AI Assistants: How They Work, Benefits, and Use Cases

AI assistants have come a long way from setting reminders and answering simple questions. Today, they can analyze complex documents, write code, research unfamiliar topics, and even complete tasks across connected applications.

But with so many tools available, what exactly counts as an AI assistant, and how do you know which one is right for you?

In this guide, we’ll explain how AI assistants work, how they compare to AI agents and traditional chatbots, and where they’re most useful. We’ll also look at seven popular AI assistants, including ChatGPT, Claude, Gemini, and Quiq, to help you understand what each one can do for your personal or professional needs.

TL;DR

• AI assistants help people complete tasks using natural language. They can answer questions, generate content, analyze information, and perform actions across connected applications.
• Modern AI assistants use large language models and natural language processing to understand requests. Advanced systems can also retrieve external information and execute authorized actions through integrations.
• AI assistants, AI agents, and chatbots serve different purposes. Assistants typically support human users, AI agents can independently work toward objectives, and chatbots provide conversational interfaces.
• Popular AI assistants include ChatGPT, Claude, Gemini, Microsoft Copilot, Perplexity, Notion AI, and Quiq. Each specializes in different applications, from personal productivity and research to enterprise customer service.
• The biggest benefits of AI assistants include faster access to information and reduced repetitive work. Businesses can also use them to support employees, improve customer experiences, and automate routine tasks.
• AI assistants have limitations, including inaccurate responses and data privacy risks. Users should verify important information, review access permissions, and maintain human oversight for sensitive actions.
• The best AI assistant depends on your specific use cases. Compare integrations, accuracy, pricing, and ease of use before choosing. For customer service teams, Quiq AI Assistants provide contextual guidance and execute authorized actions alongside human agents.

What are AI assistants?

AI assistants are software applications that use artificial intelligence to understand requests, provide information, and help people complete tasks. Instead of navigating menus or learning complicated commands, users can communicate with these tools through natural language, either by typing or speaking.

Modern AI assistants often use large language models (LLMs) and natural language processing (NLP) to interpret questions, understand context, and generate relevant responses. More advanced assistants can also connect to external applications, retrieve information, and perform actions on a user’s behalf.

You’ve probably already encountered several types of AI assistants:

• Personal assistants like Siri and Alexa can answer questions, set reminders, and control smart home devices through voice commands.
• Productivity assistants like ChatGPT and Microsoft Copilot help users draft documents, summarize information, and complete everyday work.
• Coding assistants like GitHub Copilot suggest code, explain programming concepts, and help developers troubleshoot errors.
• Customer service assistants help support employees find information, recommend responses, and resolve customer issues. For example, Quiq’s AI Assistants can guide human agents through conversations and perform actions in connected business systems.

The capabilities of an AI assistant depend on the technology behind it and the systems it can access. Some tools only generate text or answer questions. Others can retrieve live information, interact with business applications, or complete tasks with limited human involvement.

When evaluating an AI assistant, start with the work you need help with. Consider whether you need answers and recommendations or an assistant that can actually perform actions.

For example, summarizing a meeting requires very different capabilities from updating customer records in a CRM. The latter requires access to the relevant system, appropriate permissions, and safeguards against incorrect changes.

How do AI assistants work?

AI assistants combine natural language processing, large language models, and access to external tools to understand requests and help users complete tasks. Their capabilities depend on the information they can access and the actions they’re authorized to perform.

When you give an AI assistant an instruction, it generally follows four steps:

1. Interpret the request: Identify what you’re asking and what outcome you expect.
2. Understand the context: Consider relevant conversation history, instructions, and available user information.
3. Find relevant information: Retrieve information from connected sources when the task requires it.
4. Generate a response or take action: Answer your question, suggest what to do next, or execute an authorized task.

Simple assistants may only provide information. More advanced solutions, such as Quiq’s AI Assistants, can access business systems and perform actions while supporting human employees.

Here’s a closer look at the technology behind these capabilities.

Natural language processing and large language models

Natural language processing (NLP) allows computers to analyze and interpret human language, while large language models (LLMs) generate responses based on patterns learned during training.

Together, these technologies allow AI assistants to understand requests written in everyday language, including questions that don’t follow a predefined format.

For example, imagine asking an assistant:

“Can you find out why my order hasn’t arrived and help me get a replacement?”

