Tech Brew keeps business leaders up-to-date on the latest innovations, automation advances, policy shifts, and more, so they can make informed decisions about tech.

Tech Brew

Quarter Century Project

Jordyn Grzelewski

Tricia Crimmins

Patrick Kulp

techbrew.com

You’re tired of reading about tariffs. Honestly, we’re tired of writing about them. But amid the ever-shifting landscape of 

, and Truth Social missives, where do things stand 

, the Tech Brew team homed in on the ABCs of tech industries—automobiles, batteries, and chips—to illustrate how tariffs are impacting those sectors, the US economy, and your wallet.

? According to Art Wheaton, director of labor studies at Cornell University’s ILR School, the situation is “still as messy now as we were when we began.”

“There’s not a lot of clarity,” he told us late last month. “There is no final deal for Mexico. No final deal for Canada. There’s no final deal for China. So everything is still in flux for three of the biggest trading partners we have.”

In April, the Trump administration implemented tariffs of 25% on imported vehicles. Since then, the US has announced trade deals to lower auto tariff rates for several trading partners, including the UK, Japan, South Korea, and the EU.

“It’s really created a lot of confusion—which, if you ask the current administration, they like,” Wheaton said. “They like keeping everybody on their toes, but the auto industry hates uncertainty.”

In an August update on the auto tariffs landscape, Cox Automotive reported that “automakers have theoretically racked up more than $25 billion in tariff obligations so far,” based on “the average imported vehicle being charged roughly $5,200 at the US border.”

Overall, automakers and dealers appear to be absorbing at least some tariff-related costs rather than passing them on to consumers in full, according to Cox.

“But that won’t last,” Erin Keating, executive analyst at Cox, 

. Cox analysts forecast a 4%–8% YoY increase in retail prices by the end of the year.

Meanwhile, auto manufacturers are feeling the effects on their bottom lines, with companies like General Motors, Ford, and Hyundai reporting tariff-related hits to profitability in Q2. The biggest US automakers reported that tariffs hurt their collective profitability to the tune of $11.7 billion in the second quarter, Yahoo Finance 

“The auto industry is clearly under pressure,” Keating wrote. “Tariffs are increasing costs across the board for automakers, dealers, and consumers—not only for new vehicles, but for aftermarket parts and insurance costs.”

Cox analysts expect the average transaction price of a new vehicle in the US to surpass $50,000 this year, and for new-vehicle sales to be lower than in 2024.

And affordability is already a challenge in the auto industry: Yahoo Finance cited Atlanta Fed data indicating that car prices are growing six to eight times faster than household incomes.

Experts have noted that some other recent federal policy changes, like the rollback of vehicle fuel efficiency standards, could be tailwinds for domestic automakers.

“GM, Ford, Stellantis, and others can now make as many pickup trucks and large SUVs as they want,” Wheaton said. “So they’re able to absorb some of those tariffs because they think their profits are going to do better with a different vehicle mix, much worse [mileage] per gallon but higher profit margin.”

In the last few months, it’s felt like tariff uncertainty has taken a backseat to 

 in the green tech industry. But for battery manufacturers—which were able to 

 their 45Y and 48E tax credits—the tariff war has hit hard, forcing them to make tough decisions about where they source their battery cells.

Rithy Chhean, VP of technology at BoxPower, told Tech Brew that “when the price war escalated, [tariffs] became all-consuming” for the company, which produces batteries in addition to solar powered microgrids. While portions of BoxPower’s hardware is domestically produced, the company—like many other battery manufacturers—uses battery cells from China.

“Over the course of three months, it went to almost a 150% tariff,” Chhean said. “We didn’t have special terms in our contracts to say, ‘Here’s the tariff costs, and if the tariffs increase, you have to pay it.’ Some customers were able to deal with it. Some customers, you’re not able to do anything. Someone has to pay that difference.”

BoxPower’s forthcoming LFP battery, the ABX‑110‑BABA, fulfills Build America, Buy America (BABA) requirements, meaning at least 65% of the battery's materials were produced in the US. Even so, Chhean said BoxPower wasn’t able to find any cost-competitive domestic battery cells to use in the product.

