The 2026 SaaSOps checklist: Managing and securing your enterprise SaaS applications

Updated May 2026 

If you’re reading this, you already know that at every second around the clock, IT has to manage and secure dozens, maybe hundreds, of the enterprise’s SaaS apps. And for each of those SaaS applications, IT also has to manage their users, spending, and files as well as monitor activity. The result is an ever-growing, unmanageable swamp teeming with human error and negligence. It’s impossible to manage what you don’t know and even more impossible to secure against risk you cannot fully see. Meanwhile, AI tools are expanding the attack surface and creating new governance needs. If this is your world, this SaaSOps checklist is for you.

SaaS operations, or SaaSOps, is the practice of discovering, managing, securing, and optimizing spend in your SaaS environment. But in recent years,amplified by AI adoption, it has evolved from a nice-to-have into a strategic imperative. This updated mini-checklist gives you actionable SaaS operations priorities for 2026.

SaaSOps in 2026: Platform-first, AI-augmented, Zero Trust

Preferred by 70% of IT leaders, today’s modern SaaSOps leverages unified SaaS Management Platforms (SMPs) over fragmented point solutions. To reduce risk, cut waste, and deliver better employee experiences, this key technology and practice incorporates: 

• Robust cross-app automation 
• Data-driven insights 
• Zero Trust principles 
• FinOps discipline
• Automated enforcement of security and AI governance policies

The 2026 SaaSOps mini-checklist

Our mini-checklist represents the core activities every IT professional should strive for to operate the modern digital workplace. 

Of course, it’s important to remember that every organization’s journey to that digital workplace is different. So keep yours in mind as you read to best apply it to your situation.

1. Build or fortify your SaaSOps foundation

SaaSOps requires a new organizational structure, new IT skills, new end-user training and support, as well as a new change management approach. Without the right processes staffed by the right team, the remaining components are simply more challenging.

Here are some foundational best practices:

• Structure your SaaSOps team to include roles for configuring, monitoring, automating, securing, and governing SaaS applications
• Create policies that balance productivity, security, and cost, as well as align with Zero Trust and regulatory requirements (GDPR, CCPA, emerging AI rules).
• Implement your IT operations according to that strategic plan
• Deploy a unified SaaS management platform for discovery, automation, security, and spend optimization within your IT stack
• Grow expertise of APIs, orchestration tools, and AI agents
• Perform regular risk assessments for new SaaS apps, especially AI/GenAI tools and Shadow IT
• Follow continuous improvement to optimize processes
• Learn how end-user accounts, permissions, and access rights management work
• Understand SaaS app performance monitoring, incident response, and auditing
• Commit to continuous improvement, metrics tracking, and change management
• Make sure end users know what alerts and notifications of potential security violations mean
• Ensure IT retains super-admin visibility and control across all critical SaaS apps
• Train end users on safe AI usage, prompt engineering basics, and processes for reporting suspicious AI activity to reduce fear of change and get the most out of SaaS and AI-based tools

2. Master SaaS user lifecycle management (ULM)

• Create standardized processes for onboarding
• Automate onboarding processes, so new employees and AI agents gets immediate access to applications, files, folders, groups, calendars, and sites used both company-wide and specific to their role
• Limit access to data until new employees set up multi-factor authentication (MFA)
• Make standardized processes with strict timelines for offboarding based on whether a user is an employee, partner, or contractor
• Automate processes for offboarding to make sure it’s completed immediately after departure
• Automate
• Look for opportunities to automate mid-lifecycle staffing changes (role changes and departures) and events like lost or stolen endpoints and devices
• Prioritize mid-lifecycle automations based on volume and/or risk, like when employees take long-term maternity or paternity leave

3. Make full visibility into users, files, and activity across SaaS applications a priority

• Maintain comprehensive audit trails to track admin activity, log file locations, and all actions
• Maintain a living inventory of all SaaS applications, sanctioned and unsanctioned
• Prevent risky application configurations by reviewing group, calendar, file, and/or email forwarding privacy settings
• Centralize visibility into SaaS usage data, license utilization, Shadow IT, Shadow AI, and data flows for maximum insights
• Make sure IT maintains all SaaS app super admin permissions
• Delete or archive empty or unused groups and channels across SaaS apps
• Monitor SaaS-to-SaaS integrations and third-party connections
• Keep detailed audit trails for non-human identity activity
• Identify AI-to-SaaS and SaaS-to-SaaS connections
• Deploy 24/7 continuous automated discovery and policy enforcement
• Track non-human or AI agent identities, including API keys, OAuth tokens, and AI agents with data access

4. Optimize your SaaS footprint and spending

• Track login data to identify unused licenses
• Assign App Owners for all SaaS apps
• Integrate FinOps practices to optimize pricing including fixed, per-seat pricing and usage-based pricing
• Automate license reclamation from inactive users after 14 or 30 days to avoid costly, inactive licenses
• Monitor usage activity to find underutilized licenses for optimization and consolidation opportunities
• Map functional redundancies to consolidate accounts into IT-sanctioned apps
• Use usage data and AI recommendations to right-size service tiers or permissions dynamically to downgrade less active users to less costly tiers
• Cancel apps that go unused for 90+ days without activity
• Set 90-day renewal alerts to prevent unwanted autorenewals
• Benchmark renewal or new purchase pricing to know if you’re getting a good deal