Instead of looking for an exact keyword match, a modern assistant can identify the request as a delivery issue and recognize that you’re seeking a resolution.

Depending on its capabilities, it could then:

• Identify the customer’s request and relevant details.
• Ask for missing information, such as an order number.
• Generate an appropriate response based on available information.
• Determine whether it needs to access another system to investigate the issue.

Voice assistants add speech recognition to convert spoken requests into text. They can also use speech synthesis to deliver spoken responses. We explain the underlying technology in our guide to voice AI platforms.

Practical tip: Give an assistant a specific objective and include relevant constraints. For example, “Summarize this report in 200 words and highlight any findings related to customer retention” will usually produce a more useful response than “Summarize this.”

Understanding context and user intent

AI assistants can use context to interpret what users mean, rather than treating every message as an isolated request.

Suppose you’re using an assistant for task management. You ask it to create a project plan, then follow up with:

“Move the deadline to Friday and assign the remaining tasks to Sarah.”

A context aware assistant can recognize which project you’re referring to and determine which tasks need attention, provided that information is available in its current context or connected systems.

Context can come from several sources:

• Conversation history: Previous questions, instructions, and decisions made during the interaction.
• User preferences: Communication styles, preferred formats, and saved settings.
• Connected applications: Calendars, project management platforms, and other authorized software.
• Business rules: Instructions that define how the assistant should respond or which actions it can perform.

Some personal AI assistants can retain preferences or retrieve information across sessions. Others have access only to the current conversation.

Business assistants may also follow company policies. At Quiq, for example, we use Process Guides to give our assistants instructions about business objectives, available tools, and appropriate actions during customer conversations.

Practical tip: Before relying on an assistant for ongoing work, check what information it can remember, which applications it can access, and whether it can retrieve the context of previous interactions. Never assume it remembers information simply because you shared it earlier.

Retrieving information from connected data sources

Large language models learn patterns from training data, but they don’t automatically have access to current information or private company records.

To answer questions that require this information, AI assistants can use retrieval augmented generation (RAG). This technique allows an assistant to search external sources and use the retrieved information to help generate its response.

These sources might include internal knowledge bases, company documents, or live business applications.

For example, a customer service assistant handling a refund request could:

1. Retrieve the customer’s order history from a connected system.
2. Find the relevant refund policy in the company’s knowledge base.
3. Check whether the order meets the refund requirements.
4. Present the findings to a human agent or prepare an appropriate response.

This helps the assistant use current information rather than relying entirely on what the language model learned during training.

However, access to external information doesn’t guarantee accuracy. An assistant can still retrieve outdated documents, misunderstand the content, or produce an incorrect answer.

As we explain in our guide to retrieval augmented generation, connecting language models to trusted information sources can reduce these problems.

When evaluating an AI assistant, check whether it can:

• Retrieve information from the applications you already use.
• Reference the documents or records behind its answers.
• Respect user permissions when accessing sensitive information.
• Retrieve updated information without requiring the underlying model to be retrained.

For business applications, prioritize assistants that can show where their information came from. This gives employees a way to verify important answers before acting on them.

Executing tasks through integrations and APIs

Answering questions is useful, but some AI assistants can go further by taking actions in connected applications.

They do this through integrations, APIs, and tool calling. These capabilities allow the assistant to request an action from another system, such as creating a calendar event or updating a customer record.

Consider someone asking an assistant to organize an upcoming meeting.

A connected assistant might:

1. Check the user’s calendar for available time slots.
2. Identify a suitable meeting time based on the request.
3. Create the calendar event using an authorized integration.
4. Return a confirmation with the meeting details.

More advanced AI agents can use similar capabilities to work toward broader objectives, deciding which tools to call and what steps to take.

Some autonomous AI agents can complete multiple steps with limited human input. However, autonomy should depend on the task and its potential consequences.

For example, allowing an assistant to categorize incoming emails is relatively low risk. Giving it permission to issue refunds or modify financial records requires much stricter controls.

We cover the technical foundation behind these actions in our guide to LLM function calling.

When comparing AI assistants with the best AI agents for your needs, pay attention to four capabilities:

• Tool access: Which applications can the assistant read from or modify?
• Approval controls: Can you require human authorization before sensitive actions?
• Execution history: Can you review what the assistant did and which tools it used?
• Error handling: What happens when an integration fails or an action produces an unexpected result?