“It’s cheaper to get cells from basically another country and pay the tariff costs,” he told us. “Even the companies that say they’re highly domestic, we find out that their cells or modules are also coming from China anyway, or somewhere like China.”

Though the Trump administration claims the goal is to increase “advanced domestic manufacturing capacity” through tariffs, doing so will take time in the battery industry. Critical mineral developers are working together to 

, and battery makers have plans to bring manufacturing plants to the US in the future, but right now companies like BoxPower are in a bind.

At the moment, Chhean said BoxPower uses a “hybrid approach.” The company still buys battery cells from China, but when possible, it buys from companies in other countries that have lower tariffs—even though the cost of the item might be higher. Above all, BoxPower says it’s working to be transparent about tariffs with customers.

“We’re trying to show what the tariff costs are,” Chhean said. “If the tariffs do increase, we will provide a very small markup, if any markup, on it because it’s not really fair to the customer, and we understand that.”

There’s plenty of uncertainty and confusion to go around, too, when it comes to Trump’s moves on 

, which power everything from consumer electronics to advanced AI chips.

 100% tariffs on semiconductors, a possibility his administration has been probing since April. But the announcement also contained a key exemption: Companies that have committed to investing in manufacturing in the US or are already doing so are not subject to the tariffs. The Trump administration has already 

 Apple as one of these companies. Some of the biggest players in the AI infrastructure boom—Nvidia, TSM—–may 

 about the details of these tariffs, which have yet to be formally rolled out. The Semiconductor Industry Association said last month that “we are eager to learn more.”

In such an uncertain environment, Lydia Clougherty Jones, a senior director analyst with Gartner, said companies will likely need to consider multi-country sourcing strategies and stay nimble with scenario planning and analytics.

“It is critical to align technology procurement decisions with the highest-priority disruption-proofing needs, including enabling executive teams to use real-time situational analysis to prepare for future short-term and long-term trade war disruptions,” Clougherty Jones said in an email.

 in running the chipmaking industry itself, most notably by having the US government 

 in Intel. Trump is also directly negotiating fees with Nvidia and AMD to continue selling chips in China, in what legal critics say 

Clougherty Jones said the US government’s more active role in setting industrial policy for the chip sector could ultimately speed AI development—a goal for both the government and the companies involved—but they may also end up at odds over differing motivations.

“Such public-private partnerships prioritize speed, resulting in the acceleration of AI R&D and infrastructure build out, including of data centers, without regulatory guardrails, as governments can selectively remove barriers to AI progress or deprioritize their enforcement,” she said.

“On the other hand, there can be a clash of priorities, as private companies are driven by profit motives and the goal of delivering maximum returns to their shareholders, whereas governments may prioritize advancement of sovereign-specific goals such as national security and strategic AI autonomy, leading to dissimilar drivers and measurements of what successful AI advancement looks like,” she said.

A truck passes by China Shipping containers at the Port of Los Angeles, California, on September 1, 2019.

How is tariff uncertainty impacting tech?

We focused on the automotive, battery, and chip industries to tell the tale.

How is tariff uncertainty impacting tech? 

In September 2015, world leaders gathered at the UN headquarters in New York City to commit to a new agenda—one that “recognizes that ending poverty must go hand-in-hand with a plan that builds economic growth and addresses a range of social needs, while tackling climate change.”

 (SDGs), which addressed “core drivers of climate change,” and included clean water and sanitation, green energy, infrastructure and industry, sustainable consumption and production, climate action, managing oceans and forests, and combating desertification and biodiversity loss.

The following January, the efforts to achieve the goals went into effect. In the ensuing years, tech companies made commitments in support of the goals, especially those pertaining to sustainability. While the goals—and any commitments adjacent to them—weren’t legally binding, many companies used them as a “compass to guide organizations” and report progress toward initiatives for the greater good, Steven Cohen, director of the Sustainability Management program at Columbia University, told Tech Brew.

“The SDGs are a broad, general set of aspirational goals for organizations and nations, and they need to be thought of that way,” Cohen said. “But they influence how companies think about what they should be trying to do.”

