In the last years, employee support costs have soared to record highs: the average helpdesk ticket cost is $26.51, a 30% increase vs two years ago, leading to greatly increased operational costs. The Mean Time to Resolve has increased to 9.72 hours, while the days tickets are backlogged are an average 12.1 now – resulting in high downtime costs. This is just a preview of how much agents’ and employees’ productivity hurts due to inefficient support – let alone the missed opportunities for revenue generation. Productivity loss ultimately leads to higher business costs, damaging the company’s profitability.
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That’s why companies are now turning to Generative AI: AI-powered solutions offer instant employee support and enhance efficiency, reduce costs, and improve the employee experience. Let's delve into how Gaspar AI, our Generative AI helpdesk, can significantly cut the costs of your company’s employee support. 

## Eliminate Level 1 support issues

Gaspar AI automates the resolution of the most common issues faced by employees. From mundane tasks like password resets and account unlocks to more intricate matters such as accessing specific folders or editing email lists and groups, Gaspar AI ensures these L1 issues vanish into thin air, along with their cost. Our Generative AI helpdesk solution leads to significant savings in labor costs, as it promotes self-service solutions where there is no need for human support agents to intervene.
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By instantly resolving 40% of routine issues via automation or by surfacing the most relevant solutions from various systems and knowledge bases, Gaspar AI empowers employees to address common requests independently. This not only reduces the burden on the helpdesk but also minimizes downtime and opportunity costs. For example, delays in resolving technical issues that can easily be autonomously addressed may prevent employees from accessing critical systems or tools, hampering their productivity and hindering business operations.  

## Maximize ROI on your existing investments

Investing in self-service resources is a common strategy for helpdesks aiming to empower employees and reduce ticket volume. Yet, without proper guidance, employees may still resort to submitting tickets for even the most basic issues. Gaspar AI addresses this issue head-on by meticulously combing through all available resources within the organization to provide tailored solutions. By leveraging existing investments in ITSM, Identity and Access Management systems, and knowledge bases through seamless integrations, Gaspar AI ensures that every support dollar yields tangible returns. 

## Offer 24/7 employee support at no extra cost

Unlike traditional human-operated helpdesks that work within specific business hours, Generative AI helpdesks are available round-the-clock. Employees can access support whenever they encounter an issue, no matter the time. This not only improves employee satisfaction by providing timely assistance but also reduces the need for additional staff to cover extended support hours, cutting all related costs.
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At the same time, it helps reduce downtime costs: every minute of downtime due to IT issues can result in lost productivity and revenue for businesses. By offering instantaneous responses and 24/7 availability, Gaspar AI minimizes downtime and its associated costs. By resolving issues quickly and efficiently, it helps companies maintain operational continuity and avoid the financial repercussions of extended downtime. 

## Streamline the ticket lifecycle

Gaspar AI accelerates the entire ticket lifecycle even for complex issues requiring expert attention. Our AI chatbot facilitates handoff to human agents: it helps users create a ticket by simply filling in a form on Slack or MS Teams, and then routes it to the right agent, alongside with any useful information and categorization. It sends notifications when needed and allows end users and helpdesk agents to follow up and check the status either on the ITSM platform or on Slack and Teams, until the ticket is resolved. This automation helps close the tickets faster, and minimizes the time and resources spent on escalations, resulting in cost savings for companies.  

## Take command of software spend

The inefficiencies surrounding software licenses can lead to significant financial waste for large companies. Gaspar AI empowers organizations to take control of their software spend by provisioning licenses instantly, just by requesting it from our Virtual Agent. It also accelerates the process of obtaining the necessary approvals and helps reclaim unused licenses. This approach not only reduces costs but also ensures that employees have timely access to the software they require to excel in their roles. 

## Scale employee support with no additional spend

Gaspar AI’s Generative AI helpdesk offers scalability and flexibility to adapt to changing business needs and fluctuating support demands. Whether supporting a small team or a large enterprise, our AI-powered platform can efficiently handle a high volume of support requests without compromising on quality or performance. This scalability ensures that companies can effectively manage support costs without sacrificing service quality or needing additional headcount.

## Cut down your costs with Gaspar AI's Generative AI helpdesk

Gaspar AI offers an intuitive solution that addresses common challenges while driving significant cost savings. By automating routine tasks, enhancing support quality, maximizing ROI on existing investments, empowering employees with self-service solutions, streamlining ticket lifecycles, and taking command of software spend, Gaspar AI paves the way for a more efficient and effective support ecosystem. An employee helpdesk ticket costs just $1 when you deploy Gaspar AI, as opposed to $26.51 on average when you don’t. The choice is yours: do you want to keep spending your precious IT budget on non-value-adding projects, or finally start implementing high-impact activities?
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If you’d like to learn more about cutting down your helpdesk costs while improving your employee support operations and experience, [try Gaspar AI for free](https://www.gaspar.ai/free-trial-signup) or [schedule a free demo](https://www.gaspar.ai/demo-request). 

_*Source: https://www.metricnet.com/_  

Slash support costs in half with a Generative AI helpdesk

Learn all the different ways our Generative AI helpdesk can help you reduce your employee support costs and decrease your ticket cost to $1. Read our blog!

