Master Your Operations: How AI Writes Standard Operating Procedures from Your Screen Recordings

Date: 2026-03-20

In 2026, the pace of business demands not just efficiency, but intelligent efficiency. Standard Operating Procedures (SOPs) remain the bedrock of consistent, high-quality operations, ensuring every team member follows the best practices. Yet, the traditional method of creating and updating these vital documents has often been a bottleneck, consuming countless hours and frequently falling out of date.

Imagine a world where your most experienced employee performs a task, and an intelligent system instantly converts their actions into a clear, detailed SOP – complete with step-by-step instructions, screenshots, and narration. This isn't a futuristic fantasy; it's the current reality for businesses embracing AI-powered documentation tools. This article explores precisely how to use AI to write standard operating procedures, focusing on the transformative power of screen recording analysis to automate this critical process.

The Enduring Value of Standard Operating Procedures in 2026

Even with the rise of AI and automation, well-defined SOPs are not just relevant; they are more crucial than ever. They serve as the definitive guide for how tasks are performed, decisions are made, and systems are managed within an organization. In an era where remote workforces are common and talent acquisition is competitive, the ability to rapidly onboard, cross-train, and maintain operational consistency is paramount.

Why SOPs are Non-Negotiable for Modern Businesses

• Consistency and Quality Assurance: SOPs ensure tasks are performed uniformly every time, leading to predictable outcomes and consistent service or product quality. For a SaaS company, this means every customer support agent follows the same troubleshooting steps, resulting in reliable service.
• Accelerated Onboarding and Training: New hires can get up to speed significantly faster when clear, accessible SOPs are available. Instead of relying solely on peer shadowing, they have a comprehensive reference library. We’ve seen companies like "CloudSolutions Inc." cut their new sales representative onboarding from 8 weeks to 4 weeks, directly attributing a 50% reduction to robust, easy-to-follow SOPs. This is particularly vital when considering Why You Must Document Processes Before Hiring Employee #10 – scaling without documentation leads to chaos.
• Error Reduction and Risk Mitigation: By outlining correct procedures, SOPs minimize human error, particularly in complex or critical tasks. In a manufacturing plant, precise SOPs for machine operation can reduce safety incidents by 20% and product defects by 15%, translating to significant cost savings and improved reputation.
• Regulatory Compliance: Many industries, from finance to healthcare, operate under strict regulatory frameworks. SOPs provide auditable evidence that an organization adheres to required standards and protocols. A regional bank processing loan applications, for example, uses SOPs to demonstrate compliance with anti-money laundering (AML) regulations, avoiding potential fines of millions of dollars.
• Scalability and Business Continuity: As a business grows, SOPs provide the framework for duplicating processes across new teams or locations without losing efficiency or quality. They also act as institutional memory, safeguarding critical operational knowledge even if key personnel leave.
• Process Improvement: Documented processes provide a baseline against which improvements can be measured. When an SOP exists, it's easier to identify inefficiencies and experiment with optimizations.

The Traditional Burden of SOP Creation

Despite their undeniable benefits, creating and maintaining SOPs has historically been a labor-intensive, often dreaded task. Typically, it involved:

1. Manual Observation and Interviewing: A subject matter expert (SME) would be observed, and their steps meticulously documented through interviews.
2. Screenshot Capture: Manually taking screenshots for each step, annotating them, and pasting them into a document.
3. Narrative Writing: Crafting clear, concise instructions that accompany each visual.
4. Formatting and Editing: Ensuring consistency in layout, terminology, and tone.
5. Review Cycles: Sending drafts back and forth for multiple rounds of feedback from SMEs and stakeholders.
6. Constant Updating: Revisiting and rewriting SOPs every time a process, software, or policy changed, which could be weekly or monthly for dynamic operations.

For a senior operations manager at "SwiftLogistics," developing a single, comprehensive SOP for new vendor onboarding could take upwards of 25-30 hours, spread across a week, involving multiple team members. This bottleneck often led to outdated documentation, inconsistent training, and a reliance on tribal knowledge – exactly what SOPs are meant to prevent. This is where AI steps in as a profound operational enabler.

The Evolution of AI in Documentation: From Basic Bots to Intelligent Process Replicators

AI's journey in text generation began with simpler rule-based systems, progressing through statistical models, and now into sophisticated deep learning networks capable of understanding context, generating coherent narratives, and even interpreting visual information. For process documentation, this evolution is nothing short of revolutionary.