And as consumer expectations around sustainability have risen, Cohen said, tech companies have started to use AI to work toward the goals.

“You need people helped by these machines to help them deliver those services,” Cohen said. AI is a “tool which then frees humans to do other things that they otherwise couldn’t do.”

Via a review of Google and Microsoft’s sustainability reports, Tech Brew found that a handful of Big Tech companies have leaned on AI to further their progress toward the SDGs, which the UN

 last year in a resolution promoting the use of “safe, secure and trustworthy” AI.

“AI will be created and deployed through the lens of humanity and dignity, safety and security, human rights and fundamental freedoms,” Linda Thomas-Greenfield, then the US UN ambassador, said of the resolution when it was passed. “Let us commit to closing the digital gap within and between nations and using this technology to advance shared priorities around sustainable development.”

Two years before the UN resolution, Google committed to using AI toward SDG progress in the wake of the pandemic and the enormity of the climate crisis.

“Fewer people have the opportunity to move out of poverty, inequitable access to healthcare and education continues, gender inequality persists, and environmental threats pose immediate and long-term risks,” Google SVP of Technology and Society James Manyika said in a 2022 

. “We know that AI and other advanced technology can help tackle these setbacks.”

Google also made a $25 million commitment to “support NGOs and social enterprises working with AI to accelerate progress toward these goals.” Google’s Startups for Sustainable Development program worked with startups to incorporate machine learning and AI models into their work in 2024. Examples include “identifying and monitoring tree species to support reforestation efforts, predicting utilization rates for electric vehicle chargers, and monitoring marine life” using AI.

“We have a once-in-a-generation opportunity to unlock human potential, for everyone, everywhere,” Google CEO Sundar Pichai said of AI in a speech last year to the UN General Assembly. “The opportunities are too great, the challenges too urgent, and this technology too transformational to do anything less.”

Google did not respond to Tech Brew’s request for comment.

Earlier this year, Microsoft CSO Melanie Nakagawa announced that the tech company would also start using AI to support the SDGs.

“In 2020, Microsoft leaders referred to our sustainability goals as a ‘moonshot,’ and nearly five years later, we have had to acknowledge that the moon has gotten further away,” Nakagawa said in a 

. “However, the force creating this distance from our goals in the short term is the same one that will help us build a bigger, faster, and more powerful rocket to reach them in the long term: artificial intelligence.”

And Microsoft’s 2024 Global Governance report struck a similar chord. In it, the company said AI “could help put us on the right course where we’ve fallen behind on the [SDGs] and otherwise accelerate our progress.” Recent updates from Microsoft state that it hopes to use AI to cut back on waste, conserve water, optimize energy efficiency, and improve “eco-friendly” transportation.

Microsoft declined to comment on how it’s using AI to meet the SDGs, but sent a 

 detailing how it’s using the tech to support sustainability initiatives including the UN goals. It cited an AI tool aimed at reducing methane emissions—Microsoft Sustainability Manager—which helps “food banks that recover and redistribute surplus food demonstrate the impact of their actions to reduce methane emissions.”

“Already, we are seeing AI make a positive impact on the planet,” Nakagawa said in her announcement. “In the coming years, this technology will begin to rapidly accelerate climate solutions at a scale we’ve not yet seen.”

A decade after the UN set climate goals, tech companies are using AI to achieve them

Google, Microsoft, and the UN itself have said using AI can accelerate sustainability.

From a small research lab “free from financial obligations” to one of the most valuable private businesses in the world, the company that ushered in the generative AI era has evolved a lot over its decade of existence.

Now, OpenAI is on the verge of more change. Its longtime strategic partnership with Microsoft 

. The company’s long drift into for-profit-dom is 

. And as the company still at the center of the generative AI boom, OpenAI’s structural pivots and alliance shifts have implications for the rest of the industry.

“This is going to be a very, very interesting next 12 to 18 months because of all these dynamics,” Ritu Jyoti, group VP at market intelligence firm IDC, told Tech Brew.

 Having gathered top research minds in the AI space from day one, OpenAI has always encompassed a series of competing and evolving visions for what the next generation of AI should look like.