Slash support costs in half with our Generative AI helpdesk

Chatbots and AI-powered solutions have been around for a while now, but it’s only in recent years that they’ve gained real popularity among users and businesses alike, thanks to the great progress of Generative AI. You might remember Eliza, the first-ever chatbot that acted as a psychotherapist, or maybe you’ve used Clippit and you’re left with a sour taste in your mouth. Clippit (a.k.a. Clippy) was an early conversational assistant in MS Office that spoke at you rather than with you. Clippy greeted and treated repeat users as if they had never used the program before, earning widespread hate. It was less of an assistant and more of a bottleneck.
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Since then, conversational AI assistants have evolved to being an indispensable part of our lives – personal (think Siri and ChatGPT) and work (think Microsoft copilot, Gaspar AI and more). Thankfully, they’ve also become great helpers, earning widespread love thanks to Generative AI advancements. It’s become imperative to deploy Generative AI in every business: it transforms business operations by enabling them to automate tasks, create new products and services and elevate customer experiences – ultimately leading to a better bottom line.
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Gaspar AI is one such Generative AI solution. If you’re unsure about how you can use it and what the platform offers, this blog post is for you. You will discover multiple use cases of Gaspar AI across your company and understand why your employees and support teams will be better-off with our AI helpdesk by their side. 

 

## First, what is Gaspar AI?

Gaspar AI is a secure and always available Generative AI helpdesk platform that uses Generative AI for smarter and more efficient employee support. Thanks to advanced language models, it offers dynamic, human-like conversations, seamlessly integrating with various communication channels such as Slack and MS Teams, commonly used apps and IT systems. It empowers employees to act, search, query, and generate content across a multitude of enterprise applications.  

 

## What are Gaspar AI’s main components?


Our AI helpdesk blends several [advanced technologies](https://www.gaspar.ai/blog/gaspar-generative-ai-helpdesk) to deliver sophisticated automation and support, including: 

- **Conversational Interface**: Using technologies such as large language models (LLMs), natural language processing (NLP), and natural language understanding (NLU), it is possible to interpret and comprehend free-form requests. Processes including semantic analysis, entity extraction, and intent recognition enable smooth and coherent dialogues. 

- **[Retrieval Augmented Generation](https://www.gaspar.ai/blog/retrieval-augmented-generation-and-enterprise-helpdesk) (RAG)**: This involves two processes: retrieving relevant information from an extensive data source and generating a contextually enriched and accurate response which integrates the retrieved information. This step is crucial as it ensures that the output is not just factually accurate but also linguistically coherent and contextually apt.  

- **Plugins**: They are specialized components that execute planned actions. Each plugin is custom-built for specific tasks and system integrations, such as resetting passwords in Okta or adding accounts in Google Workspace. When combined, they automate processes seamlessly across your existing systems, leveraging your current setup. 

- **Generative Summarization**: Our AI model consolidates information and produces clear, accurate, human-like responses in natural language and in a digestible format, customized to each employee inquiry. 

- **Act across systems**: Efficient integration ensures seamless transitions between conversational comprehension, solution strategy, process automation, and summarization. 

- **Trust Mechanisms**: Our AI platform incorporates features such as citations, employee satisfaction review and human oversight to ensure accountability and safety.  

 

## Top 30 Gaspar AI Generative AI helpdesk use cases

The following 30 use cases highlight the extensive capabilities of Gaspar AI’s helpdesk across various enterprise systems – there are more! As you review the list, observe how our solution is uniquely equipped to not only search and retrieve information from numerous sources and repositories, or guide users to perform actions, but also to automate and act.
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We designed Gaspar AI as one unified, user-friendly, easy-to-adopt, out-the-box platform. We recognize though that every business has unique needs, which is why we made our helpdesk platform scalable and offer the flexibility for organizations to extend the platform. With robust ML operations and high customization capabilities, it is easy to build and accommodate new use cases and extend to new languages while preserving critical business logic.  

### IT support and operations AI helpdesk use cases

An AI helpdesk can empower IT operations teams to automate the ITSM process and optimize support operations. 

1. **Hardware provisioning**: Ensure all employees get the hardware – be it laptop, mobile phone or tablet - they need when they need it. 

2. **Automatically reset passwords**: Thanks to Gaspar AI password resets can be automated, saving helpdesk teams up to 50% of their time as they don’t need to get involved in the process anymore. 

3. **Software provisioning**: Enable employees to have access to the right applications and better manage licenses. 

4. **Account management**: Create new accounts, delete old ones, better manage existing ones. 

5. **MFA removal**: Easily remove the MFA from a specific account. 

6. **Provide Generative AI-powered search on the Jira SM support portal**: Allow employees to get summarized answers straight from Confluence on JSM. 

7. **Offer quick and easy ticket creation on Slack or MS Teams**: For issues that need human attention, employees simply fill in a form on Slack or MS Teams to describe their issue (they can even attach screenshots and images), and a ticket is created on your ticketing platform.  

8. **Ticket management on Slack or MS Teams**: IT agents can see their tickets’ status, any pending approval requests, daily statistics and SLAs on Slack and MS Teams at any time. 

9. **Intelligent ticket triage**: Our helpdesk helps you promptly manage tickets. With its NLP capabilities, it analyzes the tickets, categorizes them, and assigns them to the right agent (depending on their expertise and availability). Moreover, it asks follow-up questions and interacts with the user to get more information for prompt resolution and accurate categorization. 