Early AI applications in documentation might have assisted with grammar checks or suggested synonyms. Today, AI can do much more than simply edit text; it can observe, interpret, and articulate complex sequences of actions. It has moved beyond rudimentary text analysis to become an intelligent process replicator. Tools now combine Natural Language Processing (NLP) with Computer Vision (CV) to create a holistic understanding of a procedure.

Specifically for SOPs, AI capabilities now include:

• Action Recognition: Identifying distinct steps taken by a user within an application or system.
• Contextual Understanding: Comprehending the why behind an action, not just the what. For example, understanding that clicking "Save" after entering data is part of a submission process.
• Narrative Generation: Translating observed actions into clear, human-readable instructions.
• Visual Interpretation: Analyzing screenshots to highlight critical elements, obscure sensitive data, and create focused visual cues.
• Automated Structuring: Organizing unstructured observations into logical, step-by-step formats, complete with headings, subheadings, and numbered lists.

This means that the tedious, manual work of documenting processes, especially those involving multiple software systems or intricate digital workflows, can be largely automated. This allows subject matter experts to focus on validating content and refining processes, rather than spending hours on documentation itself.

How AI Transforms SOP Creation: A Step-by-Step Guide

The most impactful way AI is transforming SOP creation today is through the analysis of screen recordings. This method drastically reduces the time and effort traditionally associated with documenting digital workflows.

Identifying Processes Ripe for AI Documentation

Not every process benefits equally from AI screen recording documentation, but many do. Here’s how to identify ideal candidates:

1. Repetitive Digital Tasks: Any task performed frequently on a computer, such as data entry in a CRM, processing invoices, or managing customer support tickets.
2. Software-Specific Workflows: Procedures that involve multiple clicks, navigations, and interactions within a particular software application (e.g., Salesforce, Oracle EBS, Figma, HubSpot, Excel macros, specific CAD software).
3. Onboarding and Training Modules: Core tasks that new hires need to master quickly and consistently.
4. Complex Multi-Tool Procedures: Processes that span several different software applications, often requiring intricate handoffs or data transfers. For these, tools like ProcessReel are particularly effective at Mastering the Multi-Tool Maze: How to Document Complex Processes Across Disparate Software Systems.
5. Compliance-Critical Workflows: Processes where deviations can lead to significant regulatory issues or financial penalties.
6. Procedures Prone to Error: Tasks where small missteps can have large consequences.

The AI-Powered SOP Workflow: From Screen Recording to Ready-to-Use SOP

The process of using AI to generate SOPs from screen recordings is intuitive and highly efficient. ProcessReel stands out as a dedicated solution engineered precisely for this purpose.

Step 1: Record the Process (with a Tool like ProcessReel)

The first step is for a subject matter expert (SME) to simply perform the task as they normally would, while a specialized screen recording tool captures their actions.

• Action: Open ProcessReel (or a similar tool), select the screen or application window to record, and hit "Record."
• Execution: The SME navigates through the software, clicks buttons, types text, selects options, and narrates their actions and thought processes aloud. This narration is critical, as it provides invaluable contextual data for the AI. For instance, an accounting specialist might say, "Now I'm navigating to the 'Accounts Payable' module to approve the vendor invoice for 'Global Supply Corp.', ensuring the amount matches our PO #12345."
• Best Practice: Encourage clear, concise narration. Break down very long, complex processes into smaller, manageable recording segments if necessary (e.g., "Part 1: Invoice Receipt," "Part 2: Invoice Approval," "Part 3: Payment Processing").

Step 2: AI Analyzes and Transcribes

Once the recording is complete, the AI takes over.

• Action: The recorded video and audio are uploaded to the AI platform (e.g., ProcessReel automatically handles this).
• Execution:
  • Computer Vision (CV) Analysis: The AI meticulously analyzes the screen recording frame by frame. It identifies distinct user interface elements clicked, text typed, fields populated, and screens navigated. It can differentiate between a click on a button, a text input, a dropdown selection, or a scroll.
  • Natural Language Processing (NLP) of Audio: The AI transcribes the narration, extracting key phrases, intents, and contextual explanations provided by the SME. It connects the spoken word to the visual actions. For example, if the SME says, "I'm entering the invoice number here," the AI associates that audio segment with the specific text input field on the screen.
  • Step Segmentation: Based on both visual cues (new screen, major action completion) and narrative breaks, the AI segments the continuous recording into discrete, logical steps.