That was one of the takeaways Tyler Johnston, executive director of the nonprofit Midas Project, arrived at as he spent the past several months sifting through more than 200 news articles, legal filings, employee testimonials, and other information about OpenAI’s history. The group recently published the result of this work as a research report called the 

 in partnership with advocacy group Tech Oversight Project.

“OpenAI is a company that has existed on this insanely accelerated lifespan,” Johnston told us. “It’s just astonishing how much has happened in the 10 years that it’s existed, and how many different visions of the organization have, at various times, flourished or been squashed based on how convenient they were to the leadership at the time.”

Backed by big-name investors and co-founded by Sam Altman and Elon Musk, among others, OpenAI immediately made a splash upon its launch in 2015 as a nonprofit. The lab had already assembled a laundry list of top researchers, with the not-for-profit purpose as part of the recruiting pitch, according to a 

“We just talked about every specific structure and thought this one had the most advantages,” Altman told 

 of the nonprofit mission. “I think that the misaligned incentives [of profit-seeking] would be suboptimal to the world as a whole.”

 OpenAI once again grabbed headlines in 2019 when it declared it would not release the full second iteration of its generative pre-trained transformer model (GPT-2) due to “concerns about malicious applications of the technology.” The model was capable of producing “synthetic text samples of unprecedented quality.”

A month later, OpenAI converted to a capped profit structure, where returns beyond 100 times an investment would be passed to the nonprofit board. A few months after that, Microsoft invested $1 billion to kick off a “multiyear partnership.”

“This was brilliant, by Microsoft, by [CEO] Satya [Nadella],” Vasant Dhar, a data science professor at NYU’s Stern School of Business and author of a 

 on the history of AI, told Tech Brew. “He just saw this thing coming, you know, from much further away than most people did, and he clinched a really solid deal.”

 But as OpenAI perhaps continues down its path toward full for-profit status—despite some pushback and potential setbacks—experts we talked with say Microsoft and OpenAI were destined to drift apart eventually. The companies have reportedly clashed over their revenue-sharing agreement and OpenAI’s proposed acquisition of coding platform Windsurf. (The deal ultimately fell through when 

 with a shock acquihire of top Windsurf employees.) OpenAI has signed competing cloud agreements, and Microsoft has rolled out competing models.

Microsoft and OpenAI said in a joint statement emailed to Tech Brew that they “have a long-term, productive partnership” and are “optimistic we will continue to build together for years to come,” a statement also provided to 

, Microsoft reiterated that its partnership would continue with OpenAI through 2030, while also softening its cloud exclusivity terms.

Part of the tension, too, hinges on language around the original agreement, which ends when OpenAI achieves what its board determines to be 

, which it defines as “a highly autonomous system that outperforms humans at most economically valuable work.” But AGI does not have a single agreed-upon definition, and that’s 

“That is fundamentally a very, very slippery thing to base your benchmark on, especially as over the past 50 years, we’ve kind of continuously redefined what AGI looks like in practice,” Rowan Curran, principal analyst with Forrester Research, told us.

While the pressure campaign to keep OpenAI a nonprofit appeared to 

 earlier this year, Johnston argued that the framing of the story was misleading.

“In my mind, OpenAI is very conveniently describing control in such a way that they retain a lot of the freedom that they wanted…while still acting as if they had made a concession,” Johnston said.

But an eventual Microsoft-OpenAI split could also be a boon for the overall ecosystem and the companies that are using this technology as it spurs new competition, Jyoti said.

“It would diversify the AI providers—it will not be just centered around Microsoft and OpenAI. It will create some new alliances,” Jyoti said. “It will give developers and enterprises more choice, but it can also [add] more complexity.”

OpenAI Co-Founder & CEO Sam Altman speaks onstage during TechCrunch Disrupt at Moscone Convention Center in San Francisco, 2019. 

Nearing its 10th anniversary, OpenAI is at a crossroads

The company is drifting from its longtime backer and toward for-profit status—but not without resistance.

