Fluctuating gas prices have many feeling pain at the pump—but owners of gas-guzzling cars feel it more acutely.

Stacker used data from the Department of Energy’s fuel economy database to rank the 23 most gas-guzzling cars of 2023. Duplicate models of the same car line were excluded from this analysis: For example, the data includes information on the Rolls-Royce Ghost, Ghost Black Badge, and Ghost Extended, but this analysis only includes information for the base model, Ghost. Only 2023 model cars were considered, and those included here were released between May 2022 and February 2023.

Gas prices rise due to higher demand and higher costs for crude oil and they typically vary by season. In June 2022, the average price for a gallon of gas was over $5 in many states but fell as demand and crude oil prices sank.

New fuel efficiency standards may help your wallet when gas prices rise. In 2022, the National Highway Traffic Safety Administration released new standards that require manufacturers to have a fuel efficiency rating of 49 miles per gallon averaged across all of their models by 2026 and for every model by 2029.

Owning a gas guzzler won’t just cost you more at the pump—cars that get less than 22.5 miles per gallon also incur a “gas-guzzler tax,” which starts at $1,000 but climbs to $7,700 for cars that get less than 12.5 mpg. The tax is usually paid by the manufacturer or importer but is no doubt passed on to the customer in the purchase price.

Read on to see which new cars are the least fuel-efficient for 2023.

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Martyn Lucy // Getty Images

Aston Martin Lagonda Ltd V12 Vantage

– Combined fuel economy: 16 miles per gallon
– Highway fuel economy: 22 mpg
– City fuel economy: 14 mpg
– Manufacturer: Aston Martin
– Engine size: 5.2 liters
– Cylinders: 12
– Transmission: Automatic (A8)

Sjoerd van der Wal // Getty Images

Mercedes-Benz AMG SL 63 4MATIC+

– Combined fuel economy: 16 miles per gallon
– Highway fuel economy: 22 mpg
– City fuel economy: 14 mpg
– Manufacturer: Mercedes-Benz
– Engine size: 4 liters
– Cylinders: 8
– Transmission: Automatic (A9)

Martyn Lucy // Getty Images

Audi R8 Coupe quattro

– Combined fuel economy: 15 miles per gallon
– Highway fuel economy: 18 mpg
– City fuel economy: 13 mpg
– Manufacturer: Volkswagen
– Engine size: 5.2 liters
– Cylinders: 10
– Transmission: Automated Manual – Selectable (e.g., Automated Manual with paddles) (AM-S7)

Sue Thatcher // Shutterstock

Audi R8 Spyder quattro

– Combined fuel economy: 15 miles per gallon
– Highway fuel economy: 18 mpg
– City fuel economy: 13 mpg
– Manufacturer: Volkswagen
– Engine size: 5.2 liters
– Cylinders: 10
– Transmission: Automated Manual – Selectable (e.g., Automated Manual with paddles) (AM-S7)

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Lamborghini Huracan Coupe

– Combined fuel economy: 15 miles per gallon
– Highway fuel economy: 18 mpg
– City fuel economy: 13 mpg
– Manufacturer: Volkswagen
– Engine size: 5.2 liters
– Cylinders: 10
– Transmission: Automated Manual – Selectable (e.g., Automated Manual with paddles) (AM-S7)

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Lamborghini Huracan Spyder

– Combined fuel economy: 15 miles per gallon
– Highway fuel economy: 18 mpg
– City fuel economy: 13 mpg
– Manufacturer: Volkswagen
– Engine size: 5.2 liters
– Cylinders: 10
– Transmission: Automated Manual – Selectable (e.g., Automated Manual with paddles) (AM-S7)

GabrielPreda.ro // Shutterstock

Bentley Flying Spur

– Combined fuel economy: 15 miles per gallon
– Highway fuel economy: 19 mpg
– City fuel economy: 12 mpg
– Manufacturer: Volkswagen
– Engine size: 6 liters
– Cylinders: 12
– Transmission: Automated Manual – Selectable (e.g., Automated Manual with paddles) (AM-S8)

