The holidays are approaching, and generative artificial intelligence shows no sign of slowing down.
A provisional deal on landmark European Union rules governing the use of AI was reached Dec. 8 after three days and 36 hours of political back-and-forth.
The AI Act makes Europe the first major world power to enact laws around AI, and the bill covers various aspects of AI use, including governments’ use of AI in biometric surveillance and the regulation of AI systems like ChatGPT.
But is the EU’s first-of-its-kind AI Act historic, or prehistoric? PYMNTS explored the key takeaways of the new rules, which won’t go into effect for another two years, Wednesday (Dec. 13).
As for the rest of the AI landscape, progress continued unabated this week. From ongoing enterprise efficiency capture across sectors, to model upgrades and advances, and even the very future of work itself, this is the weekly pulse check on the top AI news and innovations PYMNTS has been tracking.
Read also: How AI Regulation Could Shape Three Digital Empires
The healthcare sector is home to one of the biggest mismatches between potential impact and actual use when it comes to AI adoption.
“AI has been revolutionizing medicine over the last few decades,” Forward CEO Adrian Aoun told PYMNTS. “The problem is that it hasn’t been doing it in the ways that we care about.”
“One of the reasons AI hasn’t gotten into the business of care is that everything goes through the doctor,” he added. “There’s not an operating system for everything to plug into. So, you realize things need to be built for a world of AI in order for that AI to work and scale.”
But things are starting to shift. Alphabet-owned Google introduced Wednesday (Dec. 13) a new family of generative AI models fine-tuned for the healthcare industry, called MedLM.
Beyond the healthcare space, Google’s approach of providing domain-specific models that can be built out further with task-oriented training offers clues into how enterprise AI can be best monetized and scaled in the future.
Despite the appearance that Google is chasing after its other tech rivals, the Mountain View tech giant is winning the AI race in an important way: Google has repeatedly proven that it can build state-of-the-art AI completely in-house, and the tech giant on Wednesday also debuted Gemini Pro for enterprises.
Fears of jobs being replaced by AI have swirled ever since the technology was first hypothesized, and on Monday (Dec. 11), the AFL-CIO and Microsoft announced they partnered to explore workers’ input into AI development.
The collaboration has three goals: to share information among labor leaders and workers on AI technology trends; to get worker input and expertise on AI development; and to help shape public policy that supports frontline workers’ skills and needs.
It comes as the MIT Schwarzman College of Computing and the MIT Washington Office have published a policy brief with recommendations on the governance of AI titled, “Can We Have Pro-Worker AI? Choosing a Path of Machines in Service of Minds.”
The policy brief from MIT wants to ensure that AI is used in such a way that it creates and supports new jobs and capabilities for workers. The MIT cohort suggested five federal policies they consider to be the most important.
Elsewhere, news publishers are alarmed by what Google’s AI means for their business, as Google’s move to integrate its “Search Generative Experience” AI tool has underlined the dangers for media companies of depending on the tech giant to bring their stories to readers.
“AI and large language models have the potential to destroy journalism and media brands as we know them,” said Axel Springer Chairman and CEO Mathias Dopfner.
His company, which owns U.S. publications including Business Insider and Politico, announced its own deal to license content to OpenAI Wednesday.
“We want to explore the opportunities of AI-empowered journalism — to bring quality, societal relevance and the business model of journalism to the next level,” Dopfer said when announcing that partnership.
On the robotics and automation front, fast-casual salad chain Sweetgreen opened its second automated location, featuring its “Infinite Kitchen” technology, Tuesday (Dec. 12) in Huntington Beach, while McDonald’s is tapping Google Cloud’s generative AI tools itself as restaurants increasingly integrate the technology into more parts of their business.
“[AI] is the most likely general-purpose technology to lead to massive productivity growth,” Avi Goldfarb, Rotman chair in AI and healthcare and a professor of marketing at the Rotman School of Management, University of Toronto, told PYMNTS. “…The important thing to remember in all discussions around AI is that when we slow it down, we slow down the benefits of it, too.”
Meanwhile, PYMNTS Intelligence this week explored the ethical implications of using AI in retail, as well as the technology’s impact more broadly within the industry.
AI’s innovations aren’t solely used by good actors. Bad actors and cybercriminals have access to the technology as well.
PYMNTS Intelligence found that fraud losses at financial institutions are up 65%, with both sides turning to AI as they continue on the good-AI-versus-bad-AI dichotomy.
OTTO Payments, the payments division serving the OTTO marketplace, announced Tuesday (Dec. 12) that it has adopted Hawk AI’s solutions for anti-money laundering compliance.
Within other payment innovations, tokenization — where sensitive information is replaced by unique algorithmically generated numbers and letters — has gained wide acknowledgment in commerce, which has led to increasing interest by fraudsters looking to use tokenization’s potential for illicit purposes, James Mirfin, Visa’s global head of Risk and Identity Solutions, told PYMNTS.
In response, Visa announced Wednesday that it launched Visa Provisioning Intelligence, a new service for clients that leverages advanced technologies including AI and machine learning to predict token fraud by assigning risk scores to provisioning requests so that issuers can make informed decisions about whether to approve or deny those requests.
It isn’t just fraud where AI can trip up a business. The Securities and Exchange Commission is querying how investment advisers use AI.
Meanwhile, the Financial Stability Oversight Council for the first time identified the use of AI in financial services as a vulnerability in the financial system.
It was a busy week more broadly within the AI landscape.
On Wednesday, retail planning solutions firm Relex debuted AI-driven price optimization capabilities, while on Tuesday Snap announced Snapchat+ now has more than 7 million subscribers and unveiled the latest generative AI features it added to the subscription tier of its instant messaging app, Snapchat.
In the startup space, Nvidia solidified its position as a prominent AI investor, participating in 35 deals in 2023, marking an increase from the previous year and making it one of the most active investors in the AI ecosystem.
Essential AI emerged Tuesday from stealth with $56.5 million in new funding. The AI startup, founded by two veterans of Google, developed technology dubbed “Enterprise Brain” that can use AI for corporate functions like data analysis and automating monotonous tasks.
Also on Tuesday, Blue Yonder announced the addition of generative AI capabilities to its range of supply chain solutions.
Mistral AI, a European provider of AI solutions, partnered with Google Cloud to make generative AI more open and accessible to developers and businesses worldwide, while Smartpricing raised $14 million to enhance its apartment and hotel sector revenue management software.
PYMNTS has been covering the impact AI can have within the travel and hospitality sector, most recently speaking with Joan Roca, CEO of private membership travel service Essentialist.
“[W]hat AI can do with matching is incredible, with personalized context is incredible,” he told PYMNTS. “… It is able to make connections that you would have missed, or I would have missed. It’s the best matching tool that we’ve seen by a factor of 10.”
But as enterprises across sectors like healthcare, banking and finance, and eCommerce look to leverage the powers of generative AI to streamline their legacy workflows, understanding the total cost of ownership for integrating an AI system into business-specific workflows is crucial.
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