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3 Houston-area companies make Fortune's first ranking of top AI adopters

Hewlett Packard Enterprise Company in Houston

Spring-based Hewlett Packard Enterprise makes the inaugural Fortune AI list.

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Three businesses based in the Houston area appear on Fortune's inaugural list of the top adopters of AI among Fortune 500 companies.

They are:

No. 7 energy company ExxonMobil, based in Spring
No. 19 tech company Hewlett Packard Enterprise, based in Spring
No. 47 energy company Chevron, based in Houston

All three companies have taken a big dive into the AI pool.

In 2024, ExxonMobil's executive chairman and CEO Darren Woods explained that AI would play a key role in achieving a $15 billion reduction in operating costs by 2027.

"There is a concerted effort to make sure that we're really working hard to apply that new technology to the opportunity set within the company to drive effectiveness and efficiency," Woods told Wall Street analysts.

Hewlett Packard Enterprise is also employing AI to decrease costs. In March, the company announced a restructuring plan — including the elimination of 3,000 jobs — aimed at cutting about $350 million in annual expenses. The restructuring is scheduled to wrap up by the end of October.

Hewlett Packard Enterprise’s Catalyst cost-cutting program includes a push to use AI across the company to improve efficiency, Marie Myers, the company’s executive vice president and chief financial officer, told Wall Street analysts in June.

"Our ambition is clear: A leaner, faster, and more competitive organization. Nothing is off limits. We are focused on rethinking the business — not just reducing our costs, but transforming the way we operate," Myers said.

At Chevron, AI tools are being used to quickly analyze data and extract insights from it, according to tech news website VentureBeat. Also, Chevron employs advanced AI systems known as large language models (LLMs) to create engineering standards, specifications and safety alerts. AI is even being put to work in Chevron’s exploration initiatives.

Bill Braun, Chevron’s chief information officer, said at a VentureBeat-sponsored event in 2024 that AI-savvy data scientists, or "digital scholars," are always embedded within workplace teams "to act as a catalyst for working differently."

The Fortune AIQ 50 ranking is based on ServiceNow’s Enterprise AI Maturity Index, an annual measurement of how prepared organizations are to adopt and scale AI. To evaluate how Fortune 500 companies are rolling out AI and how much they value AI investments, Fortune teamed up with Enterprise Technology Research. The results went into computing an AIQ score for each company.

At the top of the ranking is Alphabet (owner of Google and YouTube), followed by Visa, JPMorgan Chase, Nvidia and Mastercard.

Aside from ExxonMobil, Hewlett Packard Enterprise, and Chevron, two other Texas companies made the list: Arlington-based homebuilder D.R. Horton (No. 29) and Austin-based software company Oracle (No. 37).

"The Fortune AIQ 50 demonstrates how companies across industry sectors are beginning to find real value from the deployment of AI technology," Jeremy Kahn, Fortune’s AI editor, said in a news release. "Clearly, some sectors, such as tech and finance, are pulling ahead of others, but even in so-called 'old economy' industries like mining and transport, there are a few companies that are pulling away from their peers in the successful use of AI."

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This story originally appeared on our sister site, InnovationMap.

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brain scientists at work

Rice University scientists invent new algorithm to fight Alzheimer's

Vicky Yao and Qiliang Lai of Rice University work on a laptop.

Photo courtesy of Rice University

Vicky Yao, an assistant professor of computer science and member of the Ken Kennedy Institute at Rice University, and Qiliang Lai, a Rice postdoctoral researcher

A new breakthrough from researchers at Rice University could unlock the genetic components that determine several human diseases such as Parkinson's and Alzheimer's.

Alzheimer's disease affected 57 million people worldwide in 2021, and cases in the United States are expected to double in the next couple of decades. Despite its prevalence and widespread attention of the condition, the full mechanisms are still poorly understood. One hurdle has been identifying which brain cells are linked to the disease.

For years, it was thought that the cells most linked with Alzheimer's pathology via DNA evidence were microglia, infection-fighting cells in the brain. However, this did not match with actual studies of Alzheimer's patients' brains. It's the memory-making cells in the human brain that are implicated in the pathology.

To prove this link, researchers at Rice alongside Boston University developed a computational algorithm called “Single-cell Expression Integration System for Mapping genetically implicated Cell types," or SEISMIC. It allows researchers to zero in on specific neurons linked to Alzheimer's, the first of its kind. Qiliang Lai, a Rice doctoral student and the lead author of a paper on the discovery published in Nature Communications, believes that this is an important step in the fight against Alzheimer's.

“As we age, some brain cells naturally slow down, but in dementia ⎯ a memory-loss disease ⎯ specific brain cells actually die and can’t be replaced,” said Lai. “The fact that it is memory-making brain cells dying and not infection-fighting brain cells raises this confusing puzzle where DNA evidence and brain evidence don’t match up.”

Studying Alzheimer's has been hampered by the limitations of computational analysis. Genome-wide association studies (GWAS) and single-cell RNA sequencing (scRNA-seq) map small differences in the DNA of Alzheimer's patients. The genetic signal in these studies would often over-emphasize the presence of infection fighting cells, essentially making the activity of those cells too "loud" statistically to identify other factors. Combined with greater specificity in brain regional activity, SEISMIC reduces the data chatter to grant a clearer picture of the genetic component of Alzheimer's.

“We built our seismic algorithm to analyze genetic information and match it precisely to specific types of brain cells,” Lai said. “This enables us to create a more detailed picture of which cell types are affected by which genetic programs.”

Though the algorithm is not in and of itself likely to lead to a cure or treatment for Alzheimer's any time soon, the researchers say that SEISMIC is already performing significantly better than existing tools at identifying important disease-relevant cellular signals more clearly.

“We think this work could help reconcile some contradicting patterns in the data pertaining to Alzheimer’s research,” said Vicky Yao, assistant professor of computer science and a member of the Ken Kennedy Institute at Rice. “Beyond that, the method will likely be broadly valuable to help us better understand which cell types are relevant in different complex diseases.”

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