What makes this development feel so distinct is the sheer integration of services. While Western consumers often rely on fragmented apps to manage health data, Asia’s “super-apps” consolidate functions into single ecosystems.

For example, WeChat alone hosts over two dozen mini-programmes focused on nutrition tracking and personalised meal planning, with some achieving user satisfaction ratings close to 3.9 out of 5. Users can track meals, receive AI-generated dietary recommendations and consult dietitians without leaving their main messaging platform. Start-ups are taking notice.

The South Korean app Monolabs launched a nutrition service on WeChat, reportedly choosing China as its first overseas market in a clear recognition of the Chinese platform’s reach and infrastructure.

These ecosystems are not merely aggregating services; they are enabling the rise of personalised nutrition intelligence. When a user places an order through Grab or Gojek, AI can be leveraged to tailor suggestions for individual dietary preferences.

The artificial intelligence (AI) revolution is carrying serious momentum right now, and it’s showing no signs of slowing. Data center hardware suppliers like Nvidia are experiencing more demand than they can possibly supply, as the latest AI models require significantly more computing power than their predecessors.

As AI software becomes smarter and more capable, companies like Upstart Holdings (UPST 0.22%) and DigitalOcean (DOCN -1.66%) are likely to experience accelerating growth. In fact, here’s why investors with a spare $1,000 (money they don’t need for immediate expenses) might want to split it equally between shares of Upstart and DigitalOcean, and hold on to them for the long term.

1. The case for Upstart

Banks have relied on Fair Isaac‘s FICO credit scoring system to measure the creditworthiness of potential borrowers for more than 30 years. However, it only takes into account a handful of factors, like a person’s existing debts and their repayment history, so Upstart believes it’s outdated.

The company developed an AI-powered algorithm that can analyze a whopping 2,500 data points on each potential borrower to get a better sense of their ability to repay a loan, and it can deliver instant, fully automated approvals 92% of the time. It would take days or even weeks to parse the same amount of data using traditional human-led assessment methods.

Upstart specializes in unsecured personal loans, automotive loans, and home equity lines of credit (HELOCs). The company doesn’t lend any money itself, but rather it originates loans on behalf of banks, credit unions, and car dealers. It originated 372,599 approvals across all segments during the second quarter of 2025 (ended June 30), which was up by a whopping 159% from the year-ago period. The loans had a dollar value of $2.8 billion, which was a three-year high.

The surge in Q2 originations resulted in $257 million in revenue, representing a year-over-year increase of 102%. It marked the fourth consecutive quarter in which revenue growth accelerated, and it places the company on track to deliver more than $1 billion in annual revenue for the very first time this year.

Simply put, Upstart’s business is on the road to recovery right now after a brutal couple of years between 2022 and 2024, marred by a two-decade high in interest rates that crushed demand for credit. Rates have started to come down, and Wall Street anticipates three cuts by the Federal Reserve before this year is over, which will help Upstart build on its recent momentum.

Upstart CEO Dave Girouard thinks AI will replace all human-led loan assessment methods over the next decade, leaving a $25 trillion pool of annual originations up for grabs for AI-powered algorithms. This could translate to $1 trillion in annual fee revenue, so Upstart has an enormous market opportunity ahead.

2. The case for DigitalOcean

The cloud computing industry is dominated by tech giants like Amazon, Microsoft, and Alphabet, but they typically fight over the largest customers because they have the deepest pockets. DigitalOcean, on the other hand, exclusively serves small and midsize businesses (SMBs). It offers cheap pricing, highly personalized service, and a user-friendly dashboard, which is ideal for enterprises with limited technical expertise.

DigitalOcean can help SMBs store data, host websites, deliver video streaming services, develop software, and more. But the company also has an expanding portfolio of services designed to help businesses deploy AI software. It operates data centers powered by graphics processing units from top suppliers like Nvidia, and it allows SMBs to start with just one chip and scale up as necessary, which is perfect for small AI workloads like customer service chatbots.

DigitalOcean also launched a new AI platform called Gradient this year. It’s a cloud-based workspace with all the tools an SMB needs to develop AI software, including ready-made large language models from leading providers like OpenAI, Meta Platforms, and Anthropic, which they can use to accelerate their progress. Gradient can also be used to create AI agents, which can be trained to assist with tasks like data analysis and even writing computer code.

According to management’s most recent guidance, DigitalOcean is on track to generate up to $890 million in revenue in 2025, which would be a record high. AI will be a critical part of the long-term growth story here — while the company’s total revenue grew by 14% year over year during the second quarter, its AI revenue soared by more than 100%.

Investors have an opportunity to scoop DigitalOcean stock up at a very attractive level right now. It’s trading at a price-to-sales (P/S) ratio of just 4.3, which is a near-50% discount to its average of 8.5 since going public in 2021, so this could be a great long-term entry point.

The big question right now: How will artificial intelligence (AI) impact jobs? Will workforce and consumption trends follow the trajectory of the seismic shifts that replaced flails with mechanized harvesters and dusty ledgers with QuickBooks? 

History and recent data provide some clues. 