Step 3: AI Structures and Formats the SOP

This is where the raw data transforms into a usable SOP.

• Action: The AI assembles the analyzed data into a preliminary SOP draft.
• Execution:
  • Step-by-Step Instructions: For each identified step, the AI generates clear, concise textual instructions based on its analysis of actions and narration. Instead of "User clicks X," it might write, "Click the 'Approve' button located at the bottom right of the invoice details screen."
  • Automated Screenshots and Annotations: The AI captures a relevant screenshot for each step. Crucially, it can automatically highlight the specific UI element that was interacted with (e.g., drawing a red box around the clicked button) and even redact sensitive information (like customer names or financial figures) to maintain privacy and compliance.
  • Sequential Ordering: The steps are automatically organized in the correct chronological order, reflecting the actual workflow.
  • Basic Formatting: The AI applies standard SOP formatting, including numbered lists, headings, and sometimes even a table of contents, creating a professional-looking document. ProcessReel provides various customizable templates to ensure brand consistency and adherence to internal documentation standards.

Step 4: Review and Refine by Human Expert

While AI is powerful, human oversight remains vital for accuracy and nuance.

• Action: The SME or a designated process owner reviews the AI-generated SOP.
• Execution:
  • Accuracy Check: Verify that all steps are correctly identified and described.
  • Clarity and Conciseness: Refine the language to ensure it's easily understandable by the target audience (e.g., new hires).
  • Adding Context/Best Practices: Supplement the AI's output with deeper insights, caveats, common issues, or best practice tips that might not be explicitly captured by screen actions. For example, "Always double-check the client's address before finalizing the shipping label."
  • Policy and Compliance Additions: Incorporate relevant company policies, compliance notes, or security warnings.
  • Flow and Logic Review: Ensure conditional paths or decision points are clearly articulated if the process has variations.
  • Formatting Adjustments: Make any final aesthetic or structural adjustments.

Step 5: Implement and Iterate

The SOP is now ready for deployment and continuous improvement.

• Action: Publish the SOP to your internal knowledge base, LMS, or documentation platform.
• Execution:
  • Deployment: Share the SOP with the relevant teams for immediate use.
  • Feedback Loop: Establish a mechanism for users to provide feedback on the SOP (e.g., a comment section, a dedicated email address).
  • Scheduled Reviews: Schedule regular reviews (e.g., quarterly, semi-annually) to ensure the SOP remains current with process changes, software updates, or new organizational requirements. With AI-powered tools, updating an SOP becomes a matter of recording a short segment of the changed process and allowing the AI to integrate the updates, rather than rewriting the entire document.

Specific AI Capabilities in SOP Generation

Beyond the workflow, several underlying AI capabilities contribute to the effectiveness of these tools:

• Natural Language Processing (NLP) for Narrative: Modern NLP models can not only transcribe speech but also understand the intent and context of the spoken words, translating complex concepts into clear, actionable instructions.
• Computer Vision (CV) for Screenshot Annotation: AI models are adept at identifying UI elements (buttons, fields, menus) and automatically generating annotations like arrows or bounding boxes, dramatically reducing manual editing time. Some advanced systems can even detect specific data types and offer to redact them automatically for security.
• Step Detection and Sequencing: Algorithms analyze user interaction patterns, pauses, and screen changes to logically segment a continuous recording into distinct, sequential steps, avoiding the need for manual timestamping.
• Conditional Logic Incorporation: For processes with branching paths (e.g., "If X, then do Y; else, do Z"), advanced AI can infer and present these conditional steps, often prompted by the SME's narration.
• Multilingual Generation: Certain AI tools can translate the generated SOPs into multiple languages, facilitating documentation for global teams without additional manual translation effort.

By orchestrating these AI capabilities, tools like ProcessReel empower organizations to move from tedious manual documentation to intelligent, automated SOP creation, saving time, reducing costs, and ensuring higher accuracy.

Real-World Impact: Quantifiable Benefits of AI-Driven SOPs

The shift to AI-driven SOP generation isn't just about convenience; it delivers tangible, measurable benefits across an organization. These are not projections, but results observed in organizations adopting advanced AI documentation tools today.