10. **Identify priority automation projects**: With AI-powered insights, IT Operations teams can prioritize projects that will have the highest impact on the business bottom line. 

11. **Enable easy, no-search knowledge access from multiple sources**: Gaspar AI integrates with knowledge bases (such as Confluence, Notion, Coda, Helpjuice and more), internal sources and repositories (e.g. Sharepoint, Dropbox, Google Docs) to ingest and index information, and then answer employee questions without human intervention and with no need to look for it.  

12. **Knowledge base augmentation**: Our AI helpdesk uncovers the most common employee issues and identifies existing knowledge gaps. IT teams can fast-track the relevant content creation to enrich the company’s knowledge base and offer more opportunities for self-service. 

13. **Track key IT metrics**: On Gaspar AI’s Admin Hub, IT managers can track their chatbot’s and platform’s performance. They also monitor which features, capabilities, and resources employees find valuable, compare performance over time and take data-driven action. 

14. **Customize field values on Jira**: IT teams can add a new value to a configured custom field in Jira. 

15. **Enable Generative AI capabilities on Atlassian Data Center**: The only GenAI solution that works for Atlassian Data Center customers. 

 

### HR AI helpdesk use cases

Our Generative AI helpdesk tackles routine HR tasks and offers immediate support: 

16. **Request time off**: Streamline the time-off approval process and allow for quicker approvals. 

17. **Offer access to health insurance information**: Offer employees a straightforward way to retrieve critical information regarding their health insurance benefits. 

18. **Review retirement plan balance**: Enable employees to promptly check their retirement account balance and access important information regarding their retirement plan. 

19. **Find out PTO balance**: Offer employees quick and easy access to information tailored specifically to their needs and employment situation. 

20. **Speed-up onboarding**: Make the process swift and delightful for new hires, ensuring no crucial steps are missed. 

21. **Facilitate offboarding**: Allow for a smooth offboarding process that keeps company data secure by automating the process. 

22. **Automate reminders for performance reviews**: Ensure that all employees complete their performance reviews on time by sending reminders on Slack and MS Teams.  

23. **Update the organizational structure**: When employees move across the company, easily change the organizational unit of an account. 

24. **Send announcements for company news**: Make sure that your company updates are not staying hidden and unread in the employees’ inboxes by sending automated updates on Slack and MS Teams. 

 

### Sales AI helpdesk use cases

Offer your Sales reps quick and easy access to information tailored specifically to their needs: 

25. **Access their sales contracts**: Sales reps ask our Generative AI Virtual Agent any contract-related question and it answers with information tailored specifically to them.  

26. **Find out payment and credit policies**: Empower your Sales team to quickly respond to prospects’ questions by giving them instant access to the information they are looking for. 

27. **Know their projects’ deadlines**: Sales reps ask our AI chatbot to give them an update and they instantly know what’s urgent and what’s not. 

 

### Collaboration AI helpdesk use cases

Collaboration platforms such as [Microsoft Teams](https://www.gaspar.ai/blog/using-ms-teams-for-it-support) and [Slack](https://www.gaspar.ai/blog/employee-helpdesk-on-slack) provide ideal environments for our AI helpdesk to deliver added value through: 

28. **Request access to shared folders**: Employees effortlessly locate and ask our AI helpdesk chatbot for access to specific folders.  

29. **Get how-to instructions**: Empower your workforce to instantly find the information they are looking for: IT troubleshooting, VPN and network access, security FAQs, and much more.  

30. **Task notifications**: Send proactive reminders to employees about upcoming tasks and deadlines to boost productivity and minimize missed assignments. 

31. **Create new groups and email lists**: Allow employees to easily create a new group or email list by asking for information such as name, purpose, members, and any necessary permissions. 

32. **Add people to and remove them from groups and email lists**: Effortlessly add employees to groups and distribution lists, or remove them. 

33. **Access shared calendars**: Enable employees to access shared calendars such as vacation calendars in seconds, adhering to existing permissions. 

34. **Manage people in Slack channels**: Make it easy to add or remove people from Slack channels. 

 

**If you’re curious to learn more about our use cases or see Gaspar AI in action, please [book a free meeting](https://www.gaspar.ai/demo-request)!**  

Explore how you can use Gaspar AI's helpdesk, designed to enhance employee support and streamline issue resolution across various enterprise systems.

30+ GenAI helpdesk use cases for your business

Frustrating for both users and administrators, password management can be a challenge to manage in any organization. One lost or stolen password may be the crack in your organization's foundation, allowing an attacker to slip in.
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Resetting user passwords is a routine yet essential task for IT service and help desks. However, while it may seem straightforward, it is tedious for the IT staff, unproductive for everyone and very costly for companies. Given that passwords are still the primary authentication method for many businesses, addressing this issue is extremely important.

## Why are account lockouts and password resets so common?

From the user's perspective, creating passwords may seem simple, but remembering them is a different story. With strict character requirements, many users resort to reusing passwords, leading to forgetfulness. This often results in either getting locked out of their accounts or requesting frequent resets.
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From a business standpoint, despite updated guidelines from [NIST](https://pages.nist.gov/800-63-3/), periodic password resets remain common practice. Password age limitations in Active Directory enforce these resets, yet they often lead to weaker passwords and account lockouts due to procrastination.
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Additionally, most users have about [100 individual passwords to manage](https://tech.co/password-managers/how-many-passwords-average-person#:~:text=How%20many%20passwords%20does%20the,repeat%20passwords%20or%20password%20elements.), which increases the likelihood of forgetfulness and errors, even with password managers. This highlights the need for a more efficient approach to password management. 