Seismic labor market changes from “general-purpose technologies”—big inventions that impact entire economies—typically take decades or longer to fully emerge. In 1880, around the same time the Second Industrial Revolution began unleashing new inventions like the internal combustion engine, which mechanized farming and fueled an exodus to factory jobs, nearly three in four rural Americans worked on farms.

Today, farmers comprise less than 2% of the U.S. population. Thomas Edison invented the incandescent light bulb in 1879, yet three decades later, only one in seven American homes were wired for electricity.

“History teaches us that even if AI disrupts the labor market, its impact will unfold over many decades,” a National Bureau of Economic Research (NBER) paper said in January. 

But as AI technologies evolve at warp speed, there’s major angst over whether they will vaporize jobs and fuel mass unemployment.

More than half of adult Americans, or 149 million consumers, regularly engage with the most ubiquitous iteration, generative AI, for routine tasks at home and work and for entertainment, such as making grocery lists, summarizing emails or watching a video of AI-generated cats washing dishes at a restaurant, a recent PYMNTS Intelligence study found. The immersion is accompanied by angst: One in three gen AI users worry AI will replace jobs. Four in 10 Gen Zers fear the same.

Take a Beat

Much of the doom-and-gloom is coming straight from the horse’s mouth.

In May, Sam Altman, the CEO of ChatGPT maker OpenAI, told a Congressional hearing that AI could displace 70% of all jobs. That same month, the CEO of AI firm Anthropic, Dario Amodei, told Axios the technology could wipe out half of all entry-level white-collar jobs and create unemployment of 10-20% within the next one to five years. 

Not so fast, some economists say. While the NBER paper co-authors, who include former Treasury Secretary Lawrence Summers, argue that AI “could be a [general-purpose technology] on the scale of prior disruptive innovations,” they write it is “likely too early to assess its full impacts.”

As such, recent data suggests the worriers might want to take a beat.

New Jobs

Employment in advertising, promotions and marketing—all fields widely seen as having core tasks that can be replicated by gen AI—is projected to grow 6% by 2034, faster than the average for all occupations, according to Bureau of Labor Statistics data. 

A March BLS report that looked at professions susceptible to potential AI impacts by 2033 found only credit analysts, claims adjustors and insurance appraisers vulnerable. Everybody else, including software developers, financial advisors, engineers, lawyers, architects and business operations managers, would see more jobs.

Meanwhile, the early evidence suggests AI will help existing workers do their jobs better and create new lines of employment. Bain & Company says the market for AI-related products and services could approach $1 trillion by 2027. Workers are needed to design that software, sell products and manage client relationships over multiple industries, including payments and financial services.

In August, the Federal Reserve’s New York branch found a sharp uptick in AI use by companies in the New York and Northern New Jersey region, with 40% of services firms, including finance, healthcare, business services, hospitality and retail reporting they used AI in the past six months, up from 25% a year ago. At the same time, “layoffs have been almost nonexistent due to AI use,” Richard Deitz, an economic policy advisor at the branch, said about the survey.

What has changed is how those services firms hire. Roughly one in eight surveyed by the Fed said they had hired fewer workers overall in the past six months due to their AI use. Nearly one in four said that would continue over the next six months. But there’s an offset to those reductions. Some 11% of services firms said that when they did hire, they turned to employees with AI skills. By next February, 14% of service firms plan to hire more AI-adept workers. 

Workers in math, computer, office and administrative functions, and business and finance—jobs with more AI exposure—had larger unemployment rate increases between 2022 and 2025, the St. Louis branch of the Fed found last month. But the finding is one of correlation, not causation, the branch emphasized, adding that other factors could explain rising unemployment in AI-exposed occupations, including economic uncertainty, post-pandemic monetary policy tightening and coincidence.

The Federal Reserve Bank of Atlanta found in May that job listings mentioning AI skills were rising quickly for computer and math occupations regardless of the required level of education for the positions—suggesting the upskilling creates more opportunity. At the same time, they’re growing faster for workers with at least a bachelor’s degree, suggesting that such people may have additional, non-AI-related skills that are relevant to their AI knowledge.

Some Jobs May Go Away; Labor Won’t

In other words, AI hasn’t supplanted other important skills or taken over the show.

A recent PYMNTS Intelligence report revealed how large U.S. companies are increasingly dipping their toes into agentic AI, which has the capacity to autonomously takes actions and makes decisions independent of human oversight, like paying a vendor. But the companies are keeping a tight leash on the software, with human hands on the processes the software handles.

Americans have freaked out before about the impact of technology on jobs. In 1982, Soviet-American economist Wassily Leontief, a Nobel Prize winner, theorized in a Scientific American essay that industrial robotics, automation and computing could mirror the effect of the automobile on the horse. 

Two decades earlier, government economists had concluded the opposite. A government report on President Lyndon Johnson’s National Commission on Technology, Automation, and Economic Progress concluded that “technology eliminates jobs, not work.”

The NBER paper authors agree: “At least in the near term, AI is more likely to ratchet up firms’ expectations of knowledge workers than it is to replace them.”