Digital Experience Predictions in 2026

AI is now table stakes, but scaled value is still rare. McKinsey’s latest State of AI survey shows 88% of organizations are using AI in at least one business function, yet nearly two-thirds haven’t begun scaling AI across the enterprise and only 39% report EBIT impact at the enterprise level. At the same time, AI agents are moving quickly from curiosity to trials: 62% of respondents say their organizations are experimenting with agents, and 23% report scaling an agentic AI system somewhere in the enterprise.

For IT, the takeaway is straightforward: AI won’t compress time-to-resolution if experience data remains fragmented across endpoint tools, network tools, application monitoring, and service workflows. As we look toward 2026, the organizations that move fastest will consolidate first, creating end-to-end experience visibility with a single endpoint agent, and then use AI to turn that unified data into instant expertise for every operator.

(Source to include on publish: McKinsey & Company, QuantumBlack, “The State of AI” [November 5, 2025].)

Over the past year, we’ve learned that the future of digital experience isn’t about adding more dashboards or generating more alerts. It’s about reducing the time and effort required to get to the right answer, across the entire organization.

We’ve seen what happens when experience data becomes immediately usable in real environments:

• A global IT consulting firm avoided a significant productivity hit across 1,000 employees by using network intelligence to identify an ISP-level issue in minutes—not hours—and reroute users quickly.
• A large U.S. healthcare system uncovered thousands of endpoint failures (including blue screens, audio failures, and browser crashes), helping protect productivity for clinicians and staff.

The takeaway: when experience data is unified and actionable, teams don’t just respond faster—they prevent downstream impact.

See the Zscaler Digital Experience launch event for more information.

Predictions for 2026

Prediction 1: Consolidation becomes the execution advantage—not just a cost play

By 2026, consolidation will be driven less by license rationalization and more by a simple operational requirement: speed to clarity. Tool sprawl forces operators to swivel between consoles, reconcile conflicting signals, and escalate issues simply to gather context.

The winning model will start with a consistent foundation: a single endpoint agent that captures user experience signals across devices, networks, and applications—so teams can correlate what’s happening without manual stitching.

Why it matters: consolidation is the prerequisite for faster Zero Trust rollouts, actionable device health, and AI that can deliver precise answers.

Prediction 2: Zero Trust rollouts will accelerate when experience leads the rollout

Zero Trust adoption will continue to accelerate—but the differentiator won’t be policy ambition. It will be whether teams can prove and protect user experience through the rollout.

Organizations replacing legacy VPNs are already learning that the biggest obstacles often aren’t access controls. They’re the reality of distributed work: device instability, Wi‑Fi degradation, last-mile ISP issues, and SaaS path variability.

By 2026, successful Zero Trust programs will operationalize experience insights to:

• baseline performance before changes
• pinpoint friction during cutovers
• validate performance continuously after policy updates

Bottom line: experience becomes the accelerant for Zero Trust because it provides the evidence to move fast without breaking productivity.

Prediction 3: Device health becomes a first-class signal and remediation becomes a requirement

Devices are no longer passive endpoints. They’re complex systems that directly shape productivity and frequently the hidden root cause behind “the network is slow” or “the app is down.”

But by 2026, visibility alone won’t be enough. Leading IT organizations will require closed-loop device operations: detect → explain → remediate → verify.

That means expecting digital experience solutions to support safe, role-appropriate remediation such as:

• approved endpoint actions to address common degraders (e.g., disk cleanup, clearing browser/DNS caches, restarting specific Windows services)
• posture/readiness validation signals to isolate configuration-related friction (kept generic for external audiences)
• standard endpoint network diagnostics (DNS lookup, latency/packet-loss tests, route/path checks)
• verification loops that confirm whether the action improved experience

Why it matters: this is how service desks reduce escalations by resolving more issues at first touch with guardrails.

Prediction 4: Real-user experience becomes the primary truth; synthetic becomes supporting coverage

Synthetic monitoring still has value, but it doesn’t reflect reality at scale, especially in highly distributed environments. By 2026, teams will rely more on real-user experience signals from actual devices on real networks inside live applications.

The challenge won’t be data collection. It will be interpretation, correlating endpoint behavior, network path changes, and application performance without overwhelming teams.

Winning solutions will prioritize correlation and impact: who is affected, where the issue sits, what changed, and what to do next.

Prediction 5: The service desk becomes an intelligence layer, measured by prevented disruption

By 2026, service desk performance won’t be judged solely by ticket closure speed. It will be measured by how effectively teams:

• prevent escalations
• reduce user downtime
• resolve issues at first touch

This shift requires two things:

• instant access to cross-domain context (device, network, app, and access-path signals)
• dramatically lower cognitive load for first-line responders

And it must show up where teams work. Increasingly, customers will expect experience context and guided insights to be embedded directly into ServiceNow workflows, not trapped in separate tools.

Prediction 6: AI agents move into workflows, but only unified data makes them precise

Chat-based AI is a starting point, not the destination. By 2026, organizations will expect AI-powered troubleshooting to be:

• embedded in workflows like ServiceNow
• callable via APIs and automation
• integrated into operational views—not isolated conversations

But practitioners will demand technical fidelity. AI must be able to ground answers in concrete evidence like endpoint failures, path changes, and network quality signals without turning every responder into a specialist.

This is the unlock: AI becomes “instant expertise” only when it can reason over complete, end-to-end experience data. Without that foundation, AI scales guesswork.

Prediction 7: ISP performance incidents becomes a top priority category because “the internet” is now part of your stack

More enterprise traffic will traverse public internet segments and Zero Trust overlays, meaning user experience will increasingly depend on paths IT doesn’t directly control. The operational problem isn’t just performance variability; it’s proving where the variability lives (endpoint, Wi‑Fi, ISP, intermediate carrier, or application) fast enough to act.

This is why ISP performance will become a first-class incident category. Gartner reports that 70% of organizations struggle with network complexity and lack of end-to-end visibility, which is exactly what turns routine degradations into drawn-out war rooms. 

The winning model will look less like reactive troubleshooting and more like continuous, route-aware measurement:

• Lightweight, frequent probing and telemetry (latency, packet loss, jitter) along the user’s actual path to the app
• Baselines and automatic deviation detection to flag “what changed” immediately
• Aggregation by ISP/intermediary (e.g., ASN) and geography to pinpoint bottlenecks and quantify blast radius

Why it matters: when teams can rapidly identify ISP and carrier-driven issues with evidence, they reduce MTTR, avoid unnecessary escalations, and protect productivity at scale.

Closing

In 2026, the advantage won’t come from adding more AI on top of fragmented tools. It will come from consolidating experience signals end-to-end with a single endpoint agent, accelerating Zero Trust with evidence, and enabling every operator to act with expert-level context—directly in the workflows where work happens.