## How password resets hurt the bottom line

Password resets may seem like an easy problem to solve, but they are not, and if you add on top the volume of requests, it makes them an extremely time-consuming, repetitive, boring task.
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20% to 50% of all IT help desk tickets each year are for password resets according to the Gartner Group, and password tickets consume 31% to 40% of the help desk's time. Each reset ticket incurs substantial costs: [Forrester Research](https://conduitstreet.mdcounties.org/2020/03/24/the-true-costs-of-password-management/) estimates that one password reset can cost $70. These expenses encompass IT staff time, resources (using the necessary backend infrastructure) and lost employee productivity, so yearly costs for these common requests seem unreasonable. For instance, for a 1,000-employee company, this leads to a $70,000 yearly cost, assuming that every employee will need at least one password reset (most probably, they will need more).
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Regarding lost productivity, each time a user undergoes the password reset process— which involves pausing work on a project, contacting the help desk, waiting on hold, waiting for the reset, selecting a new password, and then logging back in—they are essentially costing the company productive time. In a study conducted by Forrester, researchers discovered that employees spend an average of eleven hours annually grappling with password issues. When extrapolated across a company with hundreds or thousands of employees, these lost hours translate into millions of dollars in lost revenue.
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Plus, when a user is locked out, the password reset takes priority over other vital tasks since that user can no longer work. Any organization's priority would be to get that individual productive once again. Thus, a password reset necessarily diverts a helpdesk's attention from the strategic and impactful tasks they would be working on. 

## Automated password reset with Gaspar AI helpdesk

Timewise and cost-wise, password resets are bad. Thankfully, with Gaspar AI you can kiss your password reset tickets goodbye! When you install Gaspar AI, you can integrate with password management applications, including SSO and MFA apps, and enable the related automation. Employees who forget a password will ask Gaspar (our AI chatbot) for a password reset. In seconds, Gaspar will identify the employee thanks to the relevant plugins and provide the necessary temporary password to the employee to reset it. Then, the employee will choose a new password, and that’s all! Their password is changed across all places that use it without any human intervention.
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**If you get a ton of these questions every month, [schedule a demo](https://www.gaspar.ai/demo-request) with us and give your employees the gift of time.** Imagine the things your helpdesk team could do when they get all this password reset tickets time back. :) 

automated password reset with Gaspar AI to save money

Struggling with password resets? Discover how Gaspar AI automates them, saving you time and money and boosting productivity.

Password resets are costing you $70k/year. Automate them.

If you are an Atlassian customer, you are likely considering their virtual agent to boost your helpdesk team’s and employees’ productivity, accelerate work and streamline your support operations. At the same time, you are not sure about the exact features and automation you will get; or you might be a Standard or Data Center customer so not eligible to deploy it.
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In this blog post, we delve into Atlassian’s features and explore how Gaspar AI can be a meaningful AI helpdesk alternative or a complementary platform. We have also created a useful [infographic](https://gaspar-www.sfo3.cdn.digitaloceanspaces.com/488983947edec9cd6d6f49f3d1561120.pdf) that compares the two virtual agents to help you quickly navigate your options. 

## What is Gaspar AI?

Gaspar AI is your AI helpdesk partner that empowers your team and employees to perform better and be more productive by getting instant support and ultimately driving your company's success. Gaspar AI automates repetitive tasks and workflows, answers questions in seconds, optimizes knowledge management and automatically resolves more than 40% of employee issues – all within your company's chat platform.
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Our helpdesk offers a [Generative AI Virtual Agent on Slack, MS Teams and Jira SM](https://www.gaspar.ai/blog/ai-employee-helpdesk-on-slack-msteams-jira) support portal trained with best-in-class LLMs to understand employee questions' context and intent and provide instant resolution. Gaspar, our AI chatbot, can dynamically ask follow-up questions and combine multiple plugins until users get accurate solutions.
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It also offers no-code Workflow Automation to streamline repetitive processes, and an Admin Hub where IT managers can review performance, get business insights and AI recommendations about high-impact automation and content that’s missing from your knowledge base. 

### Main AI helpdesk features

- Generative AI chatbot on Slack, MS Teams and [Jira SM support portal](https://www.gaspar.ai/xence-ai) for quick employee support 
- Instant resolution of more than 40% of issues 
- GenAI-enabled Knowledge Management 
- Slack and MS Teams accessible approvals and automation 
- Interactive notifications via Slack and MS Teams 
- No-code automation hub 
- Ticket automation and smart routing 
- Automated employee onboarding and offboarding 
- Multi-channel support  
- 30+ out-the-box [integrations](https://www.gaspar.ai/integrations) with most used apps 
- Admin Hub to customize the platform and review everything support-related 
- Powerful analytics with useful dashboards and KPIs 
- AI-powered insights to optimize your knowledge base and automations 

#### Pros

- Available to all customers, with unlimited capabilities and usage 
- Increased flexibility and multiple options for our chatbot: deployment on Slack, Teams or [JSM](https://www.gaspar.ai/xence-ai) 
- Out-the-box automations – no need for manual work 
- Integration with multiple Knowledge Management systems e.g. Confluence, Coda, SharePoint, Google docs, Notion, etc.
- Intuitive and customizable interface and platform 
- Super fast deployment 
- AI-powered for smart diagnosis and problem-solving 
- Integration with various enterprise software enhances service management functionalities 
- Implementation on Cloud, Data Center or other infrastructure 

#### Cons

- Lack of an online community 
- Workflow automation capabilities can be further enriched 
- No AI-powered new content generation e.g. for new knowledge articles 

## What is Atlassian’s Virtual Agent?

The Atlassian virtual agent with Atlassian Intelligence automates support interactions to free up agent time and deliver service at scale. With a built-in AI engine that leverages Natural Language Processing, it offers fast, conversational support, automating Tier 1 support issues. 

