Jonathon's AI Wiki

WalkMe State of Digital Adoption 2026

6 min read

Source: raw/Soda-Report-2026.pdf Publisher: WalkMe (SAP) Published: 2026 Methodology: Survey of 3,750 participants worldwide (1,700 senior leaders + 2,050 employees) at organizations with 1,000+ employees, combined with behavioral data from the WalkMe Digital Adoption Platform

“The AI Reality Check” — this flagship report argues that enterprise AI has moved from pilot to process, but the execution gap between investment and impact is widening. Organizations are spending more than ever on AI ($54M average DT budget, up 38% YoY) but only realizing 55% of the value, with 40% of spend underperforming due to adoption failures.

Key Takeaways

  • **39.4M (+38% YoY). 59% of budgets go to AI-related priorities. 52% of organizations now spend above $54M, up from 35%.
  • 40% of digital transformation spend underperforms because of user adoption challenges. The technology works; the adoption execution around it doesn’t.
  • Only 55% of AI value is being realized. Broader enterprise software isn’t far behind at 52%. The rest is going uncaptured.
  • **72M in employee time lost to friction, 20M in projects that failed to deliver ROI.
  • The Execution Gap = the distance between “we bought it” and “it’s working.” AI budgets nearly doubled but most employees use AI to rewrite an email or run a quick summary, then go back to doing things the old way. “That’s the most expensive spell checker ever built.”
  • Visibility gap: Executives estimate employees use ~35 apps; actual behavioral data shows 661 apps in use across the organization (1,789% gap). Leaders can’t fix what they can’t see.
  • 37% of workers skip AI entirely even when tools are available. 55% only trust AI for simple tasks. Only 12% are confident AI understands their work context.
  • 2.88 apps per task on average. When tasks cross 8+ apps, mid-task abandonment rate increases 1.8x.
  • Shadow AI: 45% of employees have used unapproved AI tools. 36% have used them with confidential data. Only 21% received any warning about unauthorized tool use.
  • Executive-employee perception gap: 41-67 point gaps across 7 dimensions of AI readiness. Executives and employees are describing different companies.
  • 8 hours per week lost to digital friction per employee (up 42% YoY). That’s 51 workdays per year.
  • 91% mean ROI for organizations with best-practice adoption programs. 4x ROI multiplier compared to those without.
  • Gartner projection: 70% of enterprises will shift to orchestration platforms by 2030.
  • 85% of respondents want a single integrated system for managing AI and software together.

Act 1: The Execution Gap

The core thesis: AI has moved from experimental to deployed, embedded, and funded at massive scale. But the returns aren’t following the money. The Execution Gap is what happens when massive investment meets a wall that technology alone can’t break through.

The visibility problem is severe. Leadership estimates ~35 apps in use; behavioral data shows 661. This 1,789% gap means leaders are making decisions about tools they don’t know employees are using.

Workers skip AI for real reasons:

  • 37% skip AI entirely, even with access
  • 55% only trust AI for simple, isolated tasks
  • Only 12% are confident AI understands their work context
  • Only 9% trust AI for high-impact decisions

The cost is measurable. Total cost of digital inefficiency climbed from 142M in 2025. Employee time lost to friction (50M.

Act 2: Why Work Breaks — The Missing Context

Where context disappears. A task starts in an email, moves to a CRM, requires approval in another system. AI helps with one step, then loses the thread. When context breaks, the employee fills the gap manually.

Trust breaks down at complexity. When tasks cross 8+ applications, mid-task abandonment rate increases 1.8x. The more complex the workflow, the less likely AI assists successfully.

Shadow AI is pervasive. 45% of employees have used unapproved AI tools. 36% have used AI with confidential company data. Only 21% received any warning. Organizations that don’t provide governed AI access push employees to ungoverned alternatives.

Executives and employees describe different companies. Across 7 dimensions — AI readiness, tool effectiveness, training adequacy, workflow complexity, satisfaction, data quality, integration quality — perception gaps range from 41 to 67 points.

Act 3: How People, Systems, and AI Work Together

The organizations getting it right aren’t spending more — they’re making the tools they already have work for the people who use them. They’re not running more advanced AI; they’re running better adoption.

In-flow support multiplier: Organizations providing guidance at the moment of need see 1.9x-3.7x improvement in task completion rates compared to traditional training.

ROI divide: Organizations with best-practice adoption programs see 91% mean ROI. Without structured adoption, ROI is approximately one-quarter of that.

What executives prioritize: 41% want to streamline IT complexity. 84% plan to invest in in-flow coaching capabilities.

Why traditional training fails: Training events happen once; the work happens daily. By the time employees encounter the actual workflow, they’ve forgotten the training. In-context guidance at the moment of friction is what changes behavior.

Try It

  1. Audit your visibility gap: Compare the number of apps leadership thinks employees use vs. actual (check IT asset management, SSO logs, browser extension data). The gap is likely larger than expected.
  2. Measure your execution gap: Track what percentage of AI tool licenses are actively used vs. purchased. “Active” means weekly, not “logged in once.”
  3. Address shadow AI proactively: Survey employees on unapproved AI tool usage. Provide governed alternatives rather than relying on prohibition.
  4. Benchmark against the $142M figure: Scale down to your organization’s size to estimate the annual cost of digital friction.

Open Questions

  • WalkMe is the publisher and also sells digital adoption platforms — how does this affect the framing? The data methodology appears rigorous (independent research agency, 3,750 participants) but the conclusions naturally point toward WalkMe’s product category.
  • The $142M cost figure applies to organizations with 5,000+ employees. What is a reasonable estimate for mid-market organizations?
  • How does the 91% ROI figure for adoption programs break down by industry? Is it applicable to marketing agencies?
  • The shadow AI stat (45% using unapproved tools, 36% with confidential data) deserves deeper investigation — what types of data are being exposed?

Graph View

Backlinks