oracle, Microsoft Dynamics 365, or NetSuite, strong ERP support is essential to keep your system running smoothly and your users confident and productive.

5 common ERP support challenges companies face after go-live

Here are five common challenges after go-live, where companies discover that supporting an ERP system is just as complex as implementing one:

High support ticket volume for routine questions

Just as learning a new software is meant to be, users face trouble understanding new workflows, even the most basic ones like running reports, finding data, or simply, the next steps, and reach out to the support team. Support desks face a flood of such basic user queries, which firstly, stall urgent issues, and secondly, burn out support teams.

Overdependence on internal experts or superusers

Because implementation has the spotlight, organizations rely heavily on a few internal ERP experts or superusers, counting on them to help keep the system running smoothly. Sure, it helps with costs and immediate support, but it’s a risky bet for the long haul, especially when they are unavailable, leave the company, or become stretched thin.

Slow onboarding for new users and departments

Onboarding isn’t a one-time event, it’s an ongoing process. As new employees join or additional departments adopt the ERP system, they need guidance and training. Without the right tools or support, these users often face confusion, poor adoption, and reduced productivity. 

Limited visibility into system adoption or training gaps

Insights into ERP adoption can be a major breakthrough to success, but not all companies have access. It is difficult to improve support and adoption without insights on training gaps, the most complicated workflows, modules that are underused, and so on.

High external support costs and long resolution times

When the internal support function isn’t sufficient, companies go around trying to hire external help, which includes either consultants or vendors. But, seeking support externally is not only time-consuming but also expensive. They take days to resolve tickets, which in turn disrupts operations and confidence in the system.

How AI is transforming ERP support across the user journey

AI-powered ERP support takes a detour from conventional help desks that users must reach out to. Rather than adding an extra step or friction, AI-led ERP support brings help right into the user’s workflows, whether on the web, within ERP apps, via chat, or even through email. 

These systems use natural language processing, machine learning, and behavioral data to understand user intent and deliver real-time, contextual support automatically, and the right blend of human support in the mix. Platforms like Auralis are leading this evolution, making ERP support more proactive, scalable, and user-centric.

Let’s understand how AI is reshaping ERP support at every stage of the user journey:

Answering common ERP questions in real time

AI assistants are deployed at different touchpoints along the workflows, so users do not have to log a support ticket and wait for resolution, but can rather seek instant support from the assistant.

For instance, if a user is unable to fetch order and invoice details, they can simply turn to tools like Auralis Assist and ask “How do I generate a purchase order?” or “Where can I view open invoices?” and the AI agent can instantly point the user in the right direction practically. It not only improves user satisfaction but also frees internal teams to focus on high-impact issues.

Helping users navigate complex workflows

ERP system-related workflows are not always simple, they can get complex with multi-step/layer processes. AI has the capability of walking users through every step in the process, carefully and with clarity, reducing errors and confusion. 

So, with tools like Auralis AI, users can independently navigate through complex workflows confidently without constant back-and-forth with IT or superusers.

Delivering personalized onboarding based on role

ERP use cases differ among roles and departments, and a standard training material for all of them would barely help. With AI, companies can personalize onboarding experiences according to each user’s role, department, and tasks.

Suggesting documentation or training resources

Beyond answering basic queries, AI can also provide greater context and understanding by suggesting relevant support content like a video walkthrough, a knowledge base article, or a system tip.

Benefits of AI-powered ERP support for IT, HR, and Operations teams

Here’s how AI-powered ERP support helps internal teams that manage, enable, and depend on ERP systems:

For IT: Reduce ticket volume, scale support, and monitor usage trends

IT teams are typically the first to feel the pressure post-ERP launch, with a hike in support tickets and user issues. AI takes the burden off by handling high volumes of repetitive queries through self-service agents embedded directly into the ERP interface.

Beyond ticket deflection, AI enables IT teams to scale support without scaling headcount. AI assistants are available 24/7, serving hundreds of users simultaneously. And with built-in analytics, platforms like Auralis give IT visibility into system usage, recurring issues, and training gaps, helping them proactively optimize both support and ERP configurations.

For HR: Improve training efficiency and accelerate employee onboarding

HR, the team responsible for ERP adoption, can benefit a great deal from AI-driven ERP support in training and onboarding new employees. As opposed to the conventional, standard onboarding for all teams, AI can help deliver personalized, in-context guidance in real-time.

