Srivastava: AI closes Asia MICE profit gap

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Srivastava: AI closes Asia MICE profit gap

Fragmented data and manual workflows keep revenues slow.

Asiaโ€™s Meetings, Incentives, Conferences and Exhibitions (MICE) industry is expanding rapidly, but many operators are struggling to convert demand into profit as response times lag behind planner expectations.

According to Cventโ€™s hospitality cloud leader in the Asia Pacific Navodit Srivastava, speed has become a commercial differentiator as the planner profile shifts throughout the region.

As he puts it: โ€œRevenue isn't lost on price, it's lost on response time. Talking about MICE speed is the new luxury, and AI delivers that at scale in Asia Pacific.โ€

Taking a โ€œdigital-firstโ€ approach

Srivastava noted that planners are increasingly digital-first, saying: โ€œToday, 76 percent of the planners are Gen Zs and millennials. They are highly responsive, and they are very comfortable with conversational technology.โ€

Keeping this in mind, delayed replies can cost business before a sales team even engages. Srivastava says of this: โ€œI imagine if a venue takes days to reply, the planner has already moved on.โ€

Likewise, Cvent data suggests the push toward AI is accelerating, given how 82 percent of planners throughout APAC are considering an increased use of AI.

However, Srivastava also warns that the real risk for MICE leaders is not about adopting AI. He said: โ€œIt's not adopting it and then quietly losing relevance.โ€

AIโ€™s revenue value comes from automating early-stage selling; as such, it enables instant responses with confident pricing, pre-qualified leads on venue websites and RFPs, and helps sales teams focus on high intent opportunities.

The barriers are there, butโ€ฆ

Nevertheless, barriers holding back the more widespread adoption of AI in the Asian MICE sector remain.

As Srivastava explains: โ€œMost AI challenges in MICE are not technical. They are operational and they are cultural, [tied in with] data fragmentation, stretched teams, as well as governance and trust.โ€

In which case, he recommends that companies start small, focus on clear ROI, build a strong data foundation, and keep humans in the loop.

 

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Srivastava: AI closes Asia MICE profit gap

Fragmented data and manual workflows keep revenues slow.

Asiaโ€™s Meetings, Incentives, Conferences and Exhibitions (MICE) industry is expanding rapidly, but many operators are struggling to convert demand into profit as response times lag behind planner expectations.

According to Cventโ€™s hospitality cloud leader in the Asia Pacific Navodit Srivastava, speed has become a commercial differentiator as the planner profile shifts throughout the region.

As he puts it: โ€œRevenue isn't lost on price, it's lost on response time. Talking about MICE speed is the new luxury, and AI delivers that at scale in Asia Pacific.โ€

Taking a โ€œdigital-firstโ€ approach

Srivastava noted that planners are increasingly digital-first, saying: โ€œToday, 76 percent of the planners are Gen Zs and millennials. They are highly responsive, and they are very comfortable with conversational technology.โ€

Keeping this in mind, delayed replies can cost business before a sales team even engages. Srivastava says of this: โ€œI imagine if a venue takes days to reply, the planner has already moved on.โ€

Likewise, Cvent data suggests the push toward AI is accelerating, given how 82 percent of planners throughout APAC are considering an increased use of AI.

However, Srivastava also warns that the real risk for MICE leaders is not about adopting AI. He said: โ€œIt's not adopting it and then quietly losing relevance.โ€

AIโ€™s revenue value comes from automating early-stage selling; as such, it enables instant responses with confident pricing, pre-qualified leads on venue websites and RFPs, and helps sales teams focus on high intent opportunities.

The barriers are there, butโ€ฆ

Nevertheless, barriers holding back the more widespread adoption of AI in the Asian MICE sector remain.

As Srivastava explains: โ€œMost AI challenges in MICE are not technical. They are operational and they are cultural, [tied in with] data fragmentation, stretched teams, as well as governance and trust.โ€

In which case, he recommends that companies start small, focus on clear ROI, build a strong data foundation, and keep humans in the loop.

 

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