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Microsoft to Let Clients Build AI Agents for Routine Tasks from November

General view of Microsoft Corporation headquarters at Issy-les-Moulineaux, near Paris, France, April 18, 2016. REUTERS/Charles Platiau/File Photo
General view of Microsoft Corporation headquarters at Issy-les-Moulineaux, near Paris, France, April 18, 2016. REUTERS/Charles Platiau/File Photo
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Microsoft to Let Clients Build AI Agents for Routine Tasks from November

General view of Microsoft Corporation headquarters at Issy-les-Moulineaux, near Paris, France, April 18, 2016. REUTERS/Charles Platiau/File Photo
General view of Microsoft Corporation headquarters at Issy-les-Moulineaux, near Paris, France, April 18, 2016. REUTERS/Charles Platiau/File Photo

Microsoft will allow its customers to build autonomous artificial intelligence agents from next month, in its latest push to tap the booming technology amid growing investor scrutiny of its hefty AI investments.
The company is positioning autonomous agents - programs that need little human intervention unlike chatbots - as "apps for an AI-driven world" that can handle client queries, identify sales leads and manage inventory, Reuters said.
Other big technology companies such as Salesforce have also touted the potential of such agents, tools that some analysts say could provide companies with an easier path to monetizing the billions of dollars they are pouring into AI.
Microsoft said its customers can use Copilot Studio - an application that requires little knowledge of computer code - to create such agents in public preview from November. It is using several AI models developed in-house and by OpenAI for the agents.
The company is also introducing 10 ready-for-use agents that can help with routine tasks ranging from managing supply chain to expense tracking and client communications.
In a demo, McKinsey & Co, which had early access to the tools, created an agent that can manage client inquires by checking interaction history, identifying the consultant for the task and scheduling a follow-up meeting.
"The idea is that Copilot (the company's chatbot) is the user interface for AI," Charles Lamanna, corporate vice president of business and industry Copilot at Microsoft, told Reuters.
"Every employee will have a Copilot, their personalized AI agent, and then they will use that Copilot to interface and interact with the sea of AI agents that will be out there."
Tech giants are facing pressure to show returns on their big AI investments. Microsoft's shares fell 2.8% in the September quarter, underperforming the S&P 500, but remain more than 10% higher for the year.
Some concerns have risen in recent months about the pace of Copilot adoption, with research firm Gartner saying in August its survey of 152 IT organizations showed the vast majority had not progressed their Copilot initiatives past the pilot stage.

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Technology

Meta Shares Skyrocket, Microsoft Slides on Wall Street after Earnings

A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
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Meta Shares Skyrocket, Microsoft Slides on Wall Street after Earnings

A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson

Shares in Meta skyrocketed by 10 percent at opening on Wall Street on Thursday, a day after the social media giant posted better than expected earnings as the company invests heavily in artificial intelligence.

Microsoft, whose earnings disappointed analysts, saw its share price tumble by 10 percent, with investors showing concern for the return on investment for the software giant's spending on AI.

Technology

Samsung Logs Best-ever Profit on AI Chip Demand

South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
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Samsung Logs Best-ever Profit on AI Chip Demand

South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File

South Korean tech giant Samsung Electronics posted record quarterly profits Thursday, riding massive market demand for the memory chips that power artificial intelligence.

A global frenzy to build AI data centers and develop the fast-evolving technology has sent orders for advanced high bandwidth memory microchips soaring.

That is also pushing up prices for less flashy chips used in consumer electronics -- threatening higher prices for phones, laptops and other devices worldwide.

In the quarter to December 2025, Samsung said it saw "its highest-ever quarterly consolidated revenue at KRW 93.8 trillion (US$65.5 billion)", a quarter-on-quarter increase of nine percent.

"Operating profit was also an all-time high, at KRW 20.1 trillion," the company said.

The dazzling earnings came a day after a key competitor, South Korean chip giant SK hynix, said operating profit had doubled last year to a record high, also buoyed by the AI boom.

The South Korean government has pledged to become one of the top three AI powers, behind the United States and China, with Samsung and SK hynix among the leading producers of high-performance memory.

Samsung said Thursday it expects "AI and server demand to continue increasing, leading to more opportunities for structural growth".

Annual revenue stood at 333.6 trillion won, while operating profit came in at 43.6 trillion won. Sales for the division that oversees its semiconductor business rose 33 percent quarter-on-quarter.

The company pointed to a $33.2 billion investment in chip production facilities -- pledging to continue spending in "transitioning to advanced manufacturing processes and upgrading existing production lines to meet rising demand".

- 'Clearly back' -

Major electronics manufacturers and industry analysts have warned that chipmakers focusing on AI sales will cause higher retail prices for consumer products across the board.

