Technology investors are bulldozing cash into blockchain and artificial intelligence, but the “why” is just starting to emerge, as is the true nature of the innovation.
“You don’t tell a small business, ‘Hey, good news: We’re using blockchain to move your money,’ ” said Jonathan Ebinger, a general partner at BlueRun Ventures in Menlo Park, Calif.
BlueRun in late January closed a $130 million fund, its sixth. The firm invests in early-stage mobile software and financial services companies, which in the past included Kabbage, Waze and Coupa. BlueRun was also an early institutional investor in PayPal.

For the next wave in investment, BlueRun is partly focused on the Latin American startup ecosystem and data sharing industries.
Blockchain and artificial intelligence are part of the mix, but within the bounds of specific use cases. Both blockchain and AI are often positioned as innovations, but are more of a delivery channel than a new business, lending both to dangers of hype and marketing. AI venture capital is a $4.2 billion industry in the U.S. alone, according to
An early blockchain-oriented investment for BlueRun is
PayStand uses blockchain technology to remove friction from the accounts receivable and payable process, simplifying what it calls one of the "most notorious headaches" for businesses — sending and collecting money.
“Blockchain is like the internet,” Ebinger said. “You don’t use that as a differentiator. It’s is differentiator for providing high-quality service.”
Another recent investment is Visor, a Mexico City-based startup that operates a marketplace for financial institutions, corporations and cloud service providers to access and transact with small businesses.
In assessing credit risk, Visor is also attacking a complicated process. “Determining credit risk requires multiple processes,” said Tim Sloane, vice president of payments innovation at Mercator, adding that it uses more than one machine learning model.
It is possible to apply Robotic Process Automation to assist in pulling records from internal and third party databases for evaluation and nontraditional data about the business, its category, location and social network information. “Multiple machine learning models will be needed to evaluate these different data sets,” Sloane said.
AI will also attract investment for merchant self-checkout technology, said Ray Pucci, director of the merchant services practice at Mercator. “Consumers want convenience and immediacy, and with Amazon Go off to a successful start, other companies are attracting VC funding."
Businesses that enable opening banking or data sharing are also on BlueRun’s radar, Ebinger said, as PSD2-style data regulations influence deeper data transfers between banks and technology companies in other countries.
Despite the concerns over data sharing that have come up in consumer markets, the benefits for B2B, business lending and supply chains are clear, Ebinger said. It adds more information about business cash flow and enabling payment and merchant credit systems to embed deeper into business practices, he said. “This is a deep integration into a business on better terms than in the past.”