AI Outages Jumped 750% in a Year. Does Your Business Have a Plan?

Major AI service disruptions went from 6 high-signal days in Q1 2025 to 51 in Q1 2026. That is according to Ookla, which analyzed 3.72 million user-reported incidents across ChatGPT, Claude, Microsoft Copilot, and Google Gemini over 16 months. By the first quarter of 2026, a major AI service outage was happening every 1.8 days on average.

If your business has quietly built workflows around these tools, that data has real implications for your business continuity planning.

How AI Tools Became Infrastructure Nobody Officially Planned For

Nobody sat down and decided to make AI tools mission-critical. It happened the way most technical debt happens. Copilot got embedded in Outlook and Teams. Someone started using it for proposal drafts. Someone else built a routine that pulls meeting summaries into the CRM. Then one day the service goes down and half the morning is gone.

That is roughly what happened on June 1, 2026. Microsoft Copilot went offline for about five hours after an authentication infrastructure failure. Microsoft confirmed the issue on its admin center status page starting around 8 a.m. ET. Full recovery was not declared until after 3 p.m. During those hours, users lost AI-assisted drafting in Word, meeting summarization in Teams, and code assistance in Visual Studio.

For a 50-person firm that has built Copilot into its sales workflow, that is not an abstract disruption. It is a real hole in the business day.

The June 1 outage was not isolated. Copilot had also been down on May 29. And in Ookla's Q1 2026 data, Anthropic's Claude showed the most volatility of any platform, accounting for 39 of the 51 high-signal disruption days tracked. Anthropic has been growing fast. The underlying infrastructure is feeling it.

The SLA Problem Most Businesses Have Not Checked

Microsoft's standard M365 SLA covers core services: Exchange Online, SharePoint, Teams. Copilot is frequently excluded from those uptime guarantees.

This is not a quirk unique to Microsoft. AI features layered onto existing platforms often fall outside the formal SLA commitments for the base product. When Copilot goes down, Microsoft is not contractually obligated to restore it within any particular window unless your agreement specifically says otherwise.

Most businesses have not looked at this. They are buying AI-enabled subscriptions and assuming AI features carry the same uptime protection as email. Often they do not.

When the tool you have built workflows around carries no SLA, there is no recovery clock running on your behalf. That is a different kind of exposure than most IT risk inventories currently account for.

Why the Old Business Continuity Playbook Falls Short

Traditional business continuity planning was built around servers, networks, and SaaS applications. The underlying assumption was that when systems fail, people can still complete the work manually, just more slowly.

AI tools break that assumption in a specific way. There is no offline mode. If ChatGPT is rate-limited during a traffic spike caused by a major model launch, there is no local fallback. If Copilot's authentication layer fails, you do not get a degraded version. You get nothing.

Businesses that have trained their teams to open an AI tool before starting most knowledge work will see productivity drop proportional to how deep that habit runs. Those habits tend to deepen faster than anyone tracks them.

The AI governance problem most growing businesses have is not that they adopted AI tools. It is that they adopted them without building any formal inventory of where the dependencies now live. The outage problem is what happens downstream of that gap.

The Gaps That Show Up Most Consistently

For businesses in the 25-to-200-person range that have not formalized their AI tool usage, the pattern is pretty consistent:

Nobody has mapped which workflows now depend on AI tools. Teams adopt tools organically and no single person has a complete picture of where the dependencies live.

Most functions run through a single AI provider. No fallback if that provider has a rough morning.

The business continuity plan, if one exists, was written before these tools were part of daily operations. AI tools are not mentioned anywhere in it.

Nobody has confirmed which AI features are actually inside their existing SLAs. The assumption is coverage that may not be there.

None of this is unusual. It is also exactly the kind of thing that shadow AI usage patterns tend to make worse, because tools adopted outside of IT visibility can create dependencies the business cannot even see until something breaks.

Four Things Worth Doing Before the Next Outage

Map your actual AI dependencies. Go team by team. List the AI tools that are now part of regular workflows. How often are they used? What happens if access disappears for two hours? What about a full business day?

Check your SLAs. Look at what your AI-enabled platform agreements actually guarantee for AI features specifically. If Copilot, ChatGPT, or any other AI tool is not explicitly mentioned in the uptime terms, do not assume it is covered.

Document fallback processes for high-stakes workflows. If Copilot goes down during a sales cycle, what is the backup plan for proposal drafting? It does not need to be sophisticated. It needs to exist and the relevant people need to know about it.

Identify a secondary option for your most critical use cases. This does not mean paying for redundant AI subscriptions across the board. It means knowing what your team would use for its most important AI-dependent tasks if the primary tool went offline for most of a workday.

None of this is technically complex. The hard part is knowing where your real AI dependencies actually are. That kind of audit tends to fall through the cracks when IT planning is informal. It is precisely the work a managed IT partner should be doing on your behalf rather than something the business figures out the first time a vendor has a rough Monday.

Frequently Asked Questions

How often do major AI tools go down in 2026?

According to Ookla's analysis of U.S. Downdetector data, high-signal disruption days across major AI platforms averaged once every 1.8 days in Q1 2026. That is up from roughly one major disruption every six weeks during Q1 2025. A 750% increase year over year.

Is Microsoft Copilot covered by the standard Microsoft 365 SLA?

Not always. Microsoft's core M365 SLA covers services like Exchange Online, SharePoint, and Teams. Copilot is frequently excluded from formal uptime guarantees. Businesses should review their specific service agreements and, for enterprise plans, negotiate explicit inclusion.

What does AI business continuity planning actually involve?

Traditional continuity planning covers servers, networks, and SaaS apps. AI-specific planning adds a layer for AI tool dependencies: mapping which workflows depend on which tools, verifying SLA coverage, documenting manual fallback processes, and considering secondary providers for critical functions. It also accounts for the fact that most AI tools have no offline mode.

Which AI services have been the most disrupted in 2026?

Anthropic's Claude was the most volatile in Q1 2026, accounting for 39 of 51 high-signal disruption days in Ookla's analysis. Microsoft Copilot had notable outages on May 29 and June 1, 2026, each lasting several hours.

What is the business risk of depending on a single AI provider?

If your critical workflows all route through one AI provider and that provider goes down, there is typically no fallback. The risk is proportional to how embedded the tool has become. Businesses with AI tools in sales, proposal drafting, meeting management, or customer communication workflows face operational disruption when those tools are unavailable.