AI: The dawn of the data age

We have turned to senior industry profiles and experts to share insights about opportunities and challenges from AI today. Get our latest issue here!

How to access AI: The dawn of the data age report 

Get real: Artificial Intelligence has, since it was first coined in 1956, gone through a boom-bust cycle alternating between wild optimism and disappointment given an inability to commercialise AI. But exponential growth in computing power and an explosion in human connectivity since the introduction of the first smartphone in 2007, has given rise to the era of Big Data.


Going big: So much human activity online means vastly more and better data to analyse, with the computing power to do so at manageable cost, improving AI algorithms performance. As consumers, we interact daily through chat bots, virtual assistants, online shopping and media, biometric identification and fraud detection, to name a few examples. AI has entered the mainstream because it is now creating commercial value.


Just another technology: The hype around AI often leaves corporate leaders concerned about missing out. They should be, but not because AI is a disruption that will suddenly make most businesses irrelevant overnight. AI will be a tool for optimising business, to allocate resources more accurately and optimally, to improve sales mix and pricing, and to reduce costs. Not using it will increasingly be a competitive disadvantage and businesses must become more data driven.


How it works: The earliest AI algorithms were rule-based but advances in computing power and quantity of data have driven advances in machine learning, dynamic AI algorithms, which can be trained with data to find the best model for generating the desired output. A further refinement is deep learning, where neural networks “self-teach” the generation of optimal output based on the input data. Both machine learning and deep learning can improve over time from learning, as new data becomes available. We outline the differences and how they work.


What to do: AI is a big, complex field, and we offer some thoughts on what business leaders should focus on. Our checklist is based on AI platform provider Peltarion’s AI handbook for leaders, and includes:

  1. getting a basic understanding
  2. identifying business problems which AI could solve
  3. finding out what data is needed and is or could be made available
  4. finding and selecting AI tools which are future-proof and fit the business.

The experts

We have turned to senior industry profiles and experts to share insights about opportunities and challenges from AI today:

  • Photo: PhonlamaiPhoto/Gettyimages

    Danish listed IT solutions group Netcompany’s  CEO André Rogaczewski,

  • Swedish listed measuring and information technology group Hexagon’s Head of Technology Claudio Simao,
  • Swedish private AI platform provider Peltarion’s CEO Luka Crnkovic-Friis,
  • US private data analytics software group Palantir Technologies regional head Frida Nordström Nilsson, and
  • Nordea’s AI experts Anna Metsäranta and Hongyu Su.

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