### Main features

- AI-powered answers on Slack and JSM help center (beta)
- Creation of custom intents  
- Automated web requests for basic support issues 
- Low/no code flow builder 
- Insights about the virtual agent’s effectiveness that help identify ways to optimize your intents and knowledge base 
- Ticket routing to the right team with pre-gathered context for complex issues  

#### Pros

- Online community for help 
- Easy to use with the rest of Atlassian products 
- Automated issue creation on Jira SM when no request resolution is possible via the virtual agent 

#### Cons

- Available only for Premium and Enterprise customers
- Available only on Cloud 
- Works only on Slack for now - JSM help center is in beta – so limited flexibility
- Offers AI summaries (in beta) for Smart Links from Confluence, Jira and Google docs only.
- Need to manually create intents and conversation flows 
- No workflow automation 
- No approvals automation across different apps
- Few integrations – works in the Atlassian environment 
- Integrates with Confluence only and no other knowledge management systems  
- Mix of paid and free capabilities 

## Complement your Atlassian tools with Gaspar AI’s helpdesk platform

Gaspar AI is a more holistic solution that comes with added features - including out-the-box automations - on top of the virtual agent. Our AI helpdesk unveils exclusive functionalities that can be tailored to your company and maximize the use of your Atlassian products with no need to switch any apps or transition to new tools. You can discover all the extra capabilities you get in our informative [infographic](https://gaspar-www.sfo3.cdn.digitaloceanspaces.com/488983947edec9cd6d6f49f3d1561120.pdf).
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You can thus improve your employee support efficiency and effectiveness. Noteworthy features include: 

- **Generative AI**: Unveiling a cutting-edge AI assistant that swiftly resolves employee issues with no human intervention.  
- **Jira SM, Slack and MS Teams chatbot integration**: user-friendly interface that facilitates real-time problem-solving. 
- **Agile Knowledge Management**: Empower your team with a dynamic knowledge base that evolves thanks to AI-powered recommendations. 
- **No code automation**: Unleash the power of automated workflows with ease. 
- **Available to all Atlassian customers, Cloud and Data Center**: no usage limits, no exclusivity, no price premiums. 

**If you'd like to learn more about how Gaspar AI can transform your support operations and be a great asset to your company, [schedule a free, personalized demo](https://www.gaspar.ai/demo-request).**  

### [Atlassian virtual agent and Gaspar AI](https://gaspar-www.sfo3.cdn.digitaloceanspaces.com/488983947edec9cd6d6f49f3d1561120.pdf)

Wondering whether to go for Atlassian chatbot? Read our blog to understand all the features and what chatbot and helpdesk alternatives you have.

Gaspar AI and Atlassian virtual agent: everything you need to know

The enterprise helpdesk responsible for employee support is undergoing a huge transformation. The goal? To end the slow issue resolution (Mean Time To Resolve is almost 27hrs!), the increasing ticket volume and the growing costs. The incorporation of Generative AI in internal employee support across the enterprise yields tangible benefits. By adopting an AI enterprise helpdesk, companies can automate repetitive process, offer instant answers and resolve routine issues in seconds, significantly reducing ticket volume and costs.
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While generative AI tools gain popularity, the persistent issue of hallucinations - plausible sounding but incorrect responses to users’ queries - hinders their enterprise adoption. These misleading responses pose significant risks in critical business interactions. Enter retrieval-augmented generation (RAG), a technique that can reduce hallucinations, thus revolutionizing enterprise AI integration. It is favored in enterprise chatbots for its ability to integrate company-specific data, enhancing AI grounding. This approach has transformative potential across various sectors including workplace support, offering a competitive edge. 

## Understanding retrieval-augmented generation (RAG)

RAG is a sophisticated AI mechanism that enhances the functionality of LLMs by integrating a dynamic retrieval system. This system allows LLMs to access and utilize external, up-to-date data sources under specific instructions, thereby helping them generate more accurate and contextually aware responses.
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RAG combines two processes: retrieving relevant information from an extensive data source and generating a contextually enriched response based on this retrieved data. This is done thanks to two components:  

1. **Information Retrieval**: The first step is to conduct a semantic search within a data source. When RAG receives a query, it utilizes advanced algorithms to navigate this source, identifying the most relevant data in relation to the query. The retrieval mechanism is designed to understand the semantic relationships between the query and the data source contents, ensuring that the data selected is contextually aligned with the query's intent.  
2. **Natural Language Generation (NLG)**: The second phase involves NLG, where the LLM processes the retrieved data and generates an accurate response which integrates the retrieved information as well. This step is crucial as it ensures that the output is not just factually accurate but also linguistically coherent and contextually apt. 