A decade ago, before all-electric vehicles were routinely spotted on roads, drivers of Volkswagen’s diesel offerings thought they were making an environmentally conscious choice. The company had touted a “best of both worlds” approach: It said its diesel vehicles produced lower emissions than competitors, but still gave customers more energy per gallon compared to gasoline.

“It was this amazing promise in vehicle technology,” Christopher Hennigan, a University of Maryland professor of environmental engineering, told Tech Brew. “But it turned out to be a lie.”

That lie involved Volkswagen putting what the Environmental Protection Agency called “defeat devices” in model year 2009–2016 cars to deceive federal emissions tests: When the cars were being tested, emissions were low. But on the road, they emitted a “major excess” of NOx, or gas particles that can lead to illness and premature death

 when then-International Council on Clean Transportation Senior Fellow John German and his team tested Volkswagen diesel vehicles on the road—not in a test facility. Using a machine in the car’s trunk and a probe down the length of the exhaust pipe, they uncovered extremely high emissions.

As a result, the EPA and Department of Justice found that Volkswagen, which included the Audi and Porsche brands, violated the Clean Air Act, a federal law passed in 1970 to regulate emissions from stationary sources, like factories, and mobile sources, like cars. Under the law, the company agreed to pay multiple settlements and pleaded guilty to criminal charges.

“The Clean Air Act worked as it was intended to—in the sense that we had a company that was violating it and when that was discovered, [there were] massive penalties in response,” Amanda Halter, a partner in Pillsbury Winthrop Shaw Pittman’s Environmental & Natural Resources practice, told us. “It’s the kind of law, frankly, that you just couldn’t get passed by today’s Congress.”

As part of the settlement, Volkswagen spent $2 billion to establish a public fast-charging network, Electrify America, which today is the second largest in the US. It now has more than 4,800 charging ports across the country, second only to 

“The contribution that Electrify America has made to the public charging infrastructure is really substantial,” Brent Gruber, executive director of JD Power’s EV practice, told Tech Brew.

However, the network has been criticized by EV drivers and electrification advocates over reliability issues, as detailed in a 

 by The Washington Post. An executive told the outlet that the network was “working hard to improve reliability.”

 on consumer satisfaction with public fast chargers in a 2024 JD Power study. It scored 559 on a 1,000-point scale, while Tesla ranked highest, with 731.

In general, there are two major problems with US public charging, Gruber said: lack of availability and 

The EV “adoption rate is outstripping the pace of charger installation by about two to one,” he said. And about one in five public charging visits fail, per JD Power and 

, because of issues like faulty chargers and long wait times.

Solving these issues is important because public-charging concerns remain the No. 1 barrier to EV adoption, Gruber said. But now, that effort must proceed without federal help, as the Trump administration 

Gruber said he expects to see a near-term slowdown in charger installation, but that states and private-sector players will push ahead, because strong public charging is key to an electric future in which manufacturers are heavily invested.

. It reported that its customers’ 16 million charging sessions represented 50% growth in 2024, and it plans a 30% expansion this year. Electrify America declined to comment on Tech Brew’s questions.

The network is working to increase the number of “Hyper-Fast” 350 kilowatt-hour chargers, per a company report, as well as opening larger stations. It says it’s implemented policies, like idle fees, aimed at reducing wait times.

“Increasing customer satisfaction and station performance is a top priority for Electrify America,” the network said in its Q1 2025 report to the California Air Resources Board. The network will report to the board annually on charger station uptime and “strive to achieve target uptime thresholds on its California network of chargers,” under the terms of its latest maintenance plan.

Meanwhile, Gruber said he was heartened to see significant progress in Q1 on customer satisfaction and charger reliability.

The public charging failure rate dropped to 16% in Q1, the largest improvement since JD Power launched the survey in 2021, according to Gruber. And the satisfaction level with public fast chargers went up by six points from Q4 2024, to 656 out of 1,000.

The results, Gruber said, “gave me a lot of hope that we’re starting to see the tides turn with public charging.”


Volkswagen Passats are offered for sale at a dealership on September 18, 2015, in Chicago, Illinois. The Environmental Protection Agency (EPA) has accused Volkswagen of installing software on nearly 500,000 diesel cars in the U.S. to evade federal emission regulations. 

