Web Administrators

Monitor systems for intrusions or denial of service attacks, and report security breaches to appropriate personnel.

AI: Fully automatable - By 2025 AI-driven SIEM/IDS and automated monitoring systems can detect intrusions or DDoS patterns and automatically alert or report breaches to the right personnel.

Identify or document backup or recovery plans.

AI: Fully automatable - AI can analyze infrastructure, assess risk and dependencies, and produce clear backup and recovery plans and documentation based on best practices and system state.

Back up or modify applications and related data to provide for disaster recovery.

AI: Fully automatable - Backup and disaster-recovery tasks (backing up data, configuring replication, orchestrating failover) are routinely automated and can be fully executed by AI-driven tooling.

Implement updates, upgrades, and patches in a timely manner to limit loss of service.

AI: Fully automatable - Automated patch management and orchestration tools, enhanced by AI for scheduling and risk assessment, can implement updates/upgrades/patches and manage rollbacks in a timely manner.

Implement Web site security measures, such as firewalls or message encryption.

AI: Fully automatable - AI and automation platforms can configure and enforce website security controls (firewalls, TLS, encryption) at scale and maintain configurations with minimal human intervention.

Perform user testing or usage analyses to determine Web sites' effectiveness or usability.

AI: Fully automatable - AI tools can run user tests, analyze behavior and metrics, synthesize usability findings, and generate actionable recommendations end-to-end.

Document application and Web site changes or change procedures.

AI: Fully automatable - AI can automatically generate, update, and format documentation from commits, change logs, and system metadata with high reliability.

Track, compile, and analyze Web site usage data.

AI: Fully automatable - Analytics ingestion, aggregation, anomaly detection, and automated insight generation are well within AI capabilities and can be fully automated.

Review or update Web page content or links in a timely manner, using appropriate tools.

AI: Fully automatable - Link checking, routine content updates, and CMS-driven edits can be fully automated with AI when editorial rules and access are provided.

Gather, analyze, or document user feedback to locate or resolve sources of problems.

AI: Fully automatable - Collecting, clustering, sentiment‑analyzing, and drafting reports from user feedback sources can be automated end-to-end by AI tools.

Set up or maintain monitoring tools on Web servers or Web sites.

AI: Fully automatable - By 2025 AI systems and automation scripts can fully install, configure, and maintain common web monitoring stacks (Prometheus, Datadog, ELK, etc.) given access and configuration parameters.

Develop or document style guidelines for Web site content.

AI: Fully automatable - AI can generate, refine, and format comprehensive website style guides from examples and requirements and produce maintainable documentation automatically.

Check and analyze operating system or application log files regularly to verify proper system performance.

AI: Fully automatable - Automated log collection and AI-driven analysis for anomaly detection and routine performance verification are mature capabilities that can run continuously with minimal human intervention.

Inform Web site users of problems, problem resolutions, or application changes and updates.

AI: Fully automatable - By 2025 AI systems can automatically generate and dispatch tailored user notifications from monitoring and ticketing data, enabling full automation of informing users about problems, resolutions, and updates.

Identify, standardize, and communicate levels of access and security.

AI: Partial - AI can analyze access patterns, propose standardized role-based schemes and auto-generate communications, but final policy decisions and governance enforcement generally require human approval.

Correct testing-identified problems, or recommend actions for their resolution.

AI: Partial - AI can identify and often fix common test-identified issues or provide actionable remediation steps, but complex or architectural problems usually need human developer intervention.

Determine sources of Web page or server problems, and take action to correct such problems.

AI: Partial - AI can diagnose many web-page or server issues and perform automated remediations for straightforward faults, but difficult root-cause investigations and nuanced fixes often need human expertise.

Collaborate with development teams to discuss, analyze, or resolve usability issues.

AI: Partial - AI can run automated usability audits, simulate user flows, and analyze metrics, but conducting live moderated user testing and nuanced qualitative interpretation remains partly human-driven.