FABRICE COFFRINI // Getty Images

Bentley Continental GT Speed

– Combined fuel economy: 15 miles per gallon
– Highway fuel economy: 20 mpg
– City fuel economy: 12 mpg
– Manufacturer: Volkswagen
– Engine size: 6 liters
– Cylinders: 12
– Transmission: Automated Manual – Selectable (e.g., Automated Manual with paddles) (AM-S8)

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Chevrolet Corvette Z06

– Combined fuel economy: 15 miles per gallon
– Highway fuel economy: 21 mpg
– City fuel economy: 12 mpg
– Manufacturer: General Motors
– Engine size: 5.5 liters
– Cylinders: 8
– Transmission: Semi-Automatic (S8)

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Dodge Charger SRT Widebody

– Combined fuel economy: 15 miles per gallon
– Highway fuel economy: 21 mpg
– City fuel economy: 12 mpg
– Manufacturer: FCA US LLC (Chrysler)
– Engine size: 6.2 liters
– Cylinders: 8
– Transmission: Automatic (A8)

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Cadillac CT5 V

– Combined fuel economy: 15 miles per gallon
– Highway fuel economy: 21 mpg
– City fuel economy: 13 mpg
– Manufacturer: General Motors
– Engine size: 6.2 liters
– Cylinders: 8
– Transmission: Manual (M6)

JDzacovsky // Shutterstock

Dodge Challenger SRT Widebody

– Combined fuel economy: 15 miles per gallon
– Highway fuel economy: 21 mpg
– City fuel economy: 13 mpg
– Manufacturer: FCA US LLC (Chrysler)
– Engine size: 6.2 liters
– Cylinders: 8
– Transmission: Automatic (A8)

Martyn Lucy // Getty Images

Ferrari North America Inc. 812 Competizione

– Combined fuel economy: 14 miles per gallon
– Highway fuel economy: 16 mpg
– City fuel economy: 12 mpg
– Manufacturer: Ferrari
– Engine size: 6.5 liters
– Cylinders: 12
– Transmission: Automated Manual (AM7)

Raymond Boyd // Getty Images

Bentley Continental GT Convertible Speed

– Combined fuel economy: 14 miles per gallon
– Highway fuel economy: 18 mpg
– City fuel economy: 12 mpg
– Manufacturer: Volkswagen
– Engine size: 6 liters
– Cylinders: 12
– Transmission: Automated Manual – Selectable (e.g., Automated Manual with paddles) (AM-S8)

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Rolls-Royce Motor Cars Limited Phantom

– Combined fuel economy: 14 miles per gallon
– Highway fuel economy: 18 mpg
– City fuel economy: 12 mpg
– Manufacturer: Rolls-Royce
– Engine size: 6.7 liters
– Cylinders: 12
– Transmission: Semi-Automatic (S8)

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Chevrolet Corvette Z06 Carbon Aero

– Combined fuel economy: 14 miles per gallon
– Highway fuel economy: 19 mpg
– City fuel economy: 12 mpg
– Manufacturer: General Motors
– Engine size: 5.5 liters
– Cylinders: 8
– Transmission: Semi-Automatic (S8)

Tricky_Shark // Shutterstock

Rolls-Royce Motor Cars Limited Ghost

– Combined fuel economy: 14 miles per gallon
– Highway fuel economy: 19 mpg
– City fuel economy: 12 mpg
– Manufacturer: Rolls-Royce
– Engine size: 6.7 liters
– Cylinders: 12
– Transmission: Semi-Automatic (S8)

Camerasandcoffee // Shutterstock

Rolls-Royce Motor Cars Limited Cullinan

– Combined fuel economy: 14 miles per gallon
– Highway fuel economy: 19 mpg
– City fuel economy: 12 mpg
– Manufacturer: Rolls-Royce
– Engine size: 6.7 liters
– Cylinders: 12
– Transmission: Semi-Automatic (S8)

Sjoerd van der Wal // Getty Images

Mercedes-Benz Maybach S 680 4Matic

– Combined fuel economy: 14 miles per gallon
– Highway fuel economy: 20 mpg
– City fuel economy: 12 mpg
– Manufacturer: Mercedes-Benz
– Engine size: 6 liters
– Cylinders: 12
– Transmission: Automatic (A9)

