How to close the 1,600% enterprise application visibility gap – and what it could mean for productivity
By: Uzi Dvir, Chief Information Officer, WalkMe
The rise of generative AI (GenAI) has given organizations incredible capabilities, but its transformative effect on business output remains largely unrealized. Despite the integration of AI tools designed to boost productivity and streamline workflows, digital inefficiencies are costing companies a lot more than one might think. WalkMe’s recently released 2025 State of Digital Adoption Report: Special AI Edition revealed that enterprises wasted an average of $104 million on underused technology in the last year alone. The report offers a comprehensive look at how enterprises are navigating digital adoption and Gen AI integration – and where critical gaps remain.
The study surveyed close to 4,000 senior executives and employees, as well as proprietary data from a subset of WalkMe’s user base, 1.5 million users across 2,400 enterprise applications. The sheer scale of enterprise AI applications might surprise even IT professionals; they now account for 28% of the average enterprise tech stack. That’s nearly 200 AI tools in the typical large enterprise, and this number is only growing. This, along with the consistent addition of non-AI software, has contributed to the application visibility gap, in which leaders dramatically underestimate the number of tools in their tech stack.The report found that executives believe that just 37 applications were in use across the business, when there is an average of 625 applications in use. That’s a 1,600% gap between perception and reality.
This fundamentally undermines digital transformation efforts, as organizations can’t effectively manage what they can’t see. The sprawl of applications, particularly AI tools, threatens to deepen transformation debt, which is the divide between innovation investments and realized value. It’s also created conflicting narratives in which executives express confidence in their digital transformation efforts, while employees are left to learn how to use and adapt AI software to their job roles and workflows largely on their own.
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Executive Optimism vs. Employee Reality
The number of applications in use across the enterprise is just one facet of this visibility gap. Vital change management programs are also impacted as executives are much more confident in their AI adoption efforts than they should be. The report found that while 78% of executives are confident in their organization’s ability to train users on new digital tools, only 28% of employees feel they have received sufficient AI training. This disparity helps explain why only 25% of employees report using AI to boost their efficiency, despite its widespread availability.
The disconnect grows deeper as executives emphasize strategic goals like performance analytics and workflow automation, while employees focus more on practical needs, such as application guidance and risk mitigation. These priorities should ultimately align – properly empowered and equipped employees drive business goals, yet instead of taking a people-first strategy, we are seeing a widescale failure of execution across industries. Companies are racing to implement AI without creating the support systems necessary for widespread adoption. In the innovation race, it seems some leaders have lost sight of who actually uses the software – employees. The result is a significant drain on productivity. The report found that employees spend 36 working days annually dealing with technology frustrations.
An effective digital adoption strategy helps mitigate these challenges, enabling enterprises to maximize the value of their technology investments, while providing employees with the tools they need to successfully perform their jobs.
A Winning Digital Adoption Strategy
Organizations that embrace digital adoption best practices see significantly greater returns on their technology investments. Key strategies include: investing in automating workflows, assessing current technology usage, creating content that drives engagement, implementing a digital adoption platform (DAP), streamlining user experiences across applications, tracking engagement metrics, and overall user training. These best practices ensure a more effective and seamless integration of technology and boil down to one commonality – they all focus on the end-user.
Yet, according to the report, only 7% of enterprises follow all digital adoption best practices. These elite digital adopters show significantly better AI adoption metrics, including:
- 90% of their employees use GenAI at work, compared to 63% in other organizations
- 90% of their executives understand how employees use AI tools, while 27% of executives elsewhere have this insight
- 49% have incorporated AI assistants into workflows, more than double the 21% seen in other enterprises
The software ROI differences are equally stark. Companies see just 22% ROI on digital transformation projects without any digital adoption best practices. Add just one best practice, and ROI jumps to 64%. Implement three or more, and ROI reaches 85%.
These elite digital adopters take a systematic approach to technology implementation, with a clear focus on user adoption. They have clear visibility into their tech stack, measure user engagement, automate processes, build content that boosts engagement, and unify experiences across applications. They are also on the path to reaching a state of HyperProductivity, an aspirational state where human capabilities and technology converge to achieve measurable gains in efficiency, innovation, and resilience.
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Where Do We Go From Here?
The growing awareness of digital adoption and digital adoption platforms (DAPs) has led to encouraging trends to help mitigate issues like the application visibility gap and transformation debt. These include the growth of dedicated digital adoption teams, or Centers of Excellence (CoEs), responsible for driving software adoption. 73% of enterprises now have teams of six or more people on these teams, up from 63% in previous years. Similarly, there has been a significant increase in DAP professionals across industries in recent years. These specialists use DAPs to create seamless user experiences across applications.
Finally, DAP technology is constantly evolving to incorporate AI that identifies and follows software usage to reduce the application visibility gap. These DAPs provide employees with specific guidance in the flow of work and complex task automation, ensuring quick, effective, and efficient digital transformation success and sustainable productivity gains. They also make for a much better digital employee experience. As enterprises continue their AI adoption journey, closing the application visibility gap and deploying effective digital adoption strategies and technology are critical to turn technology investments into measurable business results.
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