Thought Leadership

Ai’s Thought Leadership section is our way to keep you informed and inspired!

Travel and flying are (usually!) all about fun. And airlines, along with various stakeholders, strive to sustain the joy of flying and travel.

But keeping pace with today’s consumerism is complex. Today the blend of technology, content, data, analytics and cloud promises to transform the experience of flying.

Our editorial covers loyalty, ancillary merchandising co-brand cards, payments and fraud. You can click on any of the sub menus to have quick access to all our articles in these areas.

Count on us as your resource for everything from high-level insights to articles gauging the pulse of the travel industry.

Be it for the next idea, embracing change in this dynamic and unique industry, targeting new sources of revenue, combating fraud or delivering a superlative experience, Ai’s articles touch upon such relevant areas.

We are also open to suggestions/ feedback.

We intend to nurture a platform for a constructive dialogue that results in customer-centricity.

If you are fond of Tweeting, then you can follow our official Twitter account - @Ai_Connects_Us

Happy travelling

The Ai Team

This email address is being protected from spambots. You need JavaScript enabled to view it.

Editorials

  • Ai Editorial: Airlines need to be “organizationally ready” for modern commerce +

    First Published on 23rd October, 2018 Ai Editorial: Talking of a standard like NDC, a module or an engine etc. or merchandising and distribution is pointless if airlines can’t overcome Read More
  • Ai Editorial: Why easyJet’s “Instagram-inspired trip feature” is a super move? +

    First Published on 19th October, 2018 Ai Editorial: Be it for capturing the essence of travel or having an early say in the booking funnel or strengthening 1st party data, Read More
  • Ai Editorial: Machine learning and fraud – “scores” not important; results matter +

    First Published on 16th October, 2018 Ai Editorial: There are key pointers – denial rates, false positives and fraudulent transactions – that underline the performance of any machine learning technique Read More
  • 1
  • 2
  • 3
  • 4
  • 5