5. Strengthen authentication and adopt Zero Trust

• Use an Identity-as-a-Service (IDaaS) solution for single sign-on (SSO) to track access from various user endpoints
• Deploy strong and enforced MFA as a baseline
• Track failed logins, anomalous behavior, and account takeover indicators with AI-driven detection
• Implement continuous verification, device posture checks, and contextual access controls using Zero Trust
• Enforce least privilege access for admins and users and regularly review over-privileged accounts
• Secure and govern API keys, OAuth tokens, and non-human identities
• Build and maintain a workflow for granting elevated privileges only for the duration of specified tasks for users and AI agents

6. Secure your SaaS applications, users, and files

• Monitor for suspicious activity to guard against inappropriate data sharing and insider threats
• Maintain application configurations, privacy settings, and file-sharing controls across SaaS apps
• Review and govern third-party browser extensions installed by users
• Use automated alerts and notifications for real-time remediation of improper insider activity
• Use alerts and notifications to educate and engage users
• Check for users who should no longer belong to specific groups/distribution lists
• Implement data loss prevention (DLP) controls
• Scan files on a routine basis for sensitive data leakage (including AI prompts) using DLP
• Review OAuth scopes, API keys, and permissions granted to AI tools and revoke overly broad access
• Audit against the NIST Cybersecurity Framework to identify perimeter gaps

7. Build and refine an incident response plan

• Train employees on roles and responsibilities if a security incident occurs
• Conduct regular tabletop exercises focused on SaaS and AI-powered apps and agents
• Define criteria for security incidents and severity thresholds for exposure of confidential financial data, via AI tools or misconfigurations
• Use orchestrated and automated remediation across integrated systems, including SMP, SIEM, EMM, SSPM, ITSM tools
• Integrate AI governance into your broader incident response plan for rapid containment if sensitive data is fed into an external model

8. Monitor compliance continuously

• Set policy-based automated controls for data handling and retention to meet legal regulatory compliance requirements like HIPAA and GDPR or standards like PCI
• Automate log collection and evidence
• Review detailed audit logs of user and admin actions for proof of compliance (HIPAA, GDPR, SOC2, etc.)
• Conduct regular AI risk assessments for new tools, focusing on hallucination risks, bias, intellectual property leakage, and compliance (e.g., GDPR “right to explanation”)
• Detect and proactively remediate sensitive data exposure and excess admin privileges to ensure compliance

9. Strengthen AI governance and agentic workflows

• Align AI governance with the April 2026 NIST AI Risk Management Framework
• Create and enforce an AI Acceptable Use Policy (AUP) that covers approved tools, data classification rules (e.g., no sensitive/PII data in public Generative AI tools), and output review requirements
• Govern AI agents and automations by requiring approval for agentic workflows
• Monitor AI agent activities and integrations
• Define human-in-the-loop requirements and ensure human oversight for high-risk AI actions
• Track ROI on AI investments with adoption rates, costs, and related security incidents
• Identify SaaS apps in your stack with native AI features turned on
• Mandate a browser extension to track where employees paste sensitive code or PII into ungoverned browser-based AI tools
• Review and disable data training permissions in all native-AI SaaS apps
• Maintain a central AI tool inventory (sanctioned + discovered) with usage analytics, cost tracking, and risk scoring.
• Monitor agent-to-agent or agent-to-SaaS interactions for behavioral anomalies
• Plan for emerging regulations around AI transparency, accountability, and auditing
• Ensure all enabled AI features comply with the EU AI Act’s transparency requirements regarding high-risk systems

Take your next SaaSOps step in 2026

After reviewing our SaaSOps crib notes, check out our expanded best practices checklist. It’ll give you loads of detailed guidance and hot tips to help get a handle on your SaaS environment. 

After that, take a good look at all the SaaS applications across your environment. Then give an honest review and find the gaps. For instance:

• Where are the biggest security and cost risks?
• What tools, team members, skills, and/or training are missing?
• Which gaps are most important to tackle first?
• Where would automation eliminate manual work?
• How prepared are you for AI-driven usage, threats, and governance? 
• Would a unified SaaS management platform help?

When you’re done, think about the strategic roadmap that aligns with business goals and policies. Then think about your technologies. Organizations using unified SaaS management platforms and structured automation are reducing risk, lowering costs, and freeing IT to focus on higher-value work. Best of all, you’ll be able to concentrate on AI initiatives, and make IT a true value driver and engaged business partner.

Ready to level up your SaaSOps?Explore BetterCloud’s resources, including our latest State of SaaS Report, the updated SaaS operations glossary, and platform capabilities built specifically for modern SaaSOps in the age of AI.