Through these components, retrieval augmented generation significantly amplifies the capabilities of LLMs, especially for tasks requiring them to retrieve relevant information. By incorporating this retrieved information, RAG can produce more informed and contextually relevant outputs, reducing the likelihood of generating hallucinations or incorrect responses. This makes them invaluable tools in various enterprise applications where prompt and precise information is key.  

## Why is RAG better for the AI-powered enterprise helpdesk?

RAG blends text generation with information retrieval to enhance the accuracy and relevance of AI-generated content. This is particularly enticing for enterprise applications where up-to-date factual knowledge is crucial. Businesses can choose enterprise helpdesks that use RAG with foundation models to create more efficient and informative chatbots and virtual assistants.
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RAG is recommended for data that change periodically in small periods of time (dynamic data), and this is what makes it the most appropriate solution for the enterprise helpdesk. Using RAG, an AI helpdesk vendor can gather a ton of structured and unstructured company information, documents, etc., and feed it into a model without having to fine-tune or custom train it. A RAG-based AI helpdesk can generate company-specific answers from almost any external data source, without making any adjustment.  

### Enhancing response accuracy and relevance

Since company data continuously change, integrating RAG into the AI helpdesk ensures that responses to employee queries will never be outdated, generic or irrelevant. By incorporating contextual, real-time, company-specific information from a knowledge base, RAG mitigates the risk of generating misleading or incorrect responses, thus increasing reliability and improving employee support efficiency. RAG ensures LLMs use the most current data, vital for tasks requiring the latest information for decision-making.  

### Scaling beyond fixed context windows

RAG allows LLMs to access vast data pools beyond their fixed context windows, crucial for enterprises with large-scale, dynamic data. This enhances information processing and model scalability. 

### Increased speed and reduced costs

Bypassing the need to store all knowledge directly in the LLM also reduces model size, which increases speed and lowers costs. This means that RAG-based solutions can be more cost-efficient alternatives that also drive higher productivity. 

## Challenges and considerations when implementing RAG in the enterprise helpdesk

While retrieval-augmented generation offers significant benefits for the enterprise helpdesk, several challenges may arise when using this technique: 

- **Data quality**: RAG heavily relies on the quality and relevance of the data in the knowledge base. Inaccurate or outdated information can lead to incorrect responses, undermining the model’s effectiveness. Maintaining an updated knowledge base with high-quality content is crucial.  
- **Knowledge base size and coverage**: RAG's effectiveness depends on the knowledge base's size and coverage. Limited or incomplete knowledge bases may restrict the system's ability to retrieve relevant information, leading to suboptimal performance. 
- **Handling ambiguity and contextual understanding**: RAG may struggle with ambiguous queries or nuanced contextual understanding. Resolving ambiguity and accurately interpreting context remains a challenge, especially in complex or specialized domains. 
- **Ethical and privacy concerns**: Retrieving information from large datasets raises concerns regarding data privacy, security, and ethical considerations, especially when dealing with sensitive or proprietary information. 

## Integrating RAG in the enterprise helpdesk for elevated functionality

Integrating RAG in the AI-powered enterprise helpdesk significantly elevates its functionality, making it the most effective solution for employee support. It offers more accurate responses and allows for better-informed decision-making. Gaspar AI is such a solution.
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Our AI helpdesk platform integrates with various knowledge bases (such as Coda, Notion, Google Docs, Confluence and more) and uses RAG to search and retrieve relevant information. Thanks to advanced NLP it generates accurate, helpful, human-like responses, ensuring that the generated answers are contextually appropriate, reliable and tailored to the employee's needs. Our platform is characterized by reduced hallucinations when compared to others: RAG mitigates the risk of generating misleading or incorrect responses that could lead to user frustration or worse, wrong decisions.
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Using Gaspar AI improves the quality, reliability, and efficiency of employee support interactions, leading to higher user satisfaction and improved productivity for both employees and support staff. If you’d like to learn more, you can [book a free demo](https://www.gaspar.ai/demo-request).  

Retrieval-augmented generation and the enterprise helpdesk

Discover how retrieval-augmented generation (RAG) is increasing enterprise AI adoption and positively impacting workplace support. Learn everything here!

Shadow AI - also dubbed “shadow IT” or “BYOAI,”- is a term describing unsanctioned or ad-hoc generative AI use within an organization that's outside IT governance. This can occur when individual departments or employees adopt AI-powered tools or solutions independently, often without the knowledge or approval of central IT or data management teams. That enterprising spirit can be great, in a vacuum—but eager employees may lack relevant information or perspective regarding security, privacy or compliance. This can expose businesses to a great deal of risk. For example, an employee might unknowingly feed trade secrets to a public-facing AI model that continually trains on user input, or use copyright-protected material to train a proprietary model for content generation and expose their company to legal action.
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Shadow AI is an issue often overlooked when thinking about the risks of inefficient and slow employee support. And that’s too bad: according to [Salesforce](https://www.salesforce.com/news/press-releases/2023/09/07/ai-usage-research/), 75% of users are looking to automate tasks at work by using generative AI. But eager employees may lack relevant information or perspective regarding security, privacy or compliance.  This can significantly increase the risk exposure for businesses. For instance, an employee could inadvertently disclose trade secrets by feeding them into a publicly accessible AI model that continuously learns from user input.
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As if IT departments didn't have enough on their plate, the adoption of generative AI is gaining momentum. As per the Salesforce survey, 52% of respondents noted a rise in their usage of generative AI since its initial implementation. This surge signifies that the challenge of shadow AI is not only here but is also expanding, posing a growing concern for IT.
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"The reality is, everybody's using it," said Matt Barrington, Americas emerging technologies leader at EY about recent [EY research](https://www.ey.com/en_us/consulting/businesses-can-stop-rising-ai-use-from-fueling-anxiety) finding that 90% of respondents used AI at work. "Whether you like it or not, your people are using it today, so you should figure out how to align them to its ethical and responsible use." 