A free AI assistant may be perfectly adequate for drafting content, answering general questions, or organizing routine tasks. However, advanced integrations and autonomous execution capabilities may require a paid platform or additional configuration.

Practical tip: Start with tasks that are easy to verify and reverse. Test the assistant with realistic scenarios, review its actions, and expand its permissions only after you’ve established that it performs reliably.

AI assistants vs. AI agents vs. chatbots

AI assistants, AI agents, and chatbots can all communicate with users through natural language. However, their purpose, level of autonomy, and ability to perform tasks can vary considerably.

• AI assistants primarily help people complete tasks by providing information, generating content, recommending actions, or interacting with connected tools.
• AI agents work toward defined goals and can independently determine which steps to take, use available tools, and execute actions with varying levels of human oversight.
• Chatbots interact with users through conversational interfaces. Traditional chatbots follow predefined rules, while modern AI chatbots can use large language models to understand complex requests and generate responses.

These categories aren’t mutually exclusive. An AI assistant can use agentic capabilities, while an AI agent can communicate through a chatbot interface. The terminology describes how a system is used rather than establishing strict technical boundaries.

Here’s how they compare:

Feature	AI assistants	AI agents	Chatbots
Primary purpose	Help users complete tasks	Achieve defined objectives	Communicate with users
Autonomy	Usually operate with user guidance	Can plan and execute tasks independently	Depends on the underlying technology
Core capabilities	Answer questions, generate content, recommend or execute actions	Plan tasks, use tools, make decisions, execute workflows	Answer questions, guide conversations, collect information
Human involvement	Typically work alongside users	Can operate with limited supervision	Usually respond to user messages
Common examples	Microsoft Copilot, GitHub Copilot	Autonomous research agents, customer service AI agents	Website support bots, FAQ chatbots
Best use cases	Productivity, research, employee assistance	Complex workflows requiring multiple actions	Customer inquiries and conversational interfaces

Consider how each technology might handle the same customer service request.

A customer contacts an online retailer because their order hasn’t arrived.

A traditional chatbot might recognize the delivery question, provide a tracking link, and offer a predefined option to contact support.

An AI assistant could retrieve the customer’s order information, identify the delivery problem, and recommend an appropriate resolution to a human support representative. If authorized, it could also initiate a replacement request.

An autonomous AI agent could investigate the missing delivery, check company policies, determine whether a replacement is appropriate, and execute the necessary actions without requiring an employee to handle every step.

At Quiq, our AI Assistants work alongside human agents, providing contextual response suggestions, coaching, and the ability to execute authorized actions. Our AI Agents can manage customer conversations directly, using shared knowledge and integrations to resolve requests.

Which should you choose?

The best option depends on the work you’re trying to accomplish and how much control you want to retain.

• Choose an AI assistant when employees need help researching information, generating content, or completing tasks while remaining involved in the process.
• Choose an AI agent when you want software to execute multistep workflows and make decisions within established permissions.
• Choose a traditional chatbot when you primarily need to answer predictable questions or guide users through fixed conversational flows.
• Choose a modern AI chatbot with agentic capabilities when users need conversational support that can also access information and complete actions.

Before selecting a solution, ask vendors to demonstrate what happens when the software encounters missing information, an unexpected request, or an action requiring approval.

The most useful distinction is what the system can actually accomplish without human intervention. Product names alone won’t tell you whether an AI tool can retrieve information, perform actions, or reliably complete a complex task.

Examples of popular AI assistants

The AI assistant market includes everything from general purpose tools that help individuals with everyday tasks to specialized platforms designed for business operations.

Some assistants focus on writing and research. Others connect to business applications, analyze information, or execute tasks on behalf of users.

Here are seven popular AI assistants, what they do, and examples of how you can use them.

1. Quiq

Best for: Enterprise customer service and assisting human support agents.

Quiq provides AI Assistants that work alongside human customer service representatives during live conversations. Instead of simply suggesting responses, our assistants can retrieve customer information, provide contextual coaching, and take actions within connected business systems.

Our assistants share knowledge, tools, and Process Guides with our customer facing AI agents. This allows businesses to maintain consistent customer experiences whether a conversation is handled by an employee or AI.

