Mark Cuban and Will Smith just helped drop $16 million in AI startup Node, but when will AI bets pay off?
Artificial intelligence’s long, slow rise as the next big thing in tech continues to pull in cash, even as investors are forced to wait for their bets to pay off.
Case in point: AI startup Node’s $16 million in funding from the likes of Mark Cuban and actor Will Smith, announced Thursday, which continues a major venture-funding push into the technology, even as it struggles to make inroads at large businesses. The round — the largest to date for the 5-year-old company, which has raised $36 million — signals more momentum in the market, company officials insist. Being based in California doesn’t hurt, either: The state was tops in AI investments the last three months of 2018, accounting for $1.92 billion in investments over 53 deals.
A record $9.3 billion in venture funding was poured into AI last year, up 72% from $5.4 billion in 2017, according to PricewaterhouseCoopers and CB Insights’ PwC MoneyTree Report. However, the number of deals dipped to 466 last year from 533 in 2017 — its first drop in five years.
One potential reason for the that slowdown is that businesses have shown reluctance to go all-in on AI. The schizophrenic nature of adoption is outlined in a recent McKinsey Global Survey: While half the respondents say their organizations have deployed AI in some manner, only 21% have embedded the technology into multiple business units or functions.
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“Companies know that they need to use AI, they just don’t know how or how to derive sales from AI,” Cuban, owner of the NBA’s Dallas Mavericks, said in an email statement exclusively to MarketWatch. “Node’s greatest value is that it has proven it can drive sales immediately after installation and implementation.”
Node’s AI-as-a-service platform, called Artificial Intuition, is designed to predict business outcomes such as sales and marketing, allowing large enterprises to eventually build advanced AI into customer services and internal applications at affordable costs.
“There is huge disruption among Fortune 500 companies,” Node Chief Executive Falon Fatemi — who was hired by Alphabet Inc.’s GOOGL, +1.48%GOOG, +1.39% Google division when she was 19 as a sales strategist — told MarketWatch in a phone interview. “They need to leverage AI or die,” she added, noting that the average life expectancy of such companies is now less than 20 years, vs. 61 years in 1958.
One potential reason for the disconnect between funding and deployment is that AI is the rare technology that has more immediate financial upside in the consumer market than for enterprise, says Jessica Groopman, a research analyst specializing in AI at Kaleido Insights. Citing public data, she says that AI in consumer use (hardware, software, and services) should balloon to $42 billion in 2025 from $1.86 billion in 2016.
She says the enterprise market has greater long-term growth potential, particularly as smart cities and autonomous cars gain momentum. A recent Gartner report, by comparison, estimates the global enterprise AI market will grow to $6.14 billion in 2022 from $625 million in 2016.
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From Apple Inc.’s AAPL, +0.99% Siri to self-driving cars, technology displayed by machines for years has been a lightning rod of debate over its long-term impact. Tech’s largest players extol its benefits in pursuit of business opportunities and futurists like Max Tegmark, president of the Future of Life Institute, insist “amplifying our human intelligence with artificial intelligence has the potential of helping civilization flourish like never before — as long as we manage to keep the technology beneficial.”
So far, that’s been a big if. Adoption of the technology has been impeded by novices — who are typically intimidated by new technology that could cost them jobs or worse — and deep thinkers, who foresee machine learning that runs amok.
AI and robots, its critics whisper, will replace 7% of U.S. jobs by 2025, according to a report they cite by market researcher Forrester. Although 9% of jobs (8.9 million) will be created in fields like robot monitoring professionals, data scientists, automation specialists, and content curators, 16% in fields like office and administrative support will be lost.
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