This week US chip firm Micron said it was building a $24 billion plant in Singapore in response to AI-driven demand that has caused a global shortage of memory components.

SK hynix announced Wednesday that its operating profit had doubled last year to a record 47.2 trillion won.

The company's shares have surged some 220 percent over the past six months, while Samsung Electronics has risen about 130 percent, part of a huge global tech rally fueled by optimism over AI.

Both companies are on the cusp of producing next-generation high-bandwidth "HBM4" chips for AI data centers, with Samsung reportedly due to start making them in February.

American chip giant Nvidia -- now the world's most valuable company -- is expected to be one of Samsung's customers for HBM4 chips.

But Nvidia has reportedly allocated around 70 percent of its HBM4 demand to SK hynix for 2026, up from the market's previous estimate of 50 percent.

"Samsung is clearly back and we are expecting them to show a significant turnaround with HBM4 for Nvidia's new products -- helping them move past last year's quality issues," Hwang Min-seong, research director at market analysis firm Counterpoint, told AFP.

But SK still "maintains a market lead in both quality and supply" of a number of key components, including Dynamic Random Access Memory chips used in AI servers, he said.

SK also this week said it will set up an "AI solutions firm" in the United States, committing $10 billion and weighing investments in US companies.

Technology

Google Unveils AI Tool Probing Mysteries of Human Genome

A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
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Google Unveils AI Tool Probing Mysteries of Human Genome

A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)

Google unveiled an artificial intelligence tool Wednesday that its scientists said would help unravel the mysteries of the human genome -- and could one day lead to new treatments for diseases.

The deep learning model AlphaGenome was hailed by outside researchers as a "breakthrough" that would let scientists study and even simulate the roots of difficult-to-treat genetic diseases.

While the first complete map of the human genome in 2003 "gave us the book of life, reading it remained a challenge", Pushmeet Kohli, vice president of research at Google DeepMind, told journalists.

"We have the text," he said, which is a sequence of three billion nucleotide pairs represented by the letters A, T, C and G that make up DNA.

However, "understanding the grammar of this genome -- what is encoded in our DNA and how it governs life -- is the next critical frontier for research," said Kohli, co-author of a new study in the journal Nature.

Only around two percent of our DNA contains instructions for making proteins, which are the molecules that build and run the body.

The other 98 percent was long dismissed as "junk DNA" as scientists struggled to understand what it was for.

However, this "non-coding DNA" is now believed to act like a conductor, directing how genetic information works in each of our cells.

These sequences also contain many variants that have been associated with diseases. It is these sequences that AlphaGenome is aiming to understand.

- A million letters -

The project is just one part of Google's AI-powered scientific work, which also includes AlphaFold, the winner of 2024's chemistry Nobel.

AlphaGenome's model was trained on data from public projects that measured non-coding DNA across hundreds of different cell and tissue types in humans and mice.

The tool is able to analyze long DNA sequences then predict how each nucleotide pair will influence different biological processes within the cell.

This includes whether genes start and stop and how much RNA -- molecules which transmit genetic instructions inside cells -- is produced.

Other models already exist that have a similar aim. However, they have to compromise, either by analyzing far shorter DNA sequences or decreasing how detailed their predictions are, known as resolution.

DeepMind scientist and lead study author Ziga Avsec said that long sequences -- up to a million DNA letters long -- were "required to understand the full regulatory environment of a single gene".

And the high resolution of the model allows scientists to study the impact of genetic variants by comparing the differences between mutated and non-mutated sequences.

"AlphaGenome can accelerate our understanding of the genome by helping to map where the functional elements are and what their roles are on a molecular level," study co-author Natasha Latysheva said.

The model has already been tested by 3,000 scientists across 160 countries and is open for anyone to use for non-commercial reasons, Google said.

"We hope researchers will extend it with more data," Kohli added.

- 'Breakthrough' -

Ben Lehner, a researcher at Cambridge University who was not involved in developing AlphaGenome but did test it, said the model "does indeed perform very well".

"Identifying the precise differences in our genomes that make us more or less likely to develop thousands of diseases is a key step towards developing better therapeutics," he explained.

However, AlphaGenome "is far from perfect and there is still a lot of work to do", he added.

"AI models are only as good as the data used to train them" and the existing data is not very suitable, he said.

Robert Goldstone, head of genomics at the UK's Francis Crick Institute, cautioned that AlphaGenome was "not a magic bullet for all biological questions".

This was partly because "gene expression is influenced by complex environmental factors that the model cannot see", he said.

However, the tool still represented a "breakthrough" that would allow scientists to "study and simulate the genetic roots of complex disease", Goldstone added.