Mau47 // Shutterstock

Ferrari North America Inc. 812 GTS

– Combined fuel economy: 13 miles per gallon
– Highway fuel economy: 15 mpg
– City fuel economy: 12 mpg
– Manufacturer: Ferrari
– Engine size: 6.5 liters
– Cylinders: 12
– Transmission: Automated Manual (AM7)

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Ferrari North America Inc. Ferrari Monza SP1

– Combined fuel economy: 13 miles per gallon
– Highway fuel economy: 15 mpg
– City fuel economy: 12 mpg
– Manufacturer: Ferrari
– Engine size: 6.5 liters
– Cylinders: 12
– Transmission: Automated Manual (AM7)

Martyn Lucy // Getty Images

Ferrari North America Inc. Ferrari Daytona SP3

– Combined fuel economy: 13 miles per gallon
– Highway fuel economy: 16 mpg
– City fuel economy: 12 mpg
– Manufacturer: Ferrari
– Engine size: 6.5 liters
– Cylinders: 12
– Transmission: Automated Manual (AM7)

Grzegorz Czapski // Shutterstock

Bugatti Chiron

– Combined fuel economy: 11 miles per gallon
– Highway fuel economy: 14 mpg
– City fuel economy: 9 mpg
– Manufacturer: Volkswagen
– Engine size: 8 liters
– Cylinders: 16
– Transmission: Automated Manual – Selectable (e.g., Automated Manual with paddles) (AM-S7)

From chatbots that answer our questions to emails that write themselves, AI is increasingly present in our lives — and the advent of startlingly sophisticated and headline-making tools like ChatGPT suggest that presence is likely to grow.

As it stands, the technologies are advancing at a seemingly breakneck pace, impacting sectors as diverse as public health and transportation. Given the spread, it’s easy to assume AI could be used by just about any company — and there are plenty of adoptees. 

The 2022 McKinsey Global Survey on AI reported in December that although it has stabilized in recent years, the proportion of organizations adopting AI in at least one business area has more than doubled since 2017.

Furthermore, “the average number of AI capabilities that organizations use has also doubled — from 1.9 in 2018 to 3.8 in 2022,” the report found.

But what are companies actually using AI for? And, what are some critical questions experts say companies should ask themselves before going all-in?

Let’s take a closer look.

Why AI is becoming increasingly useful

One reason AI is becoming especially useful is because by definition, it is the ability of machines to learn and make decisions based on data and analytics. And it should come as no surprise that companies now have access to more data than ever before. 

How much more? Well, Gil Press — a senior contributor with Forbes — reported toward the end of 2020 that in the 10 years that came before, “the amount of data created, captured, copied, and consumed in the world increased from 1.2 trillion gigabytes to 59 trillion gigabytes.”

That’s almost 5,000 per cent growth, Press said.

And with the help of emerging technologies like AI, the University of Pennsylvania’s Wharton Online explained, companies are now able to capture user data that can help them make informed business decisions.

“AI is no longer an experimental technology only used by select brands,” it said. “For many companies around the world, it has become a core part of their operations.”

AI: What is it used for?

So, how is AI being used by companies and organizations?

Common applications cited by Business News Daily include the detection of cyberattacks and threats, digital personal assistants that manage calendars, and customer service chatbots.

The latter is also where some companies are using ChatGPT. Bloomberg reported on March 1 that the technology has already found a home on apps for Instacart, where customers will be able to ask it questions about recipes; Shopify, where it will offer suggestions; and Quizlet Inc., where it will provide users with a “tutoring experience.”

In more specialized fields like healthcare, AI’s uses include helping to make potentially life-saving cancer diagnoses. The New York Times reported on March 5 that AI known as “computer-assisted detection” is helping to detect breast cancer missed by mammograms.

More generally, some popular uses for AI include service operations optimization, contact centre automation, customer service analytics, sales and demand forecasting, and risk modeling and analytics, according to the 2022 McKinsey Global Survey on AI.

And when it comes to deciding how to apply AI, Wharton Online reported that companies often focus on driving growth. 

That growth, according to Entrepreneur’s Auria Moore, is focused on three central areas: 

• AI-powered analytics, which can allow businesses to gather information about users for better product creation.
• Customer service satisfaction, where AI chatbots can provide answers to users faster.
• Targeted digital marketing campaigns, which has AI granting marketers the ability to “enhance personalization at an individual level.”

