Despite record AI investments, enterprises are hemorrhaging productivity to technology friction, losing an average of 51 workdays per employee per year, according to a recent WalkMe study on digital friction in the enterprise. This disconnect between AI spend and realized value signals a fundamental execution gap rooted not in technology capability, but in inadequate training, guidance, and guardrails for the workforce. And although Futurum Group’s 1H 2026 Enterprise Software Decision Maker Survey (n=830) found that 66% of enterprises now favor a platform-first approach, 41% are actively planning to reduce or consolidate app stacks, potentially suggesting that without proper user enablement, even the best platforms fail to deliver on their promise of driving better user engagement and utilization of core business tools.
What is Covered in this Article
- Enterprise productivity losses from technology friction despite AI spend
- The training and enablement gap undermining AI ROI
- Why guardrails and guidance matter more than features in enterprise software
- Execution risks and what CIOs must prioritize to close the human readiness gap
The News: A recent WalkMe study on digital friction in the enterprise reveals that organizations are losing 51 workdays per employee annually to technology friction, even as AI investment reaches new highs. Friction points include poor user experiences, fragmented workflows, and, critically, a lack of adequate training, guidance, and guardrails for workers navigating increasingly complex digital environments.
These findings come as enterprise buyers double down on AI, automation, and digital transformation, yet the operational drag from insufficient user enablement persists. According to Futurum Group’s 1H 2026 Enterprise Software Decision Maker Survey (n=830), the market’s tilt toward platform-first strategies has not eliminated complexity, and many organizations are actively seeking to consolidate redundant applications. However, without addressing the human side of the equation, including ensuring workers know how to use, trust, and get value from AI-powered tools, consolidation alone will not close the ROI gap.
Will Technology Friction Derail the ROI Promise of Enterprise AI Investments?
Analyst Take: The gap between AI ambition and on-the-ground productivity is widening, but the root cause is not a shortage of innovation or features. Enterprises are investing in sophisticated AI and automation, yet technology friction is quietly eroding the very ROI these initiatives are supposed to deliver. The real battle isn’t for more capabilities; it’s for ensuring that workers receive the training, guidance, and guardrails they need to translate powerful tools into measurable business outcomes.
The Human Enablement Gap and Technology Friction: The Real ROI Killer
Enterprise buyers have swung decisively toward platform-first strategies, with 66% now favoring unified suites over best-of-breed approaches, according to Futurum Group’s 1H 2026 Enterprise Software Decision Maker Survey (n=830). Yet, 41% are actively planning to reduce or consolidate their application stacks. The problem is not simply tool sprawl. It is that workers are being handed increasingly powerful AI-driven tools without the training or contextual guidance required to use them effectively. The WalkMe study’s finding that employees lose 51 workdays per year to technology friction underscores a reality that too many enterprises overlook: deploying AI without investing in user readiness doesn’t accelerate productivity; it compounds confusion. Even the largest platforms, such as Microsoft, Salesforce, SAP, and ServiceNow, may not deliver ROI if workers lack the skills and support to navigate new workflows confidently.
Training Deficits and Technology Friction Turn AI Investments into Sunk Costs
Enterprises are pouring capital into AI, but the translation from spend to value is inconsistent. According to Futurum Group’s 1H 2026 Enterprise Software Decision Maker Survey (n=830), GenAI capabilities (44.2%) and agentic AI (39%) now rank as the top two criteria for future software purchases, yet 73.8% of organizations are considering switching vendors between 2025 and 2028, either definitively, based on market conditions, driven by market conditions, or based on a vendor’s pitch.
This churn may reflect mounting frustration with the failure to see promised returns. When workers are not properly trained on how to leverage AI tools within their daily workflows, adoption stalls, workarounds proliferate, and the friction documented by WalkMe becomes self-reinforcing. Vendor switching will not solve a problem that originates in insufficient change management, inadequate onboarding, and a lack of ongoing user support. Organizations that treat training as an afterthought are effectively converting AI investments into sunk costs.
Technology Friction: Guardrails and Guidance Must Precede AI Scale
The market’s focus on AI innovation is blinding many CIOs to the real execution risk: deploying advanced tools without the guardrails and governance structures that enable safe, productive use. The 51-day productivity loss per employee identified by WalkMe is not just a cost statistic, but a warning that AI, automation, and digital tools are only as valuable as the guidance frameworks that surround them. Without clear guardrails—defining what AI should and should not be used for, establishing escalation paths, and providing in-the-flow-of-work support—workers are left to navigate complexity on their own, leading to errors, distrust, and disengagement.
Futurum’s research finds that platform consolidation is rising because enterprises are desperate for simplicity, but simplicity without structured enablement is an illusion. The winners in the next software cycle will be organizations that pair AI investment with rigorous training programs, real-time user guidance, and governance frameworks that build trust and competence across the workforce.
Read more about the WalkMe Global Study on the company’s website.
What to Watch
- Training Investment Parity: Will enterprises begin matching their AI technology spend with proportional investments in worker training and enablement programs?
- Guardrails as Competitive Advantage: Which organizations will establish governance and guidance frameworks that turn AI adoption into measurable, sustained productivity gains?
- Vendor Churn vs. Enablement: Does the surge in switching intent subside as organizations realize the ROI gap is a training problem, not a vendor problem?
- In-Flow Guidance: Can platform vendors and digital adoption solution providers deliver contextual, real-time guidance that closes the gap between tool deployment and worker proficiency?
Declaration of generative AI and AI-assisted technologies in the writing process: This content has been generated with the support of artificial intelligence technologies. Due to the fast pace of content creation and the continuous evolution of data and information, The Futurum Group and its analysts strive to ensure the accuracy and factual integrity of the information presented. However, the opinions and interpretations expressed in this content reflect those of the individual author/analyst. The Futurum Group makes no guarantees regarding the completeness, accuracy, or reliability of any information contained herein. Readers are encouraged to verify facts independently and consult relevant sources for further clarification.
Disclosure: Futurum is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum as a whole.
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Author Information
Keith Kirkpatrick is VP & Research Director, Enterprise Software & Digital Workflows for The Futurum Group. Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
