AI and mobility-readiness checklist for the next wave of augmented intelligence
The next wave of AI and mobility could significantly enhance enterprise mobile experiences and augment human intelligence. A quarter of CIOs surveyed by Forrester will adopt “point-and-click analytics with conversational user interfaces” in 2018. For 20 percent of organizations, AI and mobility will provide real-time decision recommendations.
Next-wave innovations such as Core ML are beginning to enable the development of proprietary cognitive applications with the potential to transform industries and professions. Prepared organizations will benefit from what Apple VP Brian Croll has called a “whole new generation of smart enterprise apps that get smarter and smarter the more we use them.” Here are the areas where you can expect to see the greatest amounts of transformation:
The 7 areas of AI and mobility readiness
Enterprises lacking a strong mobility atmosphere or the right groundwork for cognitive mobile will struggle to realize the full potential of AI. A recent Teradata study revealed 80 percent of enterprises already have AI in production, but 40 percent anticipate challenges due to infrastructure readiness.
While the following checklist isn’t exhaustive, it reflects many of the essential mobile technologies required for AI and mobility advancement. These technical and strategic requirements are applicable to all organizations and industries.
1. Cloud adoption
To accommodate the “compute- and memory-intensive AI,” Jack Gold, founder and principal analyst at J. Gold Associates LLC reported for TechTarget, “back-end services will need to run in the cloud.” Providing dynamic user experiences on the application layer will require cloud maturity, including a low latency network, cloud-based engines for in-stream big data processing and secure data storage.
2. Data governance
Mobile AI adoption can expose weak data governance processes such as ineffective data collection or identification. Before organizations can integrate data with applications for smart mobile experiences, they must understand data qualities. Machine learning is trained by continuous integration of new data, which requires strong stewardship and master data management.
3. Endpoint management
Applications in the future smart enterprise are likely to deliver ultra-personalized user experiences. This has the potential to significantly complicate the management of endpoints, users and data. Unified endpoint management can simplify existing mobility management and enhance AI readiness by simplifying provisioning, security, compliance and more.
4. Flexible network architecture
The modern digital workplace is defined by network access and security anywhere. Flexible network architecture — enabled by software-defined networking — will be a necessity for enterprises to deliver high-performing, secure AI mobile experiences. Effective network management solutions are already a cornerstone of enterprise mobility, but their value is likely to increase.
5. Development solutions
With AI specialists in short supply, organizations are wise to begin actively exploring solutions such as Core ML, which enable skilled mobile developers to quickly integrate mature machine learning capabilities.
6. Application governance
With AI poised to transform mobile applications into all-encompassing experiences, it’s important to strengthen understanding and documentation of the intersections among data, apps and people in the enterprise. Mobility leaders should understand the apps being used and work to refactor legacy applications for AI-powered upgrades.
7. Identity and access management
While AI is nearly certain to improve both the security and user experience of mobile authentication, a strong identity and access management (IAM) groundwork can provide the necessary bridge between legacy and smart apps to automate user-specific provisioning and enable single sign-on.
Strengthen your mobility and AI readiness
Nearly 85 percent of executives believe AI is key to achieve and sustain a competitive advantage, according to MIT Sloan. To capitalize on the transformative potential of AI and mobility, achieving the comprehensive groundwork associated with a strong mobility stance is a necessity.
The requirements shared here provide a solid checklist so enterprises can ensure they’re ready for what the future of AI holds.