Category: 3. Business

The federal government could “explore” using artificial intelligence programs to write sensitive cabinet submissions or business cases, as part of a major initiative to embed AI across the public service, despite concerns about the technology increasing risks of security and data breaches.

The finance minister, Katy Gallagher, also announced on Wednesday the public service would build its own special AI program for government workers, spruiking productivity benefits for rolling out generative programs such as ChatGPT, Copilot and Gemini to departments.

While many public servants said trials of AI had helped their work, others voiced alarm at the poor quality and inaccuracies in AI-generated work, the potential slashing of entry-level jobs, and public fears about automated decision-making in the wake of the robodebt scandal.

“Interviews with Australian government agencies highlighted that women could be disproportionately impacted as they currently comprise most APS administration staff,” stated a government report into a trial of Microsoft Copilot.

Gallagher, also minister for the public service, told a conference the government wanted to see AI “widely taken up across government in every department” in a bid to “take hold of the opportunities that AI presents”.

Gallagher also launched a “whole of government AI plan”, and results from a six-month trial of Microsoft’s Copilot across government.

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The report’s main finding was: “There are clear benefits to the adoption of generative AI but also challenges with adoption and concerns that need to be monitored.”

Surveys found most trial participants were positive, noting management and executives specifically had reported productivity benefits and saving up to an hour each day through AI helping summarise information, write first drafts, or search for information.

Some 69% said it helped them work faster and 61% said it improved the quality of their work.

However, a range of negatives were also reported, including “inaccuracy” of AI output, with 60% of participants saying they had to make “moderate to significant” edits to the AI-generated work. There were also concerns about “Copilot’s potential unpredictability and lack of contextual knowledge”.

The AI plan sets out a goal “that every public servant will have training and access to generative AI tools”. It says the to-be-developed GovAI Chat program will be rolled out widely, expected to be in the first part of 2026, but the government will also develop guidance on public servants using public platforms, such as ChatGPT, Claude and Gemini, to handle government information up to the “official” level of classification.

That included “novel” suggestions from participants to use AI for assessing documents, writing public documents, and “drafting content for business cases and Cabinet submissions”. The report included these ideas under a heading of “opportunities to further explore use cases”.

But the Copilot report also raised security issues with data, with instances of “Copilot inappropriately accessing sensitive information”.

“Use of Copilot enabled some participants to access documents that they should not have had permission to access. Trial participants raised instances where Copilot surfaced sensitive data that staff had not classified or stored appropriately,” it said.

“This was largely because their organisation had not properly assured the security and storage of some instances of data and information before adopting Copilot. Without the appropriate data infrastructure and governance in place, the use of Copilot may further exacerbate risks of data and security breaches in the APS.”

The report also noted public expectations around managing data.

“In the wake of the Royal Commission into the Robodebt Scheme, public scrutiny around the APS’ use of technology and automation to support decision-making is particularly high,” it stated.

Gallagher pledged ongoing consultation with staff and unions about job changes, stressing that the government “does not view widespread AI adoption across the APS as a way of replacing people”. The Community and Public Sector Union was contacted for comment.

Vivek Puthucode, Microsoft’s general manager of public sector, backed the government’s plan and said the new technology could “help improve service delivery, strengthen policy outcomes and make government more responsive to community needs”.

November 12, 2025

NTT DATA Group Corporation

TOKYO – November 12, 2025 – NTT DATA, a global leader in AI, digital business and technology services, today announced that it has once again been named a Leader by Everest Group in its 5G Engineering Services PEAK Matrix^® Assessment 2025 report (PDF : 551KB). This is the second consecutive time NTT DATA has been recognized as a leader in the assessment This distinction underscores NTT DATA’s consistent growth in market impact, vision and capabilities.

The report evaluated 20 leading providers across the 5G engineering services ecosystem, assessing their vision, capabilities and market impact. Everest Group highlighted NTT DATA’s robust offerings across the value chain, from equipment and network orchestration to engineering solutions and use case deployments, positioning the company as a true provider of end-to-end solutions.

Everest Group praised NTT DATA for its globally distributed delivery model, which offers clients local proximity, access to regional talent and cost efficiency at scale. The recognition also reflects NTT DATA’s ongoing investments in intellectual property (IP) development, strategic partnerships, skills development initiatives and its global network of labs and Centers of Excellence (CoEs).