## Why employees resort to shadow AI?

There are various reasons why employees resort to shadow IT, including: 

1. Perceiving the IT/helpdesk department as slow and unresponsive or lacking the expertise to manage new technologies effectively. Think about it: with the Mean Time to Resolve an issue being 26 hours, oftentimes they can’t be bothered to remain idle for so long and potentially be unproductive.  
2. Needing solutions for specific use cases that approved applications don't cover. 
3. Facing budget limitations that prevent the adoption of officially sanctioned enterprise-level versions of emerging technologies. 
4. Finding the technological and tooling constraints of approved projects too limiting for their needs. 


They thus turn to user-friendly Generative AI tools such as ChatGPT, which they can try out in their web browsers with little difficulty - without going through IT review and approval processes. The impulse is understandable, but shadow AI -- as with any sanctioned large language model (LLM) AI project -- presents various cybersecurity and business risks.  

## What are the risks associated with shadow AI?

Shadow AI can present various challenges and risks to companies, including the following: 

- **Functional risks**: Functional risks arise from the operational capabilities of an AI tool. Take, for instance, model drift, which occurs when the AI model deviates from its intended purpose due to changes in the technical environment or outdated training data. This deviation renders the model ineffective and potentially misleading, posing a functional risk to the company. 
- **Operational risks**: Operational risks pose threats to the company’s ability to conduct business effectively. These risks manifest in various forms. For example, a shadow AI tool might provide inaccurate advice due to model drift or might be hallucinating and generating false information. Acting on such advice could lead to wrong decisions.  
- **Data security and privacy concerns**: When using an unsanctioned AI system without proper oversight, there's a risk of sensitive data being mishandled or exposed, leading to potential breaches or compliance violations. For instance, a chatbot might ingest information included in an employee’s prompt; use it as training data; make it available to platform operators; and make it available to other users outside the company when answering their prompts. If the AI platform were to suffer a cyberattack, the data could also fall into cybercriminals' hands. Sharing such sensitive information with an LLM poses significant risks, including jeopardizing intellectual property, empowering competitors, violating data privacy regulations, eroding customer trust, and tarnishing the company’s reputation. 
- **Legal risks**: These materialize if shadow AI exposes the company to lawsuits or fines. Say the model advises leadership on business strategy. But the information is incorrect, and the company wastes a huge amount of money doing the wrong thing. Shareholders might sue. Lawsuits might also materialize if the shadow tool provides customers with bad advice generated by model drift or poisoned training data or if the model uses copyright-protected data for self-training. And, of course, violations of data privacy regulations could result in hefty legal penalties. 
- **Costs**: There can be wasteful or duplicative spending among shadow projects or between shadow and sanctioned ones. In some cases, shadow AI users may also waste money by failing to take advantage of volume and negotiated rates for similar, sanctioned technology. Consider, too, the opportunity cost stemming from shadow projects that ultimately fail because they do not follow company policies or good practices - that time and money could have been put toward other projects.  
- **Fragmentation and inconsistency**: Different departments or teams using disparate shadow AI tools can lead to inconsistencies in resource procurement, configuration and use.  
- **Control**: IT teams cannot see shadow IT resources, which means they can’t manage, organize and support them. 

## Unmasking shadow AI: how to get started

To address the challenges posed by shadow AI, companies need to implement robust governance frameworks and establish clear policies regarding the adoption and use of AI technologies. They should also encourage the collaboration between IT and business leaders to understand how various departments want to use AI. Additionally, centralizing AI deployment and management under the supervision of IT and data governance teams can help mitigate risks and ensure that AI initiatives contribute positively to the organization's overall success.
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However, as mentioned before, there is no guaranteed way to keep employees from using Generative AI to work more efficiently. Therefore, the most effective way to address Shadow IT is to provide an approved AI helpdesk platform. An AI employee helpdesk is a secure and always available support platform built for an AI-first world. Thanks to advanced language models, it offers dynamic, human-like conversations, seamlessly integrating with various communication channels and IT systems. It automates tasks and support resolution, and empowers employees to act, search, query, and generate content across a multitude of enterprise applications. Fueled by constantly improving generative models, AI-driven analytics for performance evaluation, and developer tools for customizable use cases, it's the future of assistance.  