Meanwhile, supply-chain management is where the highest-reported cost benefits from AI were identified in the McKinsey survey — while “the biggest reported revenue effects are found in marketing and sales, product and service development, and strategy and corporate finance.”

“The bottom-line value realized from AI remains strong and largely consistent,” the report said.

“About a quarter of respondents report this year that at least 5 percent of their organizations’ [earnings before interest and taxes] was attributable to AI in 2021, in line with findings from the previous two years.”

What to consider before going all-in

Given its vast possibilities for application and seemingly limitless potential, investing in AI could seem like a no-brainer for businesses. But some experts warn that it shouldn’t be.

“The first question to ask yourself when considering AI is what problems might be solved with the technology,” Inc.’s Ben Sherry reported last May.

While some companies would find AI genuinely useful — for example, Sherry said, an e-commerce company could use it to market specific products to customers based on data — others could wind up with an unnecessary expense.

“Ask yourself if automating part of your business has an easily identifiable benefit, or whether you have routine tasks that could easily be automated,” he suggested.

AI’s algorithms also need a lot of high-quality data to deliver valuable insights, Open Data Science (ODSC) explained in November 2021, and machine learning needs varied data to build its intelligence.

So before investing in AI, ODSC said, it’s critical to make sure your company has access to a sufficient amount of high-quality data sets.

“Without data and specifically, high-quality data, your AI investment is useless,” ODSC said. 

“It’s essentially like purchasing an expensive car with an incredibly powerful motor without any access to a fuel source.”

Finally, some experts say a critically important question for companies considering AI to ask themselves is: what are the consequences if it fails?

“AI models work through very sophisticated algorithms and statistical correlations, but there is always a margin of error. Does the company want to implement AI in a process with high variability and a low accuracy rate, or the opposite? What risks and how much investment would be lost if it didn’t work out?” industrial IoT company Nexus Integra asked in a blog post.

“Depending on which systems and data are available, the company must evaluate whether the accuracy of these models is expected to be high enough to proceed.”

And Ricardo Baeza-Yates, director of research at the Institute for Experiential AI at Northeastern University, wrote in an August 2021 piece for Forbes that “as the usage of AI grows exponentially, so have the number of AI incidents.”

As such, Baeza-Yates said companies looking to use AI should first ask themselves if they have deeply considered the direct, and indirect, impact of their product or service.

“Here, the accuracy of your model is irrelevant. What matters is the impact of the mistakes you make, even if they are few,” he wrote.“In cases where people were falsely accused by facial recognition systems, killed by driverless cars or unethically targeted for fraud, the damage was severe and lasting.”

For many Americans, the typical life plan has long been school, work, retirement at 65, and living comfortably. But not as many people are traveling that path anymore.

Nearly 19% of people of retirement age—65 years or older—remain in the workforce. In fact, Americans over 55 are the only age group that increased its labor force participation rate from 2001 to 2021. Projections expect that trend to continue into the next decade.

Many simply don’t want to retire because they enjoy what they do and don’t want to slow down. Some find that retirement doesn’t suit them and return to work to add meaning to their lives.

Others work because they can’t afford retirement. According to the Economic Policy Institute, roughly one-third of workers aged 55 to 64 don’t have access to a retirement savings plan. Those who rely solely on Social Security benefits may find they don’t cover all of their living expenses. Major unplanned expenses like medical bills can also keep people in the workforce.

Stacker used 2021 data from the Bureau of Labor Statistics and the Census Bureau to find what share of each state’s retirement-age population, those 65 and older, still participate in the labor force. Labor force statistics are calculated based on the civilian noninstitutional population, meaning those adults who are not incarcerated or in long-term medical facilities. It’s helpful to note that age 65 is the typical age for retirement, as it’s the age to qualify for Medicare.

Continue reading to find out whether your state has the most adults of retirement age still at work.