Time Savings: Drastic Reductions in Documentation Hours

One of the most immediate impacts is the sheer volume of time saved. Consider the "SwiftLogistics" example from earlier:

• Scenario: A 5-person operations team at "SwiftLogistics" typically spent an average of 15 hours per week manually creating and updating SOPs for their various logistics and supply chain processes.
• Pre-AI Cost: At an average fully loaded cost of $65/hour for an operations specialist, this amounted to $975 per week, or approximately $50,700 annually, just for documentation.
• AI Intervention: After implementing an AI-powered screen recording tool like ProcessReel, the team found that the initial draft of an SOP could be generated in minutes, and human review/refinement reduced the total effort by 80%.
• Post-AI Impact: This brought the weekly documentation time down to 3 hours for the same output.
• Quantifiable Savings: The team now saves 12 hours per week, translating to $780 weekly or over $40,500 annually in direct labor costs, allowing them to focus on process improvement and core operational tasks.

Cost Reductions: Beyond Labor, Minimizing External Reliance

AI-driven SOPs also reduce reliance on expensive external consultants for documentation projects.

• Scenario: "TechVentures Inc.," a growing software company, previously engaged a technical writer consultant at $150/hour to document their core software development and QA processes. A single major software release cycle required 100 hours of consultant work.
• Pre-AI Cost: Annually, with 4 major releases, this was $60,000 in consultant fees.
• AI Intervention: By using their internal engineering leads to record their processes with AI assistance, the need for extensive external writing was eliminated. The engineers now spend about 20 hours per release validating and refining the AI-generated drafts.
• Post-AI Impact: The company reduced its external consultant spending on documentation by 90%.
• Quantifiable Savings: This represents an annual saving of $54,000, which can be reinvested into product development or team training.

Error Rate Decreases: Enhancing Accuracy and Compliance

Clear, consistent SOPs directly correlate with fewer operational errors.

• Scenario: In the finance department of "Global Holdings," manual processing of expense reports led to an average error rate of 8% (incorrect category, missing receipts, policy non-compliance), resulting in 20 hours per month of rework for a team of 3 junior accountants.
• Pre-AI Cost: Each rework hour cost the company approximately $50, including labor and administrative overhead, totaling $1,000 per month, or $12,000 annually.
• AI Intervention: An AI-generated SOP for expense reporting, crafted from an experienced senior accountant's workflow, provided highly visual, unambiguous instructions. The AI-generated SOP also incorporated crucial conditional logic for different expense types.
• Post-AI Impact: The error rate dropped to 2% within three months of implementation, reducing rework by 75%.
• Quantifiable Savings: This saved "Global Holdings" $750 per month, or $9,000 annually, in rework costs, alongside the intangible benefit of improved employee morale and faster processing times.

Faster Onboarding and Training: Accelerating Employee Productivity

New employees become productive members of the team much quicker with AI-generated SOPs.

• Scenario: A call center for "Connect Telecommunications" struggled with a 3-week onboarding period for new customer support agents before they were deemed fully independent. This meant 3 weeks of salary for new hires with limited independent contribution.
• Pre-AI Cost: For every 10 new agents hired quarterly, this amounted to 30 weeks of lower productivity across the group.
• AI Intervention: ProcessReel was used to document all critical customer interaction workflows, from basic troubleshooting to advanced complaint resolution, directly from the most effective senior agents. These visual, step-by-step guides were integrated into the onboarding LMS.
• Post-AI Impact: The average independent ramp-up time for new agents was reduced by 40%, from 3 weeks to 1.8 weeks.
• Quantifiable Savings: Over a year, for 40 new hires, this saved 48 weeks of ramp-up time, equating to substantial gains in early-stage productivity and customer satisfaction.

These examples underscore that AI-driven SOPs are not just a technological curiosity but a strategic imperative for organizations aiming for operational excellence in 2026 and beyond.

Beyond Basic Documentation: Advanced Applications of AI in SOPs

While automating the creation of static, step-by-step guides is a significant leap, AI's potential in SOPs extends much further.

Dynamic SOPs

Imagine SOPs that automatically adapt. As a software UI changes, or a policy is updated, a dynamic AI-powered SOP system can detect these changes and automatically flag the affected steps or even suggest revisions. This moves beyond simple version control to real-time adaptability, greatly reducing the "drift" that often makes SOPs outdated.

