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

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Editorials

  • Ai Editorial: Emotional data in travel shopping - is it knocking on the doors of realism? +

    First Published on 23rd February, 2018 Ai Editorial: Facial coding or voice analytics can definitely help in understanding how travellers feels or what their intent is. But the key question Read More
  • Ai Editorial: 4 fraud-related issues that travel merchants need to handle diligently +

    First Published on 20th February, 2018 Ai Editorial: Loyalty fraud and account takeover, friendly fraud, inferior user experience and avoiding a risk-averse fraud strategy are areas that continue to garner Read More
  • Ai Editorial: To count on AI, ML and DL, bank on astute data strategy +

    First Published on 15th February, 2018 Ai Editorial: For one to reap maximum benefits from artificial intelligence (AI), machine learning (ML) and deep learning (DL), there has to be a Read More
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