Emerging Technology Trends

May 3, 2018

SAP recently posted a new report titled: Trend Report 2018 - Emerging Technology Trends. This report takes a look at new technology trends that will impact all businesses over the next few years. Here are a few major hightlights from the report.


EMERGING - Technology not yet used at scale


  • Immersive Technologies

  • Conversational Systems

  • Robotic Process Automation

  • Machine Learning

  • Contextual Workspace

  • Digital Twin

  • Blockchain

  • Neuromorphic Hardware

  • Quantum Computing

ON THE  HORIZON - Technology or concepts in prototyping or design phase


  • Autonomous Robots/Drones/Vehicles

  • Intelligent Assistants

  • Brain Computer Interfaces

  • Human-Machine Convergence

  • Advanced Robotics

  • Bio Computing

  • 4D Printing


Enhancing the Digital Experience

Two  distinct  but  merging  technologies  are  behindimmersive technologies: Virtual Reality (VR), com-puter-generated,  digital  environments  that fully immerse  users  in  a  virtual  world  and  AugmentedReality (AR), which overlays digital information onthe  physical  world  and  augmented  reality operating environments.


Companies  are  already  experimenting  in  pilot  proj-ects and the technology has the potential to becomethe  next  computing  platform.  Mobile devices are currently at the center of the implementation of AR/VR and they could replace large parts of the PC landscape. We  observe  a  coevolution  with digital  twins and  gaming.  Hardware  is  important, but  the  user  experience such  as  easeand  comfort  of use and  real-time performance as well as a structured con-tent  are  keys  for  success.  High  dataquality  including realtime  analytics  is also a prerequisite.


The Algorithms to Make Everything More Intelligent

The success of Google AlphaGo in 2016 marks the rise of machine learning. It is based on the idea that machines  can  learn  for  themselves  if  they  get access to large volumes of data and comprises deep learning, neural   networks and   natural-language   processing  algorithms.  The  technology has very  strong  connections  to  big  data  and  real-time  ana-ytics  but  needs high  quality  data  and  a  clear  pro-cess to be trained.


Machine learning and IT vendors will inbuild intelligent  capabilities  into business  intelligence  systems,  analytics  and  into  many  devices,  robots  and  machines.  This  is  rising  a  number  of  ethical  questions  such  as  the future  of  our  work, how machine learning will affect our behavior,  how  can we  guard  us  against  mistakes  and unintended consequences, and how do we stay  in  control.  Extracting  the  qualitative  data  needed for machine learning training is a challenge, as well as finding experts.


Machine learning can  be  used  to  solve  a  tre-mendous  variety  of problems and  automate  tasks that had to be handled by humans before, such as translations,  face,  speech  and  pattern  recognition, text analytics, analyzing large data sets  and  more.  The  technology  promises  to  save  costs  and improve  the  quality  of  work  by  automating  80%  of  the  roughly  50%  work activities that are suitable for automation. Most of todays’ knowledge work contains the following activities:  pattern  recognition  (99%),  generating and understanding natural language (75%), optimizing and planning (30%).


Blockchain – Decentralized Trust

Blockchain is  based  on  distributed ledger  technology, which records data (transactions, files, or information) across a peer-to-peer  net-work. Participant can see the data and verify (or  reject) it  using  consensus algorithms. Approved data is entered into the ledger as a collection of “blocks”,   stored   in achronological“chain”,and secured through cryptography.


The disruptive nature of Blockchain is its ability to move control over interactions from centralized systems to distributed  users.  For  now, legal and institutional  barriers  restrict  a shift away from central systems but blockchain has a high disruptive potential for all trust-bound activities.


Four types  of  blockchain  are  evolving: the consortium (controlled by a preselected  group), the semi-private (a single company granting access to any user), and private and public blockchains  like  Bitcoin  and Ethereum. Up to now the consortium model  is  the most accepted model for business although the technology is still unproven in a larger business context.


Blockchain  might  make  systems  more  transparent, potentially more democratic and help inventing new trust models. It could improve cash flow, compliance and  accountability,  it  could  lower  transaction cost sand reduce fraud. Furthermore, it offers a huge potential to unify flows of payments, physical goods and information in the rather chaotic relationships among untrusted parties, like in complex supply chains.


Blockchain will impact organizations and businesses firstly in a first non-disruptive, incremental change, by leaving processes unchanged and realizing cost savings and process improvements. A use case will start around verifications, smart contracting, transparency and accountability,  sharing  and leasing models, rights, and IP and government records. The second wave of block-chain will radically restructure existing industry sectors or business ecosystems into systems of trust

View the full report on the SAP website


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