Common use cases include:

• Real time agent assistance: Recommend responses, surface relevant knowledge articles, and guide employees through complex customer requests.
• Customer service automation: Process returns, update CRM records, and complete routine tasks without requiring agents to switch applications.
• Agent coaching: Provide contextual guidance based on company policies and the customer’s current situation.
• Multilingual support: Help employees communicate with customers who speak other languages.

Businesses can also use Quiq AI Studio to create custom AI agents, configure their behavior, connect business systems, and test their performance before deployment.

2. ChatGPT

Best for: General productivity, content creation, research, and data analysis.

ChatGPT is OpenAI’s conversational AI assistant. Users can ask questions, generate written content, analyze uploaded files, and get help with everyday work through a conversational interface.

Its flexibility makes it useful across many industries. You can use it as a writing assistant, research partner, or analytical tool without needing programming knowledge.

Common use cases include:

• Content creation: Draft emails, outline articles, rewrite documents, and brainstorm campaign ideas.
• Data analysis: Upload spreadsheets to identify trends, generate charts, and investigate unusual changes in performance.
• Research: Find information, compare products, and summarize documents.
• Programming: Explain unfamiliar code, identify errors, and generate code snippets.

ChatGPT offers a free tier with access to core capabilities, including limited file uploads and data analysis. Paid plans provide higher usage limits and additional functionality.

Although ChatGPT can assist with customer service tasks, businesses should consider data access, accuracy controls, and system integrations before using it for live support. We explore these considerations in our guide to using ChatGPT in customer service.

3. Claude

Best for: Long document analysis, writing, coding, and complex reasoning.

Claude is an AI assistant developed by Anthropic. It can analyze uploaded documents, explain technical subjects, write code, and help users work through problems that require several reasoning steps.

One of its useful capabilities is Artifacts, which allows users to create and edit standalone documents, interactive tools, and visual outputs alongside their conversations.

Common use cases include:

• Document analysis: Review lengthy contracts, research papers, and internal reports to identify important information.
• Writing assistance: Improve drafts, edit technical documentation, and adapt content to specific audiences.
• Software development: Generate code, troubleshoot errors, and explain existing applications.
• Interactive content: Create simple web applications, visualizations, and dashboards using Artifacts.

Claude has a free plan with usage limits, while paid subscriptions provide additional capacity and capabilities.

For organizations evaluating Claude or other language models, our guide to enterprise LLMs explains important considerations around model behavior and brand safety.

4. Google Gemini

Best for: Personal productivity, research, and working with Google applications.

Gemini is Google’s AI assistant, available as a standalone conversational application and through integrations with Google’s products.

It supports text and voice conversations, can analyze uploaded information, and helps users create content. Eligible Google Workspace subscriptions also provide Gemini capabilities inside applications such as Gmail, Google Docs, and Google Sheets.

Common use cases include:

• Email management: Summarize lengthy email conversations and draft replies in Gmail.
• Document creation: Generate initial drafts and revise existing content in Google Docs.
• Research: Explore unfamiliar subjects, ask follow up questions, and analyze information.
• Personal assistance: Use voice conversations to ask questions, plan activities, and get help with everyday tasks.

Gemini offers free access with model and usage restrictions. More advanced capabilities require eligible Google AI or Workspace subscriptions.

Gemini models can also support enterprise applications beyond Google’s own products. For example, our AI Studio allows businesses to select from multiple language model providers, including Google, when building AI agents.

5. Microsoft Copilot

Best for: Workplace productivity and organizations using Microsoft 365.

Microsoft Copilot helps users generate content, answer questions, and complete tasks through natural language.

Its Microsoft 365 integrations are particularly useful for employees who spend much of their workday in Word, Excel, Outlook, or Teams. The capabilities available inside these applications depend on the user’s subscription and organizational settings.

Common use cases include:

• Spreadsheet analysis: Explore data in Excel, identify patterns, and generate explanations of numerical results.
• Meeting productivity: Summarize Teams meetings and identify decisions or assigned actions.
• Document preparation: Draft reports in Word and turn existing information into presentations.
• Email assistance: Summarize conversations and prepare responses in Outlook.

Microsoft offers a free Copilot experience for general questions and content generation. Access to advanced Microsoft 365 integrations depends on the relevant license.

Copilot is also an example of how AI can assist employees without taking over their responsibilities. In customer service, similar capabilities are often described as real time agent assist.