“NTT DATA has been recognized as a Leader in Everest Group’s 5G Engineering Services PEAK Matrix^® Assessment 2025, supported by its rapid client expansion, combined capabilities post-merger and a robust services portfolio spanning across the 5G value chain. Its strengths include end-to-end solutions from networks to use cases, in-house IP and frameworks and investments in labs and CoEs that enhance service quality. NTT DATA is diversifying its portfolio across private 5G, AI, NTN and monetization-oriented use cases. Clients have appreciated NTT DATA’s telecom heritage, delivery model efficiency and ability to execute with global consistency,” said Nishant Udupa, Practice Director at Everest Group.

The report also highlighted NTT DATA’s ability to capitalize on emerging technologies such as Artificial Intelligence (AI), Non-terrestrial Networks (NTN), Multi-access Edge Computing (MEC), Application Programming Interfaces (APIs) and monetization strategies as key strengths, report also noted the company’s strong presence in private 5G.

As enterprises adopt private 5G to power intelligent operations, digital transformations and new revenue streams, NTT DATA is delivering innovative, outcome-driven solutions.

Across industries such as manufacturing and automotive as well as smart cities, clients are already benefiting from private 5G networks for AI-driven analytics, real-time monitoring and enhanced connectivity. A recent example includes the City of Brownsville, Texas which is using NTT DATA’s Private 5G network to improve city operations and community services.

“Enterprises today expect far more from private 5G than just connectivity, they look to it as a catalyst for AI-based operations such as robotics and Physical AI,” said Shahid Ahmed, Global Head of Edge Services, NTT DATA, Inc. “This recognition from Everest Group underscores our ability to deliver on those expectations. By securing contracts from world-class clients, strategic partnerships and a globally distributed delivery model, we help clients accelerate time to market, enhance performance and unlock the full value of private 5G.”

The PEAK Matrix^® assessment is based on Everest Group’s RFI submissions, briefings, client references and ongoing research in the 5G engineering space. Leaders are distinguished by significant investments in building IP, automation frameworks and CoEs to support full-stack 5G engineering across RAN, core, private 5G and monetization use cases, including with hyperscalers, NEPs and OEMs.

For more information, find the full report here.

By Bill Peters

One analyst says payment delays across states are likely, even after the government’s reopening

McDonald’s last week said disruptions to SNAP payments could be putting “additional pressure” on consumers.

As the U.S. government shutdown constrains SNAP food assistance for millions of low-income Americans this month, corporate executives have started to get nervous, even as some say they have yet to feel the impact.

Their remarks on recent earnings calls have come amid what has been the longest government shutdown in the nation’s history. A bill to keep the government open until Jan. 30 cleared the Senate on Monday; the House of Representatives could vote on it Wednesday, but it could still take days for services to be fully restored.

The pause on some of the SNAP benefits, along with recent cuts to the program, also arrived after more than three years in which lower-income customers have felt the impact of price increases more acutely. More executive commentary on that issue, and the shutdown’s impact on SNAP, could come next week when Walmart Inc. (WMT) reports results.

At McDonald’s Corp. (MCD), Chief Executive Chris Kempczinski said last week that the disruption in SNAP benefits added to the stress that lower-income consumers, in particular, were facing.

“If you’re not in that segment and you’re higher income, you don’t feel it as acutely – but lower income, for sure, you’re feeling it acutely,” Kempczinski said during the burger chain’s earnings call. “And I think some of what’s going on most recently with SNAP and other things might be additional pressure on that.”

Kristina Lambert, chief growth officer at poultry producer Tyson Foods Inc. (TSN), said on Monday that “we do see consumer spending patterns again changing from nonfood to more food categories.” She added that the company had a “wide range of product offerings at different budget levels.”

The government shutdown began on Oct. 1, and disruptions to SNAP payments – short for Supplemental Nutrition Assistance Program, although the benefits are still commonly referred to as food stamps – began this month, overwhelming food banks and deepening concerns about food security in the nation. A court battle has ensued over how much of that funding people can receive while the government is shut down. The agreement that advanced through the Senate on Monday would keep SNAP payments flowing through next September.

More than 40 million Americans receive SNAP benefits. Robert Moskow, an analyst at TD Cowen, said in a research note last month that SNAP accounts for 12% of spending on food and beverages. The One Big Beautiful Bill Act that President Donald Trump signed into law over the summer included cuts to that program, expanded work requirements and other restrictions.

