These six trends for 2018 illustrate how technologies like AI and big data can translate into real added value for companies

These six trends for 2018 illustrate how technologies like AI and big data can translate into real added value for companies



The opportunities offered by modern technologies are skyrocketing. The only question is how to navigate them to find the solutions that lead to business success. Knowledge management and AI specialist Mindbreeze summarizes the most important trends that create tangible added value.

 

1. Applied AI: practical applications instead of marketing hype

Artificial intelligence (AI) is one of today's hottest megatrends. IDC expects the market to multiply from just under $8 billion in 2016 to an estimated $47 billion in 2020.

The year 2018 will bring more clarity: Concrete practical applications will help companies set their AI strategies on a solid footing and define the anticipated added value. The sectors that are already benefiting from concrete AI solutions include areas such as

  • automated document processing
  • assistance systems for healthcare
  • recognizing high potentials in the company
  • smart field management and
  • intelligent customer service

 

The future-oriented technologies that make all this possible include

  • Narrow AI: Although also referred to as "weak artificial intelligence," in fact, narrow AI has some powerful applications due to the very fact that it can fully exploit its strengths within deliberately narrow limits.
  • Deep NLP: Natural language processing (NLP) technology: is the prerequisite for machines to be capable of processing human speech. Combine this ability with deep learning, which entails the automated and continuously improving recognition of specific attributes, and you get assistance systems that offer practicable support for departments in their specific activities and processes.   

 

2. Business process transformation instead of business process improvement

In recent years, business has focused on optimizing processes, which translates primarily into increased speed as a result of the more intelligent use of tools. In 2018, the trend from purely quantitative measures to a qualitative approach will pick up sharply.

Investment in modern technologies such as artificial intelligence and enterprise search is heading stronger in the direction of rethinking complete processes: Many traditional workflows are becoming obsolete as a result of end-to-end automation, while others are being upgraded to a new level of quality from which innovative ways of gathering and distributing information can emerge. This results in measurable added value. And freeing up resources opens up a host of opportunities for developing new and promising business models.

A trailblazing method for strategically transforming business processes is by means of "digital twins": This term means that physical products, systems, and processes are mirrored on the digital level as a software representation. With the help of AI and machine learning, new business processes can be simulated and can continuously adapt to ever shifting conditions.

 

3. Personalization & contextual reference: tailor-made information instead of the scattergun approach

The mere collection or random provision of information doesn't really create added value for companies. Employees are still left on their own with the tedious and time-consuming process of filtering out any relevant data from the vast mass of information.

The aim of every modern information management initiative simply has to be to ensure that every employee receives exactly the information they need for their specific tasks, depending on their position and the workflow. As a result, in 2018 companies will increasingly focus on automated extraction and personalized distribution of information.

Any system capable of doing this needs to combine several technologies under one roof. These include AI, big data, enterprise search, and machine learning to ensure that the longer the system is in use, the more precisely it can deliver. 

 

4. Conversational platforms: interacting with information instead of painstakingly searching for it

Chatbots bear the promise of automatic interaction with systems or organizers based on human language, enabling swift response to customer inquiries without using staff resources. However, the lion's share of chatbots used today can only partially accomplish this mission. That's because the solutions are typically based on simple decision trees that aren't really capable of simulating intelligence very well. Not only that, content has to be entered manually. Large companies that have thousands of products in their portfolio and are potentially confronted with millions of possible queries are fighting a losing battle with this method.

As a result, in 2018 companies will increasingly invest in conversational platforms that go far beyond the capabilities of today's chatbots. The principle is not unlike that of the chatbots: The employee or customer receives a practical answer to a specific question − fast and accurate assistance − the very definition of customer service. In the background, however, conversational platforms use a highly complex Al and NLP system that is scalable across all levels and renders manual servicing unnecessary.

 

5. Unified Everything: a single information pool instead of data silos

The idea of making information and processes available irrespective of the particular application or data silo is nothing new. Such approaches are known as unified information access or unified collaboration.

With "unified everything" and modern technologies, this idea is acquiring a new dimension. The approach, which will be more vigorously pursued in 2018, will enable a company's employees to enjoy an unprecedented "information experience", something that is already a reality in the mobility sector with its smartphones, tablets and apps.

In order to achieve the goal of unified everything, an enterprise-wide intelligence level is implemented that bundles and consolidates information across the boundaries of data silos, applications, and formats.

 

6. AI-optimized hardware: turbo intelligence instead of paralyzing inefficiency

Due to the rapidly increasing volumes of data and bursting data silos, there is an ever-growing demand on hardware to not only store this data, but also to transform it into usable information. This challenge can no longer be met effectively using conventional systems. For this reason, systems optimized for the processing of AI-relevant tasks will increasingly be used in 2018.

Take NVIDIA, for example −the Tesla accelerated computing platform, whose GPU has proven to be extremely effective in solving the most complex computing problems. Thus, the trend for AI is also clearly heading in the direction of task-optimized hardware.

 

The take-away: AI at your fingertips

The six trends outlined here have one thing in common: The technologies and solutions presented in these top trends already exist and are a central part of everyday business for top companies.

This demonstrates that concepts like AI and big data, which many still only vaguely comprehend, can generate tangible added value for companies already today.