6. Perplexity

Best for: Research, finding current information, and exploring unfamiliar topics.

Perplexity is an AI search and research assistant that retrieves information from the web and generates answers supported by source links.

Rather than requiring users to open multiple search results individually, it combines relevant findings into a conversational response. You can then ask additional questions to narrow your research.

Common use cases include:

• Market research: Investigate competitors, industry developments, and emerging technologies.
• Fact checking: Find supporting sources for factual claims and verify information against original publications.
• Product comparisons: Research software capabilities, pricing structures, and available alternatives.
• Academic research: Discover relevant publications and explore questions related to a particular subject.

Perplexity’s free plan provides basic searches and limited access to more advanced search capabilities. Paid subscriptions expand research features and model access.

Its emphasis on retrieving external information also illustrates an important concept behind AI assistants: grounding responses in relevant sources. We explain this in our guide to retrieval augmented generation.

7. Notion AI

Best for: Knowledge management, project organization, and team productivity.

Notion AI integrates artificial intelligence directly into Notion’s workspace, where teams manage documents, project information, and internal knowledge.

It can help users create content, find information, and organize work without leaving the application.

More advanced features allow users to search connected business tools, generate research reports, and use Notion Agent to complete tasks within their workspace.

Common use cases include:

• Knowledge management: Find answers within company documentation and connected applications.
• Project management: Create task databases, organize project information, and update workspace content.
• Meeting documentation: Transcribe meetings, summarize discussions, and capture action items.
• Content preparation: Draft internal documents, rewrite existing pages, and translate information.

Notion offers a free plan, but Notion AI access is limited to complimentary responses unless users upgrade to an eligible Business or Enterprise subscription.

Notion illustrates how useful AI assistants can become when they have access to relevant organizational knowledge. The same principle applies to customer support, where connecting AI to company information is an important part of AI customer service solutions.

Pros and cons of using AI assistants

AI assistants can make everyday tasks easier, whether you’re organizing your personal schedule or managing customer conversations across a large business. However, their usefulness depends on accuracy, available integrations, and how much control users have over their actions.

Understanding the advantages and limitations of AI assistants for business can help you decide where to use them and when human involvement is still necessary.

Pros of using AI assistants

AI assistants excel at repetitive work and tasks that require processing large amounts of information. Some benefits apply to individual users, while others become more valuable when assistants connect to company systems.

• Faster access to information: Instead of searching through multiple websites or documents, users can ask questions and receive summarized answers. For example, a student might summarize research papers, while a customer service representative could retrieve company policies during a live conversation.
• Less time spent on routine tasks: Personal AI assistants can organize calendars, draft emails, and prepare shopping lists. Businesses can use custom AI assistants to categorize support requests, update customer records, or prepare meeting summaries.
• Better productivity at work: AI assistance can help employees complete tasks without constantly switching applications. Developers can troubleshoot code, marketers can analyze campaign performance, and support representatives can use real time agent assist to find answers during customer conversations.
• More accessible technology: Users can interact with AI through everyday language instead of learning complicated software interfaces. Voice AI also allows people to get assistance while driving, cooking, or performing other activities where typing isn’t convenient.
• Availability outside regular business hours: AI assistants can answer questions at any time. For businesses, this can mean providing assistance during evenings and weekends without requiring employees to remain available around the clock.
• More personalized experiences: Assistants with access to relevant context can adapt their recommendations based on user preferences or previous interactions. A personal assistant might recommend activities based on your interests, while a business assistant could suggest solutions based on a customer’s purchase history.

Cons of using AI assistants

Despite these advantages, AI assistants can produce incorrect information, misunderstand requests, or perform actions that users didn’t intend. These risks become more significant when assistants handle sensitive information or interact with business systems.