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#51. South Carolina

– Labor force participation among ages 65+: 14% (142,000 people)
– Population ages 65+: 18.6% (967,223 people)

Sean Pavone // Shutterstock

#50. West Virginia

– Labor force participation among ages 65+: 14.8% (56,000 people)
– Population ages 65+: 20.7% (368,775 people)

Sean Pavone // Shutterstock

#49. Mississippi

– Labor force participation among ages 65+: 14.9% (73,000 people)
– Population ages 65+: 16.8% (496,945 people)

Tim Roberts Photography // Shutterstock

#48. Arizona

– Labor force participation among ages 65+: 15.1% (195,000 people)
– Population ages 65+: 18.3% (1.33 million people)

Sean Pavone // Shutterstock

#47. Alabama

– Labor force participation among ages 65+: 15.8% (137,000 people)
– Population ages 65+: 17.6% (885,809 people)

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#46. Tennessee

– Labor force participation among ages 65+: 16% (194,000 people)
– Population ages 65+: 17.0% (1.19 million people)

f11photo // Shutterstock

#45. Kentucky

– Labor force participation among ages 65+: 16.1% (123,000 people)
– Population ages 65+: 17.0% (768,416 people)

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#44. New Mexico

– Labor force participation among ages 65+: 16.3% (65,000 people)
– Population ages 65+: 18.5% (391,797 people)

Eduardo Medrano // Shutterstock

#43. Arkansas

– Labor force participation among ages 65+: 16.6% (91,000 people)
– Population ages 65+: 17.4% (525,153 people)

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#42. Florida

– Labor force participation among ages 65+: 16.7% (744,000 people)
– Population ages 65+: 21.1% (4.60 million people)

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#41. Delaware

– Labor force participation among ages 65+: 17.1% (35,000 people)
– Population ages 65+: 20.1% (201,551 people)

Paul Brady Photography // Shutterstock

#39. Michigan (tie)

– Labor force participation among ages 65+: 17.2% (319,000 people)
– Population ages 65+: 18.1% (1.82 million people)

photo.ua // Shutterstock

#39. Ohio (tie)

– Labor force participation among ages 65+: 17.2% (373,000 people)
– Population ages 65+: 17.8% (2.10 million people)

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#37. Georgia (tie)

– Labor force participation among ages 65+: 17.4% (279,000 people)
– Population ages 65+: 14.7% (1.59 million people)

Charles Knowles // Shutterstock

#37. Idaho (tie)

– Labor force participation among ages 65+: 17.4% (56,000 people)
– Population ages 65+: 16.5% (314,010 people)

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#35. Washington (tie)

– Labor force participation among ages 65+: 17.8% (213,000 people)
– Population ages 65+: 16.2% (1.25 million people)

marchello74 // Shutterstock

#35. Illinois (tie)

– Labor force participation among ages 65+: 17.8% (373,000 people)
– Population ages 65+: 16.6% (2.10 million people)

Josemaria Toscano // Shutterstock

#34. Oregon

– Labor force participation among ages 65+: 18% (148,000 people)
– Population ages 65+: 18.6% (789,896 people)

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#33. Pennsylvania

– Labor force participation among ages 65+: 18.3% (466,000 people)
– Population ages 65+: 19.0% (2.46 million people)

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#32. Missouri

– Labor force participation among ages 65+: 18.6% (203,000 people)
– Population ages 65+: 17.6% (1.08 million people)

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#31. New York

– Labor force participation among ages 65+: 18.9% (669,000 people)
– Population ages 65+: 17.5% (3.48 million people)

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#30. North Carolina

– Labor force participation among ages 65+: 19.1% (367,000 people)
– Population ages 65+: 17.0% (1.80 million people)

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#29. Louisiana

– Labor force participation among ages 65+: 19.3% (147,000 people)
– Population ages 65+: 16.6% (766,330 people)

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#27. Indiana (tie)

– Labor force participation among ages 65+: 19.5% (219,000 people)
– Population ages 65+: 16.4% (1.12 million people)

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#27. California (tie)

– Labor force participation among ages 65+: 19.5% (1.18 million people)
– Population ages 65+: 15.2% (5.96 million people)

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#26. Virginia

– Labor force participation among ages 65+: 19.6% (277,000 people)
– Population ages 65+: 16.3% (1.41 million people)