Dieselgate spawned a large US EV charging network. Why is public charging still so vexing?

Volkswagen agreed to spend $2 billion to build out a network of EV chargers as part of a settlement in the wake of an emissions scandal. A decade later, drivers frequently cite charger unavailability as a roadblock to EV adoption. 

Edwin Olson can still hear the faint sound of the autonomous vehicle he helped build as part of MIT’s team for the DARPA Urban Challenge in 2007 as it returned from the hourslong competition.

“It was the most amazing feeling,” he told Tech Brew.

Nearly 20 years later, Olson is the CEO of an AV company of his own, 

, and the industry is in a much different position than it was in the early days of self-driving vehicle technology.

Plenty of would-be contenders have come and gone. Leaders have emerged. Lots of modern vehicles now come equipped with some automated features, and fully self-driving vehicles are operating on a limited basis—progress is being made. But hype around people being ferried to and fro in AVs on a mass scale has collided with technical, regulatory, and scalability challenges. Yet industry stakeholders are still working toward a future where many more of our transportation needs are met by driverless vehicles—and someday by steering wheel- and pedal-free ones.

“The public sentiment was significantly ahead of the technical reality…And then what basically happened is, the technical reality got ahead of public sentiment. And I think that’s where we are right now,” Olson said. “It can’t do everything. But it works pretty damn well, and it can solve real problems.”

Research into self-driving vehicles dates back decades, but many point to the DARPA challenges as seminal events that helped kickstart the modern AV sector.

In the early 2000s, the US Defense Advanced Research Projects Agency (DARPA) started testing AVs on a 150-mile off-road course, according to the University of Michigan. The DARPA Grand Challenge series pitted major universities like MIT, Stanford, and Carnegie Mellon against each other, starting with a competition in the desert in 2004 in which none of the AVs completed the course.

Olson was part of MIT’s team for the DARPA Urban Challenge in 2007, and recalled it as a “humbling” experience that involved creating what was essentially a rudimentary joystick to control the vehicle.

“The hardware was terrible…The vehicle control was very imprecise,” Olson said. “Everything was dodgy. The ride quality was bad. The autonomy was really bad. But we got there.”

The challenges are widely credited with establishing the foundation of the AV sector as we know it today, including contributing to the start in 2009 of Google’s self-driving vehicle project—what is today Waymo, the robotaxi sector’s leader.

“Since then, we’ve gone up and down in hype and disappointment and adjusting expectations and whatnot,” Jeremy Carlson, associate director for autonomy at S&P Global Mobility, told Tech Brew, “because it turns out that it’s a pretty challenging task, what we’re trying to do in building autonomous vehicles to replicate and improve upon human driving.”

While the DARPA challenges generated lots of momentum around AV tech, it became clear soon enough that there were massive technical hurdles to overcome, according to experts and stakeholders. One of them, Carlson noted, is that it’s nearly impossible to teach AV systems the infinite number of complex driving scenarios they could encounter in the real world.

“We don’t have a system today that’s going to address every single possible corner case in the world,” Carlson said. “Whether or not we need to build that in the first place is an argument that most developers will say, ‘Hey, it’s impossible to actually cover every corner case.’ To do that kind of rules-based approach, which is where a lot of the software and programming side of this started, it’s just kind of unrealistic.”

Then there are the realities of the automotive business, which is capital-intensive and slower-moving than the tech industry’s hype cycles, Carlson said. And AV tech in and of itself is incredibly costly—not just in terms of hardware like cameras, sensors, and radar, but in terms of establishing operating bases and maintaining large vehicle fleets.

These challenges are one reason why we’ve seen much of the traditional auto industry put its resources into 

, or ADAS, which partially automate the driving experience (for example, allowing drivers to take their hands off the wheel on the highway or automatically change lanes) but still require human involvement.

In one of the starkest examples of this shift, GM last year 

 it was pulling the plug on its robotaxi business, Cruise, and focusing, at least for now, on ADAS. The company attributed the decision to “the considerable time and resources that would be needed to scale the business, along with an increasingly competitive robotaxi market.”

 that rules-based, software approach to what we might describe as an end-to-end architecture, something that’s a little bit more flexible in identifying the situation, understanding what it’s supposed to do…that will cover a lot more of those corner cases,” Carlson added. “It will make those systems a lot more adaptable, very much like a human brain would be.”

