Customers provide Tripedia with their information and travel preferences. AITD uses the data it has on previous reviews, accommodation, and flight availability. Through this, it recommends the best travel plan for them. This type of learning saves time and energy compared to traditional machine-learning algorithms. Using blockchain, the self-evolving system learns consumers' travel preferences as they emerge.

Technology is all set to transform the new age traveller experience. Meet the connected traveller, seeking instant responses, always impatient and ever demanding, always on the go. Digitally savvy, these travellers are growing fast, stimulating huge demand in the tourism industry. Their travel search planning begins with googling and ends with online agencies. Enticing these travellers put enormous pressure as the industry struggles to come up with innovative solutions to fulfil their needs.

Ever since the internet collided with travel, consumers have been using the power of technology and better data to plan, and then save, on their travel. NB: This is a viewpoint by Bala Chandran, co-founder and CEO for Flightsayer. Consider a hypothetical traveller, John, flying from San Francisco to London next week. If John is traveling on leisure, he checks Kayak, Expedia, Orbitz, and so on, to find a flight that meets his needs. John is faced with options to connect at Chicago, New York, or Dallas; he recognizes that connecting through Chicago in the winter is risky, and that missing his connection would be bad, but ends up connecting through Chicago anyway, basing his decision largely on price.