## Addressing shadow IT challenges with an AI employee helpdesk

The AI helpdesk's swift and dependable issue resolution encourages employees to seek help from IT instead of resorting to unsafe fixes and shadow AI. Let's review how it addresses the main reasons why users resort to shadow AI in the first place. You will then understand why an AI employee helpdesk such as Gaspar AI can be your best ally in your fight against shadow IT.
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**1. Slow response times and lacking expertise** 

- **24/7 availability**: the AI helpdesk is available anytime, anywhere, so employees don’t have to rely on the agents’ work schedule or resort to unsecure fixes when the helpdesk team is not available. 
- **Instant resolution**: By automatically solving their most common issues, employees have no reason to seek help elsewhere. Also, by facilitating handoff to the right agent, they can resolve even the most complex issues easier and more quickly. 
- **Ease of use**: Thanks to LLM training, NLP and NLU, employees just talk to the AI helpdesk’s chatbot in everyday language on your company’s chat platform, e.g. Slack, MS Teams. They are instantly understood, engage in interactive conversations and get human-like answers. They now have one user-friendly, unified solution for their support. 
- **Accurate answers based on your company’s data**: All answers generated are precise and based on your company’s information, as opposed to using shadow AI. At Gaspar AI for instance, we use [Retrieval Augmented Generation](https://www.gaspar.ai/blog/retrieval-augmented-generation-and-enterprise-helpdesk) which means that our language model generates answers based on your knowledge base. 
- **AI trained with sector-specific datasets**: This means that answers accurately depict your company’s specific environment and context. 

**2. No approved solutions for specific use cases**  

- **AI customization**: It’s very easy to build specific uses cases with an AI tool. With Gaspar AI for example, you can [automate workflows ](https://www.gaspar.ai/blog/how-to-complete-employee-onboarding-in-under-one-minute)(e.g. employee onboarding) and connect systems without coding – just use our intuitive templates! 
- **Out-the-box integrations**: Most AI helpdesks come with ready-to-use integrations that offer solutions to the most common use cases.  

**3. No access to officially sanctioned solutions due to budget limitations** 

- **Low cost**: Contrary to what one would believe, an AI helpdesk can be a very cost-effective solution making it possible to be adopted at enterprise level. Gaspar AI, for example, has a cost of $4 per user monthly, therefore allowing even small companies to deploy it.   

**4. Limiting technological and tooling constraints of approved projects**

- **Scalability**: A well-chosen AI helpdesk is easy to scale and accommodate more use cases and increasing support demands.  
- **Flexibility**: AI employee helpdesks offer flexibility to connect with tools such as IT management systems and commonly used apps, covering most user needs. 
- **Multiple features**: A good AI helpdesk offers a wide variety of features such as issue resolution, ticket management, asset management, incident management, change management, business insights, analytics and reporting.  
 

## From shadow AI to safe solutions: harnessing the power of AI helpdesks

Security, IT and risk leaders should not expect shadow AI to go away any time soon. As new-generation LLMs become more numerous and diverse, there is every reason to expect shadow AI projects will multiply as well – an AI employee helpdesk is probably the safest and smartest solution. As generative AI usage becomes increasingly pervasive, companies will need to consider a broader strategy which will include adopting helpdesk tools that better meet business needs and encourage ethical and safe AI use. And data shows the effort is worth it. 76% of IT leaders believe GenAI will be significant if not transformative for their organizations, and 65% believe they will see meaningful results within the next year according to a [recent Dell survey](https://www.dell.com/en-us/perspectives/new-research-the-dell-genai-pulse-survey/?dgc=Af&cid=aithoughtleadership&lid=Forbes14).
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With an AI employee helpdesk such as Gaspar AI you can offer easy, instant, accurate and scalable support to end users minimizing their eagerness to seek solutions in unsafe places. You can rest assured that your company’s data and sensitive information will remain private. Any information collected from our customers is strictly confidential and will never be shared with other customers or utilized to train our generic AI model. The sole purpose of collecting these data is to enhance and personalize your individual model for an improved and tailored experience. What’s more, all generated answers and solutions adhere to existing permissions and access rights. Employees won’t be able to view or access information they are not supposed to.
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If you’d like to start addressing shadow AI projects today, you can [schedule a free demo](https://www.gaspar.ai/demo-request) where we will discuss your company-specific needs, show you around the platform and experience first-hand the magic of AI-powered support.
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_Citations:_

- _TechTarget, 10 top AI and machine learning trends for 2024, https://www.techtarget.com/searchenterpriseai/tip/9-top-AI-and-machine-learning-trends_ 
- _Forbes, What Is Shadow AI And What Can IT Do About It https://www.forbes.com/sites/delltechnologies/2023/10/31/what-is-shadow-ai-and-what-can-it-do-about-it/_  
- _TechTarget, Shadow AI poses new generation of threats to enterprise IT, https://www.techtarget.com/searchsecurity/tip/Shadow-AI-poses-new-generation-of-threats-to-enterprise-IT#:~:text=Operational%20risks%20come%20in%20many,%2D%2D%20i.e.%2C%20generating%20false%20information_
- _EY, AI Anxiety in Business Survey October 2023, https://www.ey.com/en_us/consulting/businesses-can-stop-rising-ai-use-from-fueling-anxiety_
- _The Dell GenAI Pulse Survey October 2023, https://www.dell.com/en-us/perspectives/new-research-the-dell-genai-pulse-survey/?dgc=Af&cid=aithoughtleadership&lid=Forbes14_

How to address shadow AI risks with an AI employee helpdesk

Discover the impact of shadow AI and how AI employee helpdesks offer secure, scalable, and ethical solutions to mitigate risks and enhance support.

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