In 2022, the biggest trend in customer care is providing a total experience. This includes:
- Customer experience
- User experience
- Employee experience
Interconnecting the experience of customers has become the foundation stone of successful businesses. Technology research and consulting company Gartner is predicting that by 2026, 60% of large enterprises will incorporate the total experience to transform their business model to achieve “world-class customer and employee advocacy levels.”
A total experience in action can be applied by using analytics and AI to learn client behaviors and to proactively respond to a client’s next action. This data can be used to create realistic training simulations for companies.
When identity services are unified, customers can move more through self-service onboarding and integrate the advisor’s view across multiple touchpoints. The research firm is advising clients that want to adopt a total experience approach to instruct teams pursuing experience improvement initiatives to partner with and learn from others. “Make all leaders of experience-related initiatives equally responsible for solving the combined needs of customers and employees,” says the report.
Gartner predicts that 75% of organizations that exploit distributed enterprise benefits will realize revenue growth 25% faster than competitors.
AI Engineering means making updates to AI models using integrated data and model and development pipelines to deliver consistent business value from AI. It combines automated update pipelines with strong AI governance. By 2025, it is predicted that 10% of enterprises that use AI engineering best practices will generate at least three times more value from their AI efforts than their competitors that do not.
Decision intelligence: Integrating Ai, with data and analytics creates a decision intelligence platform to support, augment and automate decisions. Systems like this are relatively new, and in recent years more businesses are adopting technology that streamlines difficult decision-making with quantifiable data.
Privacy-enhancing computation approaches allow data to be shared across ecosystems while preserving privacy. It is expected that by 2025, 60% of larger businesses will use multiple privacy-enhancing computation techniques in analytics, business intelligence, or cloud computing.
Generative AI is a type of AI that learns a digital representation of artifacts from sample data and uses it to generate new, original, realistic artifacts that are like training data but not the same. It allows generative AI to be an engine of rapid innovation.
Composable applications are packaged-business capabilities (PBCs) or software-defined business objects. PBCs create reusable modules that teams can assemble, rapidly creating applications and reducing time to market. PBCs with repeatable capabilities such as fraud detection, mean teams can assemble apps in low-code environments, saving hundreds of thousands of hours of manual effort. It is expected that by 2024, the design go-to for new SaaS and custom applications will be “composable API-first or API-only,” rendering traditional SaaS and custom applications as “legacy.”
Data fabric is an architecture and set of data services that provide consistent capabilities across multiple endpoints in hybrid multicloud environments. The architecture standardizes data management protocols across Cloud networks. It is predicted that by 2024, data fabric deployments will improve efficiency in data utilization four-fold. It can also half the time of human-driven data management tasks.
Cybersecurity mesh architecture is a distributed approach to scalable and flexible cyber control. The mesh centralizes policy orchestration but distributes enforcement of cyber security policy. This allows network managers to control access to different constituents and assets, making it harder for nefarious actors to exploit the entire network. Organizations adopting a cybersecurity mesh architecture can reduce the financial impact of singualr security incidents by about 90%.
Autonomic Systems are self-managing software systems that learn from their environments. In contrast to autonomous or automated systems, automatic systems can dynamically modify their algorithms without software updates. This allows rapid response change and management of complex environments.
Cloud-native platforms take advantage of the central elasticity and scalability of Cloud computing. By 2025, cloud native platforms are expected to serve as the foundation for more than 95% of new digital initiatives, up from less than 40% in 2021.
Hyperautomation is a business-driven approach to identify, vet and automate multiple business and IT processes. It requires multiple technologies and platforms, including RPA, low-code platforms, and process mining tools to work together in harmony. It is predicted that adaptive governance, powered by hyperautomation, will accelerate business performance.
- Mastering the Art of Online Business Presentations: A Comprehensive Guide - February 22, 2024
- Benefits of Networking for Online Businesses - February 8, 2024
- Leveraging Micro-Influencing: Powerful Digital Marketing for Ecommerce - January 10, 2024