We are just beginning to realize the potential for application development productivity improvements driven by generative AI. However, we should soon expect a tidal wave of apps that IT admins will need to manage. This will inevitably present challenges for enterprise IT teams responsible for deploying, managing, securing, and updating applications at scale. AI is already impacting many enterprise functions (HR, Marketing, Sales, Support, etc.), but today I want you to dive into this AI development trend and how it will inevitably impact how you think about end-user application management strategy. 

AI’s impact on app development 

Preliminary studies and anecdotal assertions from enterprises have noted the marked impact generative AI has had on application development teams, employee productivity, and frontline task completions rates. A study by McKinsey noted significant reductions across key development task workflows including: 

Source: Data from McKinsey, June 27, 2023.

These already impressive milestones hint at the vast potential that GenAI could eventually lead to. AI thought leaders like Sam Altman, CEO of OpenAI, even foresee the elimination of human capital investments associated with designing, developing, marketing, and selling solutions to customers. 

“We’re going to see 10-person companies with billion-dollar valuations pretty soon … in my little group chat with my tech CEO friends there’s this betting pool for the first year there is a one-person billion-dollar company, which would’ve been unimaginable without AI. And now [it] will happen.”

Why this is salient for your digital transformation 

I observe investors starting to do more with less. They are positioning funds dedicated to taking advantage of the future ease of company and application development, and the expected minimal investment it will require. Chamath Palihapitiya, Founder/CEO of Social Capital and “All-In Podcast” fame, is positioning a fund (8090 Incubator) to capitalize on the proliferation of applications that inevitably will result due to the new business and development scaling possibilities. He asserts that your favorite enterprise application will soon face competing solutions that can provide 80% of the existing premier application brands’ features but that will sell at a 90% discount.

A move toward generative AI and AI-infused applications and task workflows will also be buoyed exponentially by trends like low-code/no-code platforms, generative AI APIs, continued cloud dominance, AI-driven digital work, composable architectures, and 5G/edge computing trends. These significant AI trends have Gartner estimating that more than 80% of enterprises will have used generative AI APIs or deployed generative AI-enabled applications by 2026, up from less than 5% in 2023. Considering these trends, I postulate that both the pace of innovation and AI’s inherent continuous-learning nature will continue toward a future where artificial general intelligence (AGI) will be increasingly accepted as an inevitability. 

How can a prudent IT or app admin prepare for app proliferation? 

These GenAI-driven trends should naturally urge prudent and inquisitive IT/application administrators to be prepared with a scalable platform ready to handle the amplified proliferation of applications to come. As part of this important solution evaluation and AI-led transformation exercise, I’ve assembled the following top five problems encountered, the top five benefits a solution could provide, and the five key value metrics to track and guide improvement toward your objectives: 

Five top app management problem areas include: 

1. Application deployment and management workflow complexity
2. Inconsistent/inadequate user experience across devices
3. Security and compliance risks in application usage
4. Lack of visibility and control over application performance
5. Challenges supporting remote and hybrid Workers, including access 

Five top app management solution benefits an AI-driven work platform like Omnissa should include: 

1. Unified platform for application delivery and management, simplifying app deployment, agile updates, and lifecycle management across all devices from a central console, at enterprise scale.
2. Seamless user experience by enabling access to applications and data from any device, whether through virtual desktops (Horizon) or mobile and desktop apps (Workspace ONE), ensuring a consistent digital experience.
3. Security policy enforcement such as multi-factor authentication (MFA), end-to-end encryption, and secure app containerization, ensuring that only authorized users can access sensitive applications while maintaining compliance with industry regulations.
4. Comprehensive monitoring and analytics, guided root cause analysis and predictive analytics, giving IT teams visibility into app performance, user activity, and system health. This helps identify bottlenecks, optimize app delivery, and ensure smooth application usage.
5. Secure applications delivery to remote workers, regardless of device or location, ensuring business continuity and productivity with Horizon's virtual desktop infrastructure (VDI) and Workspace ONE’s unified endpoint management 

 Five key value metrics to track should include:  

1. Time to deploy applications: Measures the time taken to deploy new applications across various devices and platforms before and after implementing Omnissa solutions. A reduction in deployment time signifies streamlined application delivery processes, faster onboarding of new software, and less IT overhead for manual deployments.
2. User productivity and application access time: Measures how quickly users can access applications and data across devices, along with reduction in login times or delays. An increase in productivity and reduction in time spent switching between devices and accessing applications indicate improved user experience and consistency.
3. Security incidents related to application access: Tracks the number of security incidents or compliance violations tied to application usage, such as unauthorized access, data breaches, or failed audits. A decrease in security incidents highlights enhanced security measures, such as better authentication, encryption, and secure application access policies.
4. Application performance and availability: Measures the uptime, responsiveness, and availability of applications across the enterprise, along with user-reported issues and system health. Increased application uptime and reduced performance complaints reflect better app management, optimization, and proactive issue resolution through Omnissa monitoring tools.
5. Support ticket volume for remote application access issues: Tracks the number of IT support tickets raised for issues related to remote or hybrid workers accessing applications (e.g., connectivity, access errors, or slow performance). A reduction in support ticket volume demonstrates that remote access issues are being resolved or prevented, reflecting improved app delivery, stability, and user satisfaction for remote workers. 

AI is likely to change many of today’s IT norms in the future, but ensuring you are working with the right application lifecycle management platform now is still critical. With the right platform, you’ll be prepared to handle the growing trend toward a proliferation of applications. By taking one simple but crucial step, you will be able to successfully navigate this ambiguous AI-driven digital transformation.