• Inaccurate or fabricated answers: AI assistants can confidently provide incorrect information, particularly when questions involve recent events or specialized knowledge. Verify important claims against reliable sources, especially when making financial or business decisions.
• Privacy and security concerns: Assistants may process personal information, customer records, or confidential business documents. Before connecting sensitive data, review the provider’s retention policies and access controls. Businesses should also consider approaches such as retrieval augmented generation to ground responses in authorized company information.
• Limited capabilities in free versions: Even the best free AI assistant may restrict file uploads, advanced models, or the number of requests users can submit. Check whether the free plan supports your intended tasks before committing to a particular platform.
• Difficulty handling unusual situations: An assistant might successfully answer common customer questions but struggle with a complicated complaint or an unexpected exception to company policy. Businesses should provide a clear path to human assistance when the system cannot resolve a request.
• Integration and setup requirements: Advanced AI assistants often need access to external applications before they can perform useful actions. For example, an assistant cannot reliably reschedule appointments without access to the relevant calendar system and permission to modify events.
• Risk of excessive reliance: Users may accept recommendations without verifying them, especially when responses sound convincing. This can become problematic in data analysis, legal research, or decisions involving customers.
• Unpredictable behavior during automated actions: Assistants that can execute tasks may select the wrong record or misunderstand an instruction. For sensitive actions, require approval and maintain execution logs. The same principle applies to voice AI systems handling customer phone calls, particularly when requests involve account changes or payments.

The safest approach is to introduce AI assistants gradually. Start with tasks where mistakes are easy to identify and correct. Once you’ve tested accuracy and reliability, expand their responsibilities while maintaining appropriate human oversight.

How to choose the right AI assistant

The best AI assistant depends on what you need it to accomplish. A tool that’s excellent at writing and research might struggle with scheduling meetings or executing actions in business applications.

Before choosing a platform, consider the following factors.

1. Identify your primary use cases

Start by listing the daily tasks you want assistance with. Be specific about the outcomes you expect.

For example:

• Research: Look for web browsing capabilities, source citations, and access to current information.
• Personal productivity: Prioritize calendar integrations, reminders, and scheduling meetings.
• Content creation: Test the assistant’s writing quality, editing capabilities, and ability to follow detailed instructions.
• Business operations: Choose a platform that can access company information and automate workflows across connected applications.

Test your most frequent tasks first. There’s little reason to pay for advanced automation capabilities if you primarily need help summarizing documents.

2. Check integrations and available tools

An assistant’s usefulness often depends on which applications it can access.

If you want an assistant to organize your calendar, it needs the appropriate permissions to create and modify events. Similarly, businesses that want AI to update customer records need integrations with their existing systems.

Check whether the assistant supports your current software and whether it can execute actions or only recommend them.

For example, Quiq AI Assistants can retrieve customer information and execute authorized actions in connected business systems while supporting human agents.

3. Evaluate accuracy and data privacy

Test the assistant with questions where you already know the correct answers. Then introduce more complicated requests that require information retrieval or several steps.

Pay attention to whether the assistant:

• Provides sources you can verify.
• Acknowledges uncertainty instead of inventing answers.
• Respects access permissions when retrieving information.
• Allows administrators to control how sensitive data is handled.

For business applications, review the provider’s security documentation before uploading confidential information.

4. Compare free and paid plans

The assistant with the most generous free tier isn’t necessarily the best choice.

Free plans often impose restrictions on advanced models, file uploads, and usage frequency. Some also exclude integrations or automation features.

Compare the limitations against your actual needs. If you only use an assistant occasionally, a free plan may be sufficient. However, frequent users should consider whether paid access provides meaningful improvements in reliability or functionality.

5. Consider the learning curve

Some AI assistants work immediately after registration. Others require considerable configuration before they can perform useful tasks.

Evaluate how easily you can write instructions, connect applications, and manage permissions.

Run the same five realistic tasks through two or more assistants. Compare the accuracy of their outputs, how much correction they require, and whether they can complete the work without additional intervention.

For businesses, also consider how employees will learn to use the software and what support the vendor provides during implementation.

The goal is to find an assistant that performs your most important tasks reliably, without introducing unnecessary complexity.

Put AI assistants to work with Quiq

AI assistants can help with everything from personal productivity to complex business operations. But in customer service, their value comes down to something simple: helping agents resolve customer issues faster and with less effort.

At Quiq, our AI Assistants give human support agents immediate access to customer context, relevant knowledge, and recommended next steps. They can also execute actions across connected business systems, so agents spend less time searching for information and more time helping customers.

And because our AI Assistants share knowledge and tools with our autonomous AI agents, your team can deliver consistent support whether a conversation is handled by a person or AI.

Want to see how Quiq AI Assistants can improve your customer service operations? Book a demo to see how our platform helps your agents work more efficiently and resolve customer requests with greater confidence.