Some of the AI-powered support functions specific to HR teams include role-based walkthroughs, smart tips, and reminders inside the ERP itself, without depending upon live trainers or lengthy documentation. 

For Operations and Finance: Increase ERP adoption, reduce downtime, and improve process compliance

Inconsistent ERP usage is a tie-break for operations and finance teams because errors and delays can cause bottlenecks and financial constraints. AI can iron out these hiccups by embedding intelligent nudges and workflow support that guide users toward correct processes.

For example, they can use AI-powered ERP support to reduce inconsistencies in procurement, invoicing, reporting, or approvals. All of it results in greater adoption, reduced delays, financial accuracy, and better compliance with internal processes.

Key features to look for in an AI ERP support solution

Here are the key capabilities that define a high-impact AI-powered ERP support platform:

Context-aware AI chat for ERP platforms

An AI assistant shouldn’t just understand language. Understanding context is just as important. The right solution would integrate deeply into the system and offer answers based on user role, screen, and task. 

For example, if a user is stuck in the purchase order module, Auralis would pick up the issue exactly and provide detailed next steps, not a link to a generic knowledge base article.

Embedded self-service directly within the ERP interface

A separate support workflow defeats the point of timely help, as it pulls users out of the ERP system and interrupts their work. Embedding self-service into the day-to-day workflows will foster real-time support. 

Role-based learning paths and resource recommendations

One-size-fits-all training is not valuable for all teams, say, providing the same training to a finance analyst and warehouse manager, especially in complex ERP environments. Effective AI solutions like Auralis deliver dynamic, role-specific guidance to enhance productivity and understanding and reduce friction.

Analytics for support trends, adoption gaps, and user sentiment

Detailed insights on ERP usage can help maximize workflows that are working and fix any gaps in adoption. Tools like Auralis offer visibility into how users interact with the system via dashboards that track support volumes, resolution rates, common issues, feature adoption, and even user sentiment, to take corrective actions.

Compliance (GDPR, SOC 2, HIPAA for Healthcare/Life Sciences)

Agent support or AI-driven support, compliance is non-negotiable because it includes user data and critical systems. It is especially true in regulated industries like healthcare or life sciences, where an AI ERP support solution must meet standards like GDPR, SOC 2, and HIPAA. 

Auralis is built with enterprise-grade compliance in mind, ensuring data security and privacy standards are upheld at every step of the support experience.

Real-world results: What AI can deliver in ERP support

Here’s what companies that have adopted intelligent AI-driven support platforms into their operations are seeing in the real world:

Support ticket volume reduced by up to 30%

Industrial Scientific, a global leader in gas detection and safety solutions, adopted Oracle’s AI-powered service desk to automate support operations. Using advanced AI capabilities resulted in time saving of over 185 hours, improved customer experience, a 30% operational efficiency gain, and enhanced data-driven decisions.

Onboarding time cut in half

Motion Industries, a major industrial parts distributor, had a hard time categorizing millions of products and adopted AI to put products in the right categories. The adoption slashed the onboarding time by half, showcasing how AI can expedite training and integration processes.

Hours saved per support staff every week

According to a study by Freshworks, employees who have embedded AI tools into their workflows are reported to save an average of 3 hours and 47 minutes per week. They use AI to handle the most mundane tasks like summarizing issues and handling repetitive activities, freeing up time for higher-value work.

Improved user satisfaction with lower friction

A case study featured on Parsimony highlighted a retail company’s experience using AI chatbots to improve both customer service and back-end operations. The combined implementation led to a 30% increase in customer satisfaction and a 15% improvement in overall operational efficiency.

Reduced reliance on external support vendors

Grant Thornton, in an audit report, revealed how the project implementation turned into a cautionary tale of project mismanagement, highlighting critical failures in governance, technical oversight, and vendor management that continue to impact the council’s core operations. It shows how important building internal capabilities is, and AI can be used to reduce this dependency.

Conclusion

ERP implementation isn’t the last step, companies face real challenges after the go-live phase.

Users need help navigating new software and workflows, while organizations need support to drive ERP adoption across departments and reduce operational costs. Traditional support models simply weren’t built to scale with this complexity.

AI-powered ERP support offers a smarter, more scalable alternative. 

By automating routine queries, guiding users in real time, and surfacing insights that help teams improve continuously, solutions like Auralis empower companies to support their ERP systems without adding headcount or compromising user experience.

Book a demo today.