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Unlocking Potential: AI's Impact on Software Adoption

Khadim Batti
Whatfix

DAP-er Things to Come: The Future of AI-Driven Software Adoption

Imagine a future where software, once a complex obstacle, becomes a natural extension of daily workflow — an intuitive, seamless experience that maximizes productivity and efficiency. This future is no longer a distant vision but a reality being crafted by the transformative power of Artificial Intelligence (AI). As AI advances, it is poised to redefine how we interact with technology, ushering in a new era of digital adoption that empowers enterprises to thrive.

The reality today is far from this ideal. Organizations are grappling with a deluge of software applications, each adding layers of complexity to the digital landscape. Employees, navigating a maze of applications and features, frequently encounter digital fatigue — a substantial barrier to business growth, innovation, and employee satisfaction.

According to Gartner Research, the average employee relies on 11 applications daily to perform their tasks. Over a third (36%) need proficiency with 11 to 25 applications, while power users (5%) manage 26 applications or more. This surge in application use contributes to "digital friction," with two-thirds (66%) of employees reporting moderate to high levels of friction while working with their software tools.

This complexity underlines a critical need for AI-driven solutions that not only streamline user experiences but also fuel digital transformation, reduce digital friction, and foster seamless, efficient workflows that propel businesses forward.

Reimagining DAP with AI

Digital Adoption Platforms (DAPs) have emerged as essential tools in helping users navigate complex software systems, offering in-app guidance, onboarding support, and ongoing assistance. By reducing the cognitive load of managing numerous applications, DAPs make software more accessible for employees across roles and departments.

The rise of AI is driving a transformative shift in the future of Digital Adoption Platforms (DAPs), paving the way for groundbreaking advancements in user experience. While GenAI agents and assistants promise to revolutionize user experiences, their successful adoption often hinges on effective onboarding and ongoing support. Organizations may introduce these tools without sufficient guidance, leaving employees unsure of how to leverage their full potential. AI-powered DAPs can bridge this gap by providing clear instructions, prompts and best practices for interacting with co-pilots and further extending the impact of each GenAI agent.

By empowering employees to understand and utilize these tools effectively, DAPs can significantly enhance user adoption and productivity. For example, generating reports on a CRM can be a tedious task and one that users often can get wrong, requiring repeated rework. When a user hovers over the "Reports" section of the CRM, a DAP can identify the user's role and their current context, and provide suggestions on the type of report the user may want to generate. One mouse click later, the DAP fires up the GenAI Assistant and feeds it the relevant prompt. The GenAI assistant then takes over and executes the requisite steps to deliver the report to the user. What would often take a user many minutes and rework is now reduced to mere seconds and a single click.

This is a simple illustration of how a DAP and GenAI assistant working in tandem can achieve higher user productivity for the organization while reducing user effort and digital friction.

AI-driven DAPs play a strategic role in digital transformation by aligning technology with business objectives, fostering a digital-first culture, and providing continuous data-driven insights. They enable employees to navigate software easily, ensuring that digital adoption efforts support key business outcomes, such as boosting supply chain agility to cut costs and meet market demands.

By adapting to individual user needs, DAPs encourage a culture of ongoing digital learning and readiness for new technology. With real-time analysis of user behavior and software usage, AI-powered DAPs highlight areas for improvement, allowing organizations to optimize user experiences, enhance feature adoption, and make informed workflow adjustments — ultimately increasing productivity and maximizing the value of digital tools.

The Future of Software Adoption

The journey toward a seamless, intuitive digital future has already begun. With AI transforming DAPs into intelligent, adaptive tools, we are closer than ever to a reality where software serves as an enabler, free from the complexities that hold businesses back. By empowering users with predictive guidance, automating tedious workflows, and offering real-time insights, AI-powered DAPs are bridging the gap between the technology we have today and the vision we aspire to achieve. This is more than just a transformation; it's a pivotal shift toward an empowered, productive workforce, driving innovation and growth on the path to an AI-enhanced digital landscape.