Sean Pavone // Shutterstock

#25. Oklahoma

– Labor force participation among ages 65+: 19.7% (126,000 people)
– Population ages 65+: 16.2% (645,174 people)

Canva

#24. Texas

– Labor force participation among ages 65+: 19.9% (788,000 people)
– Population ages 65+: 13.2% (3.89 million people)

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#21. Wisconsin (tie)

– Labor force participation among ages 65+: 20.1% (205,000 people)
– Population ages 65+: 17.9% (1.05 million people)

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#21. Maine (tie)

– Labor force participation among ages 65+: 20.1% (63,000 people)
– Population ages 65+: 21.7% (297,101 people)

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#21. Nevada (tie)

– Labor force participation among ages 65+: 20.1% (114,000 people)
– Population ages 65+: 16.5% (519,568 people)

Canva

#20. Utah

– Labor force participation among ages 65+: 20.9% (79,000 people)
– Population ages 65+: 11.6% (388,120 people)

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#18. Colorado (tie)

– Labor force participation among ages 65+: 21% (182,000 people)
– Population ages 65+: 15.1% (880,167 people)

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#18. New Jersey (tie)

– Labor force participation among ages 65+: 21% (341,000 people)
– Population ages 65+: 16.9% (1.56 million people)

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#17. Montana

– Labor force participation among ages 65+: 21.1% (49,000 people)
– Population ages 65+: 19.7% (217,298 people)

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#16. New Hampshire

– Labor force participation among ages 65+: 22% (65,000 people)
– Population ages 65+: 19.3% (267,741 people)

MNStudio // Shutterstock

#13. Hawaii (tie)

– Labor force participation among ages 65+: 22.1% (62,000 people)
– Population ages 65+: 19.6% (282,567 people)

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#13. Wyoming (tie)

– Labor force participation among ages 65+: 22.1% (23,000 people)
– Population ages 65+: 17.9% (103,822 people)

Wangkun Jia // Shutterstock

#13. Massachusetts (tie)

– Labor force participation among ages 65+: 22.1% (271,000 people)
– Population ages 65+: 17.4% (1.22 million people)

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#12. North Dakota

– Labor force participation among ages 65+: 22.7% (29,000 people)
– Population ages 65+: 16.0% (123,840 people)

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#11. Rhode Island

– Labor force participation among ages 65+: 22.9% (48,000 people)
– Population ages 65+: 18.3% (200,201 people)

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#10. Iowa

– Labor force participation among ages 65+: 23.3% (130,000 people)
– Population ages 65+: 17.8% (567,581 people)

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#9. Maryland

– Labor force participation among ages 65+: 23.4% (234,000 people)
– Population ages 65+: 16.3% (1.00 million people)

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#7. Minnesota (tie)

– Labor force participation among ages 65+: 23.5% (215,000 people)
– Population ages 65+: 16.8% (959,272 people)

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#7. Washington D.C. (tie)

– Labor force participation among ages 65+: 23.5% (20,000 people)
– Population ages 65+: 12.8% (85,615 people)

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#6. Kansas

– Labor force participation among ages 65+: 23.8% (116,000 people)
– Population ages 65+: 16.7% (489,676 people)

Sean Pavone // Shutterstock

#5. Connecticut

– Labor force participation among ages 65+: 24.3% (164,000 people)
– Population ages 65+: 18.0% (649,172 people)

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#4. Alaska

– Labor force participation among ages 65+: 24.7% (24,000 people)
– Population ages 65+: 13.4% (98,410 people)

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#2. Nebraska (tie)

– Labor force participation among ages 65+: 25% (77,000 people)
– Population ages 65+: 16.4% (322,833 people)

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#2. Vermont (tie)

– Labor force participation among ages 65+: 25% (36,000 people)
– Population ages 65+: 20.6% (133,173 people)

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#1. South Dakota

– Labor force participation among ages 65+: 26.7% (Estimated 42,000)
– Population ages 65+: 17.6% (157,883 people)

Note: Labor force participation data for South Dakota seniors was not available from BLS, so Stacker used data from a South Dakota Department of Labor report. Stacker estimated the state’s 65+ labor force based on available Census Bureau data. Since the data comes from two sources, there may be some discrepancies in actual values and comparisons.