Though the highest levels of vehicle automation operating on a wide scale may still be many years away, in the next several years, experts expect to see expansions in ADAS features and the more sophisticated automation we’re already seeing today for use cases like ride-hailing and trucking. Think of packages being delivered via autonomous vans, 

 no longer featuring human drivers behind the wheel.

“You’ve got Waymo out showing everybody this can happen,” Olson said. “And I think this is really important, too, because the way that we build our cities today…this personal car ownership thing, it’s a disaster.”

He and other industry stakeholders describe a future in which multi-car households go down to one car, and eventually, just maybe, to zero—perhaps eventually spurring complementary zoning and development changes to meet the needs of a society less dependent on personal vehicles.

Johann Jungwirth, EVP of autonomous vehicles for 

, touted potential benefits like restoring lots of free time to people no longer beholden to their daily commutes, increased productivity at work, more choices around where people live if transportation is less of a concern, better transit accessibility for people with disabilities, and huge safety improvements. These boons, he believes, will be delivered both by autonomous personal vehicles and fleets.

“I think we are just at the beginning of this,” Jungwirth said. “There is so much more to come, once vehicles can be designed without steering wheels or pedals.”

In the next five years, Carlson expects to see AVs become more integrated into many people’s everyday lives—largely in the areas where the tech is available today, like 

“Those vehicles are very much a part of people’s lives today. It’s obviously in limited areas,” Carlson said. “But that is beginning to expand quite quickly.”

He also expects to see gradual advancement into small- and medium-sized cities in the coming years, and that technology advancements will “also make it possible to put it into locations where we might have inclement weather or other obstacles that we don’t see them being deployed in today.”

May Mobility, which has partnerships with 

, is working toward a future of transportation in which autonomy, paired with public transit, outcompetes the experience of owning a car.

“I think we’re very, very close to that,” Olson said. “When people ride in an autonomous vehicle…it’s like getting somewhere in a way that doesn’t suck.”

A member of the SciAutononics II team gives a thumbs-up gesture from the chase vehicle as they follow their autonomous vehicle from the starting line in a quest for a million-dollar prize at the DARPA (Defense Advanced Research Projects Agency) Challenge on March 13, 2004 near Barstow, California. 

Our self-driving future has yet to materialize. What’s next for AV tech?

Autonomous vehicles have yet to live up to the hype around them, but industry stakeholders still see them as a way to transform transportation as we know it.

Slack, Gmail, Monday.com, Google Meet, Zoom, Microsoft Teams, Google Docs—this is a (surely incomplete) list of apps and platforms used over the course of reporting and writing this story.

It may ring familiar to many digital workers who have grown accustomed to constantly toggling among the seemingly infinite number of workplace productivity tools that have come to populate our professional lives.

One of the most influential of these tools, Gmail, 

 on April 1, 2004, and is credited with forever changing the ways we use email—and influencing the trajectory of the internet and workplace tech.

At the time, the service’s offering of 1,000 megabytes of storage seemed so improbable that many assumed it was an April Fool’s joke.

“Google’s rivals have copied Gmail so thoroughly that it’s hard to remember just how terrible webmail was before Gmail came along,” Slate recounted in a 

 marking Gmail’s 10th birthday. “Pages were clunky and slow to load, search functions were terrible, and spam was rampant. You couldn’t organize messages by conversation. Storage capacity was anemic, and if you ran out of space, you had to spend hours deleting old emails or buy more storage from your provider. Gmail…taught us that Web apps could run as smoothly as desktop applications. And it taught us the power of cloud storage.”

Aamer Baig, a senior partner at McKinsey, recalled how in the early days of email, communications were limited within a company. Now, the entire world is theoretically connected.

“Now it is literally a countless number of channels,” Baig told Tech Brew. “You have Slack, you have text, you have email, then you have collaboration spaces in documents and workflow, in applications. On top of that you’re also getting AI that is getting embedded into all these tools.”