Test issues such as system integration, performance, and system security on a regular schedule or after any major program modifications.

AI: Partial - Automated CI/CD pipelines and testing tools can run integration and performance tests and many security scans, but complex security validation and interpretation still require human oversight.

Test backup or recovery plans regularly and resolve any problems.

AI: Partial - Scheduled automated restores and validation can be run by AI/automation, but diagnosing novel recovery failures and making higher‑risk remediation decisions typically need human intervention.

Recommend Web site improvements, and develop budgets to support recommendations.

AI: Partial - AI can analyze data and propose site improvements and cost estimates, but final prioritization and organizational budget decision-making require human accountability and context.

Install or configure Web server software or hardware to ensure that directory structure is well-defined, logical, and secure, and that files are named properly.

AI: Partial - Provisioning and configuration can be largely automated via IaC and scripts, but secure architecture decisions and hardware-level setup often need human oversight and environment-specific judgment.

Administer internet or intranet infrastructure, including Web, file, and mail servers.

AI: Partial - AI can automate many infrastructure tasks (monitoring, patching, backups, configuration management), but full administration including complex incident response, physical maintenance, and nuanced troubleshooting still needs human operators.

Monitor Web developments through continuing education, reading, or participation in professional conferences, workshops, or groups.

AI: Partial - AI can continuously ingest, summarize, and alert on web-development trends and virtual content but cannot fully substitute for human networking and active participation in in-person professional events.

Develop Web site performance metrics.

AI: Partial - AI can propose standardized website performance metrics and instrument them, but selecting and prioritizing metrics still requires human strategic context and stakeholder trade-offs.

Collaborate with Web developers to create and operate internal and external Web sites, or to manage projects, such as e-marketing campaigns.

AI: Partial - AI can assist heavily with code, deployment, task coordination, and campaign automation, but genuine collaboration, negotiation, and project leadership still need human oversight.

Identify or address interoperability requirements.

AI: Partial - AI can analyze system interfaces, recommend interoperability requirements and mappings, and generate integration code, yet real-world requirement negotiation and cross-system testing typically require humans.

Develop or implement procedures for ongoing Web site revision.

AI: Partial - AI can draft and implement CI/CD procedures and automated revision workflows, but governance, approval processes, and organizational change management require human input.

Provide training or technical assistance in Web site implementation or use.

AI: Partial - AI can produce tutorials, interactive walkthroughs, and on-demand technical assistance chatbots, but complex, adaptive training and high-touch support still benefit from human trainers.

Evaluate testing routines or procedures for adequacy, sufficiency, and effectiveness.

AI: Partial - AI can evaluate test coverage, detect gaps, and recommend improvements, but final judgments about adequacy and business risk trade-offs generally require human decision-makers.

Document installation or configuration procedures to allow maintenance and repetition.

AI: Partial - AI can draft detailed installation and configuration documentation from system inputs, scripts, and templates, but typically requires human validation and environment-specific adjustments for completeness and accuracy.

Develop testing routines and procedures.

AI: Partial - AI can produce comprehensive testing routines and procedures based on specifications and historical test data, yet human expertise is usually needed to design integration and edge-case tests.

Test new software packages for use in Web operations or other applications.

AI: Partial - AI can run automated test suites, static analysis, and compatibility checks for new software packages, but interpreting complex failures and performing real-world validation generally requires human judgment.

Develop and implement marketing plans for home pages, including print advertising or advertisement rotation.

AI: Partial - AI can generate marketing plans, creative variants, and manage ad rotations and digital implementation, but strategic branding decisions, cross-channel coordination, and print production oversight typically need human input.

Evaluate or recommend server hardware or software.

AI: Partial - AI can analyze requirements, performance data, and pricing to recommend server hardware or software, but procurement tradeoffs, contractual considerations, and risk assessment usually require human decision-making.