By Miguel Hanz L. Antivola

WHILE investors are enthusiastic about capitalizing on opportunities presented by startups leveraging artificial intelligence (AI), they also give high priority to assessing the practical applications and the specific needs being addressed, according to experts.

“We look at the deck: Is it viable? Is it scalable? Does it have economic potential? Does it solve a real problem?” Anna Irmina “Minette” B. Navarrete, co-founder and president of Kickstart Ventures, Inc., said in an interview.

In seeing traction, investors consider factors such as repeat purchases, feedback, and overall commercial output, she said.

“We don’t have a lot of traction data with AI,” Ms. Navarrete noted.

Traction may not weigh as heavy as other criteria for businesses in early stages, but they should find their use-case and appropriate business model to gain such, she added.

Investors, she said, start to look for evidence and substantial data regarding product reach when the company is three to four years old already.

According to Brian Dy, the head of research at Kickstart, ChatGPT, a popular AI chatbot, achieved a remarkable feat by amassing 100 million users within a mere two months after its launch.

A study by global market research firm UBS said that ChatGPT is the fastest-growing consumer application ever recorded. In January, it garnered an average of 13 million unique visitors per day, which is more than twice the number it had in December 2022.

To put this into perspective, Instagram, a widely popular social media platform, took two and a half years to reach the milestone of a hundred million users, while TikTok, another well-known social media app, took nine months.

The global AI market size is expected to reach $407.0 billion by 2027, with a compound annual growth rate of 36.2% during the forecast period of 2022-2027, according to a report by analytics firm MarketsandMarkets.

“This large TAM (total addressable market) leads us to believe that there is significant opportunity for growth and profitability in AI technology,” Mr. Dy said.

However, Ms. Navarrete noted the importance of skepticism when reading through TAM, as there are many data providers available online to source such information. “It is very easy to look and be impressed,” she said.

“We must also look at the direction of growth and the trends surrounding the market,” she added.

She also said that technology tends to go through a “hype cycle” where there is a widespread belief that it has the potential to revolutionize the world and address all its challenges.

While there may be some truth to this, she said, investors should assess factors such as market readiness, costs, and consumer openness, especially for businesses based on AI.

Timing is also a crucial aspect that investors consider when evaluating potential partnerships with AI-driven businesses, Ms. Navarrete said.

“In technology, so much will change, but people will not frequently change,” she added.

Investors look for credible people in a team behind a viable product or solution. They must have mastery in the field and show signs of integrity.

“We look for a management team who can overcome difficulties, make good choices, and go their way around gray areas,” she said.

According to Mr. Dy, investments in technology-driven startups, including those focused on AI, revolve around distinguishing between “must-have” and “nice-to-have” concepts. Investors are advised to prioritize and favor the former.

“Labor is affordable, and companies may find it more cost-effective to hire someone to do the functions that AI is tasked with,” he said.

“If the technology is a ‘must have,’ then that simply makes it stickier and more scalable over the long run,” he added.