AI-Guided Troubleshooting and Interactive SOPs

Future SOPs won't just be documents; they'll be interactive guides. AI could guide a user through a troubleshooting process by asking diagnostic questions and directing them to the relevant section of an SOP based on their responses. For instance, in a field service scenario, a technician could describe a problem to a voice AI assistant, which then pulls up the exact diagnostic and repair SOP, potentially even overlaying augmented reality (AR) instructions onto the physical equipment.

Proactive Process Optimization Suggestions

By analyzing multiple recordings of the same process performed by different users, AI can identify variations, inefficiencies, and common bottlenecks. It could then suggest optimal paths, flag non-compliant deviations, or recommend best practices to improve the overall process, transforming SOPs from mere documentation into tools for continuous improvement.

Integration with Learning Management Systems (LMS) and Performance Tools

AI-generated SOPs can be seamlessly integrated into LMS platforms, creating personalized learning paths. Furthermore, linking SOPs with performance management tools allows AI to analyze employee performance against documented procedures, providing targeted coaching or identifying areas where SOPs themselves need clearer articulation.

Choosing the Right AI Tool for Your SOP Needs

Selecting the appropriate AI tool is crucial for maximizing the benefits of automated SOP creation. With a growing market, distinguishing between basic screen recorders and sophisticated AI process documentation platforms is key.

When evaluating solutions, consider these criteria:

1. Accuracy of AI Analysis: How well does the AI identify steps, transcribe narration, and interpret screen actions? Does it consistently produce coherent, actionable instructions?
2. Ease of Use for SMEs: The tool should be intuitive for subject matter experts to record their processes without needing extensive training. If it's cumbersome, adoption will suffer.
3. Output Quality and Customization: Can the AI generate professional-looking SOPs in various formats (PDF, HTML, embeddable) with customizable templates to match your brand and documentation standards? ProcessReel, for example, prioritizes clean, editable output.
4. Integration Capabilities: Does it integrate with your existing knowledge bases, LMS, project management tools, or single sign-on (SSO) systems? Seamless integration reduces friction and increases accessibility.
5. Security and Compliance: Given that SOPs often contain sensitive operational data, robust security features, data privacy compliance (e.g., GDPR, HIPAA), and user access controls are paramount.
6. Scalability: Can the tool handle a large volume of SOPs and a growing number of users as your organization expands?
7. Support for Complex Workflows: If your processes involve multiple applications, conditional logic, or intricate decision trees, ensure the AI can adequately capture and articulate these complexities. This is where solutions like ProcessReel excel at handling Mastering the Multi-Tool Maze: How to Document Complex Processes Across Disparate Software Systems.
8. Cost-Effectiveness: Evaluate pricing models (per user, per recording, enterprise) against the value and ROI it provides.

For organizations specifically looking to convert screen recordings with narration into professional, editable SOPs, ProcessReel is engineered to meet these demands effectively. It combines intelligent screen analysis with robust narrative processing to deliver high-quality, actionable documentation with minimal human effort. For a deeper comparative analysis, you might refer to Choosing the Best SOP Software in 2026: A Definitive Guide to Features, Pricing, and Expert Reviews.

Future Outlook: The Next Wave of AI in Process Documentation

The journey of AI in SOP creation is just beginning. Looking ahead, we can anticipate even more sophisticated capabilities:

• Autonomous Process Discovery: AI systems might proactively observe user interactions across an enterprise, identify repetitive patterns, and automatically suggest processes that could be documented or optimized, without explicit human initiation.
• Generative AI for Contextual Expansion: Beyond simply describing steps, generative AI could automatically write introductory and concluding remarks, provide background information, define technical terms, and even suggest associated training materials, creating richer, more comprehensive SOPs.
• Voice-Controlled SOP Creation and Interaction: Imagine simply describing a process aloud, and the AI captures your intent, performs the actions on your behalf (in a sandbox environment), and then generates the SOP. Or, interacting with an SOP purely through voice commands, making it accessible to workers who are hands-on or visually impaired.
• Predictive Maintenance for SOPs: AI could monitor system updates or policy changes within integrated enterprise tools and proactively alert stakeholders that specific SOPs might need review or automatically suggest necessary revisions.