All of this innovation has made us more connected than ever—and yet!—somehow still exhausted and struggling to optimize our work lives. So how can we work smarter and not harder?

 is the phenomenon of becoming overwhelmed and exhausted from toggling between various apps and platforms. Research has demonstrated that switching between different contexts or tasks doesn’t just make workers feel burned out—it actually reduces productivity.

In response to a 2023 survey by project management software provider Wrike, 58% of knowledge workers said they’d like to use fewer apps at work: “They are crying out for clear, streamlined, and consolidated processes.”

The report also pointed out that the proliferation of apps and platforms makes it more difficult for business leaders to have visibility into what employees are doing, which “leads to wasted efforts, delayed or canceled projects, and employee burnout.”

 found that each employee working on “a single supply-chain transaction” at a Fortune 500 consumer goods company toggled 350 times between 22 apps and websites. In the course of one day, every person toggled more than 3,600 times.

The study found that this act of “context switching” causes workers to lose up to five working weeks per year, or nearly a tenth of their time on the clock––what the authors dubbed the “toggling tax.”

And it appears that workers are struggling to effectively use all of these tools. Nearly half of digital workers reported “that at least half the time they look for information they couldn’t find it,” in 2022, according to Gartner. In 2024, only 31% reported having that issue, but those who used AI were more likely to struggle. And solutions like intranets and new employee communications platforms haven’t solved the problem.

Tori Paulman, a VP analyst at Gartner, told Tech Brew that in the last two years, digital workers’ reported satisfaction with the apps they use for work has plummeted.

Amid all this exhaustion, frustration, and dissatisfaction, workers are devising their own solutions and turning to their personal favorite apps to meet their professional needs.

“This causes a huge problem,” Paulman said. “This is one of the things that’s fueling the ROI crisis with AI, is that information is fragmented across hundreds of apps.”

To that end, Paulman pointed to personalization as the solution that employees are clamoring for.

Gartner’s 2024 Digital Worker Survey, for example, found that 51% of digital workers “customize or build tools leveraging the digital technology their organization provides,” or get their own.

“Getting people to use the thing you give them, rather than the thing they like, it’s the perennial issue,” Paulman said.

Instead of trying to get employees to buy into a consolidated platform or yet another new tool, Paulman said it’s best to first determine how employees are using their existing tools. It may be that rather than a new tech solution, what’s needed is clearer communication at the front end of a new project about which tools will be used and how.

“The leaders need to bring some sanity to how and when we use these technologies, in order to calm that cognitive fatigue,” Paulman said.

McKinsey’s Baig, too, offered a low-tech solution: creating individual and company-level rubrics to guide how employees use workplace productivity tools.

Time sensitivity, for example, is a rubric he uses in his own work. Employers might encourage workers to use Slack and text for urgent matters and emails for non-time-sensitive ones. And workers might block off chunks of time to work without constant interruptions from notifications, with incoming communications limited to higher-ups who need a quick response.

“I’m exceptionally excited about the tools we have at our disposal,” Baig said. “But I don’t think all of them should be used all the time.”

He believes we’ll continue to find ways to integrate technology into our lives and careers in beneficial ways, but to make the most out of what technology has to offer, he suggests less multi-tasking.

“Sometimes the most productive and the most effective we are is when we are mono-tasking,” he said.

Of course, one of the much-touted solutions to the problems surrounding workplace productivity is AI.

Google, for one, is integrating AI into Gmail and its Google Workspace suite of apps.

“Our goal is to provide powerful, genuinely useful technology that clears people’s path to productivity instead of complicating it,” Gmail said in a statement. The email service now has AI-enabled capabilities like summaries of email threads, a Smart Reply feature, and a Q&A tool that enables users to ask questions about their inbox.

“With Gmail connected to the broader Google Workspace suite of apps, and with AI assistance woven in seamlessly,” according to Gmail, “all of our tools work together so people can stay in their flow of work without app or context switching.”

Both Paulman and Baig said they’re hearing more and more about workers using AI to manage emails, generate content, and summarize information—raising the possibility that we might someday be much less attached to our inboxes.

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