7 Trends 2022: Increased resilience through increased knowledge
From Generative AI to refining hyperautomation, the upcoming year will focus on information and how it can be intelligently combined to gain new insights, improve processes, and take the customer experience to a new level.
Daniel Fallmann, Founder and CEO of Mindbreeze, briefly summarized the seven most important trends for the year 2022. The entire version of the Trends 2022 with more information and the strategic value can be downloaded here.
1. Generative AI against shortage of skilled workers
The trend to use AI is consistent worldwide. In addition to the right products, the introduction of AI systems also requires qualified specialists. However, these are hard to find. Generative AI works against this. Generative AI refers to machine learning methods that derive information from existing objects and data without manual and resource-intensive training of the AI models. This means that companies are able to extract valuable information from existing data with an out-of-the-box AI system and use it for further learning.
2. Customer engagement: flywheel instead of funnel
Instead of the familiar "purchase funnel" (funnel model), today's sales process is referred to as a "flywheel". Here, companies enter into a partnership with customers and exchange information on an ongoing basis.
How successful this model is dependent on the company's level of information about customer needs and on the employees' knowledge about developments in their own organization. In order to meet these requirements, an information-driven system is needed in the background to provide the necessary information with just one query.
3. Total Experience
Total Experience (TX) is about linking the discrete areas of Customer Experience (CX), User Experience (UX), Employee Experience (EX) and Multi-Experience (MX) for an overall experience.
One use case in the area of total experience is so-called case deflection: even before a customer completes his inquiry and contacts the help desk about a technical problem, they receive automated assistance from a smart system based on the problem description. Ideally, the customer can solve their problem immediately and the helpdesk does not have to process a ticket. Practical experience shows that this reduces the support workload by roughly 35 percent.
4. Interdisciplinary innovation is becoming increasingly important
Today, departments are increasingly being replaced by functional areas. One reason for this is that projects are increasingly being thought about and implemented across departmental boundaries.
This development creates new challenges in data preparation. For example, functional areas require cross-departmental information that is available in the company but is not appropriately linked or visualized.
5. Knowledge enhancement through augmentation of information
The possibilities of "augmented reality" in the business sector go far beyond the classic data glasses. In principle, all digital entities can be enriched with additional information, whether it be the radiological image of a bone or the 3D model of a component - and this applies for a wide variety of output devices.
Here, AI-based systems use methods such as machine and deep learning as well as speech recognition to ensure not only that the database required for augmentation is available, but also that the relevant information and content is provided proactively and in the right context.
6. Refinement of hyperautomation creates new knowledge
Hyperautomation will continue to occupy the industry in the coming year. Numerous companies are already automating repetitive business and IT processes.
However, the strategic approach plays a central role in the refinement of hyperautomation. Here, the focus is on dovetailing the individual automation projects and the added value that can be achieved. This consists of the recognition of patterns to support informed decision-making.
7. More resilience: AI-based solutions against knowledge defragmentation
The challenge here is to counteract the threatening defragmentation of information, which is exacerbated by decentralization. This requires clear guidelines from management and ideally the support of intelligent systems. These not only form a common knowledge base across all local and content-related distances, but also a reliable basis for rapid decisions.
In addition to the benefits already described, such as support for AI projects, realization of the Total Experience, augmentation of information or refinement of hyperautomation, AI-based systems also ensure greater resilience in the company as a whole.