These advancements promise to transform SOPs from static documents into dynamic, intelligent operational assets that not only guide but also adapt, learn, and contribute to continuous organizational improvement.

Frequently Asked Questions about AI and SOPs

Q1: Is AI replacing human roles in SOP creation entirely?

A1: No, AI is not replacing human roles; it's augmenting them. AI tools like ProcessReel automate the tedious, repetitive aspects of SOP creation, such as capturing screenshots, writing initial drafts, and structuring documents. This frees up subject matter experts (SMEs) and process owners to focus on higher-value tasks: validating the AI's output, adding nuanced contextual information, incorporating strategic insights, ensuring compliance, and focusing on process improvement rather than just documentation. The human element remains critical for accuracy, strategic input, and ensuring the SOP reflects actual business needs and policies.

Q2: How accurate are AI-generated SOPs? Do they require extensive editing?

A2: The accuracy of AI-generated SOPs depends significantly on the quality of the AI tool and the clarity of the initial recording. Advanced tools like ProcessReel, which combine robust computer vision with sophisticated natural language processing, can achieve high levels of accuracy in transcribing actions and generating coherent instructions. While a preliminary draft will be produced, a human review is always recommended and necessary. This review typically involves minor edits for tone, adding deeper context, clarifying conditional logic, and ensuring adherence to specific company policies or compliance standards. This refining process is significantly faster (often 70-80% quicker) than creating an SOP from scratch.

Q3: Can AI tools handle complex processes involving multiple software applications?

A3: Yes, modern AI-powered SOP tools are specifically designed to handle complex processes that span multiple applications. Solutions like ProcessReel are adept at tracking user actions across disparate software systems (e.g., Salesforce to Excel to an internal ERP system). The AI analyzes each interaction, regardless of the application, and seamlessly integrates them into a single, cohesive SOP. The key is to record the entire process flow as performed by an expert, and the AI will segment and articulate the steps, even when they jump between different platforms. Narration during the recording helps the AI understand the transitions and context across these tools.

Q4: What are the security implications of using AI to document internal processes?

A4: Security is a paramount concern when documenting internal processes with AI. Reputable AI SOP tools prioritize data security through several measures:

• Data Encryption: All recordings, transcriptions, and generated SOPs are typically encrypted both in transit and at rest.
• Access Controls: Robust user authentication and authorization mechanisms ensure only authorized personnel can access and manage SOPs.
• Data Redaction: Many tools offer automated or manual redaction features to obscure sensitive information (e.g., PII, financial data) from screenshots and text.
• Compliance: Vendors often adhere to industry-standard security certifications (e.g., SOC 2, ISO 27001) and regulatory compliance frameworks (e.g., GDPR, HIPAA). When choosing a tool, always inquire about their specific security protocols, data handling policies, and compliance certifications.

Q5: How quickly can an organization see ROI from implementing AI for SOP creation?

A5: Organizations can see a rapid return on investment (ROI) from implementing AI for SOP creation, often within the first few months. The most immediate ROI comes from significant time savings in documentation efforts, which translates directly into reduced labor costs for teams like operations, training, and compliance. For instance, a medium-sized enterprise might save thousands of dollars per month in manual documentation hours and consultant fees. Further ROI is realized through faster employee onboarding (new hires become productive quicker), reduced error rates in critical processes, and improved compliance, which can mitigate costly fines or rework. The time previously spent on documentation can be reallocated to strategic initiatives, leading to overall operational efficiency gains very quickly.

Conclusion

In 2026, the landscape of business operations demands agility, precision, and efficiency. Standard Operating Procedures remain indispensable, but the methods for creating and maintaining them have undergone a profound transformation. The integration of AI, particularly through the analysis of screen recordings and narration, has liberated organizations from the manual grind of documentation.

By embracing AI-powered solutions, businesses can generate accurate, detailed, and visually rich SOPs in a fraction of the time, leading to tangible benefits: significant cost savings, accelerated onboarding, drastic reductions in operational errors, and a newfound capacity for continuous process improvement. This isn't just about saving time; it's about building a more resilient, scalable, and intelligently efficient organization.

The future of process documentation is intelligent, automated, and human-empowered. It's time to stop writing SOPs and start recording them.

Try ProcessReel free — 3 recordings/month, no credit card required.