Khadim Batti is Co-founder and CEO of Whatfix

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Unlocking Potential: AI's Impact on Software Adoption

Khadim Batti
Whatfix

DAP-er Things to Come: The Future of AI-Driven Software Adoption

Imagine a future where software, once a complex obstacle, becomes a natural extension of daily workflow — an intuitive, seamless experience that maximizes productivity and efficiency. This future is no longer a distant vision but a reality being crafted by the transformative power of Artificial Intelligence (AI). As AI advances, it is poised to redefine how we interact with technology, ushering in a new era of digital adoption that empowers enterprises to thrive.

The reality today is far from this ideal. Organizations are grappling with a deluge of software applications, each adding layers of complexity to the digital landscape. Employees, navigating a maze of applications and features, frequently encounter digital fatigue — a substantial barrier to business growth, innovation, and employee satisfaction.

According to Gartner Research, the average employee relies on 11 applications daily to perform their tasks. Over a third (36%) need proficiency with 11 to 25 applications, while power users (5%) manage 26 applications or more. This surge in application use contributes to "digital friction," with two-thirds (66%) of employees reporting moderate to high levels of friction while working with their software tools.

This complexity underlines a critical need for AI-driven solutions that not only streamline user experiences but also fuel digital transformation, reduce digital friction, and foster seamless, efficient workflows that propel businesses forward.

Reimagining DAP with AI

Digital Adoption Platforms (DAPs) have emerged as essential tools in helping users navigate complex software systems, offering in-app guidance, onboarding support, and ongoing assistance. By reducing the cognitive load of managing numerous applications, DAPs make software more accessible for employees across roles and departments.

The rise of AI is driving a transformative shift in the future of Digital Adoption Platforms (DAPs), paving the way for groundbreaking advancements in user experience. While GenAI agents and assistants promise to revolutionize user experiences, their successful adoption often hinges on effective onboarding and ongoing support. Organizations may introduce these tools without sufficient guidance, leaving employees unsure of how to leverage their full potential. AI-powered DAPs can bridge this gap by providing clear instructions, prompts and best practices for interacting with co-pilots and further extending the impact of each GenAI agent.

By empowering employees to understand and utilize these tools effectively, DAPs can significantly enhance user adoption and productivity. For example, generating reports on a CRM can be a tedious task and one that users often can get wrong, requiring repeated rework. When a user hovers over the "Reports" section of the CRM, a DAP can identify the user's role and their current context, and provide suggestions on the type of report the user may want to generate. One mouse click later, the DAP fires up the GenAI Assistant and feeds it the relevant prompt. The GenAI assistant then takes over and executes the requisite steps to deliver the report to the user. What would often take a user many minutes and rework is now reduced to mere seconds and a single click.

This is a simple illustration of how a DAP and GenAI assistant working in tandem can achieve higher user productivity for the organization while reducing user effort and digital friction.

AI-driven DAPs play a strategic role in digital transformation by aligning technology with business objectives, fostering a digital-first culture, and providing continuous data-driven insights. They enable employees to navigate software easily, ensuring that digital adoption efforts support key business outcomes, such as boosting supply chain agility to cut costs and meet market demands.

By adapting to individual user needs, DAPs encourage a culture of ongoing digital learning and readiness for new technology. With real-time analysis of user behavior and software usage, AI-powered DAPs highlight areas for improvement, allowing organizations to optimize user experiences, enhance feature adoption, and make informed workflow adjustments — ultimately increasing productivity and maximizing the value of digital tools.

The Future of Software Adoption

The journey toward a seamless, intuitive digital future has already begun. With AI transforming DAPs into intelligent, adaptive tools, we are closer than ever to a reality where software serves as an enabler, free from the complexities that hold businesses back. By empowering users with predictive guidance, automating tedious workflows, and offering real-time insights, AI-powered DAPs are bridging the gap between the technology we have today and the vision we aspire to achieve. This is more than just a transformation; it's a pivotal shift toward an empowered, productive workforce, driving innovation and growth on the path to an AI-enhanced digital landscape.

Khadim Batti is Co-founder and CEO of Whatfix

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...