Still, Moskow said payment delays across states were likely after the government reopened. If people who receive those benefits cut back their grocery bills by 15%, total grocery sales would fall 1.8%, he estimated.

Elsewhere on recent earnings calls, Instacart (CART) said it didn’t expect a big impact from missed or delayed SNAP payments, noting the program accounted for a small part of its business. Hershey Co. (HSY) said it hadn’t seen a big impact yet, and poultry producer Pilgrim’s Pride Corp. (PPC) said it believed the impact would be temporary.

Dole (DOLE) said it had “not seen any trends out of the shutdowns,” while food producer B&G Foods Inc. (BGS)- known for brands like Crisco, Green Giant and Ortega – said last week that it was too early to gauge the impact.

More broadly, some companies have been more cautious with their forecasts overall to account for any possible impact from the shutdown. But for others, the SNAP disruptions proved too difficult to predict.

Grocery Outlet Holding Corp. (GO) said on its earnings call last week that “any potential disruption to sales resulting from delayed or missed SNAP benefits” was not currently factored into the company’s financial outlook. Chief Financial Officer Christopher Miller noted that the percentage of the grocery chain’s sales that came from electronic benefits transfer, or EBT, payments – which are often tied to SNAP benefits – was around 9% last year.

Grocery Outlet CEO Jason Potter said that its independent store operators would be raising money for food banks. He noted that cuts to SNAP benefits in 2023 didn’t affect sales, and that payments of the benefits typically led to immediate spending.

But at Kraft Heinz Co. (KHC), CEO Carlos Abrams-Rivera said last month that consumers’ difficulties would likely extend into next year, as they continue to grapple with higher costs of living.

“With sentiment worsening, costs continuing to rise, the SNAP-related headwinds expected to intensify, we see these pressures as persisting beyond the fourth quarter, leading to a longer path to consumer recovery,” he said.

-Bill Peters

This content was created by MarketWatch, which is operated by Dow Jones & Co. MarketWatch is published independently from Dow Jones Newswires and The Wall Street Journal.

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  11-11-25 2221ET
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Oil prices rallied yesterday, with ICE Brent settling more than 1.4% higher on the day, moving back above $65/bbl. The recent strength in the oil market has been driven by refined products, with gasoline and gasoil cracks surging amid concerns about supply. Continued Ukrainian drone attacks on Russian refineries are a concern for the market, particularly middle distillates. Meanwhile, US sanctions on Lukoil and Rosneft, and what they mean for refining assets outside of Russia, is also a concern for broader product markets. While the outlook for oil is bearish, the strength in the refined products market is proving to be a significant obstacle.

There’s still plenty of uncertainty over Russian crude oil flows due to sanctions. Ship tracking data indicate that flows have slowed in recent weeks, with the 4-week average at its lowest level since mid-September. Additionally, data show a significant decline in volumes to China and India. Yet, there’s a significant share of Russian seaborne shipments for which the destination is currently unknown, and which could ultimately end up in India and/or China.

Today, OPEC will release its monthly oil market report, offering its outlook for the remainder of this year and into 2026. The Energy Information Administration will release its latest Short-Term Energy Outlook, which includes forecasts for US oil and gas supplies. And finally, the American Petroleum Institute will publish its weekly US crude and refined product inventory numbers. They were delayed by a public holiday in the US yesterday.

Thank you for the opportunity to speak to you today.¹ It is an honor and a pleasure to be here with you in Singapore, a crossroads for global trade and finance, to discuss the transformational nature of artificial intelligence (AI). Like other central banks around the world, including the Monetary Authority of Singapore, we at the Federal Reserve have been exploring the use of AI in our operations for quite some time as well as considering the implications of AI’s adoption for the financial sector and the broader economy.

At the Fed, we’ve been interested in the effects of AI on the economy and its role in the financial system for decades. Remarkably, in 1997, Governor Susan Phillips delivered a speech noting the use of AI in consumer loan underwriting.² In the past year, no fewer than seven speeches by Fed Governors have had “AI” in the title.

Today I’ll discuss the opportunities presented by AI relevant for central bankers as well as the risks it may pose that policymakers should consider. I will leave you with three main takeaways.

The State of AI Innovation and Deployment

My first main point is that while AI is a big deal that will transform economies, there are a range of outcomes for how it could do so.

AI—algorithms that mimic human thought, communication, and choices—has been with us for decades, but AI entered a new era with the launch of ChatGPT in late 2022. Generative AI (GenAI) captured our imagination with convincing conversations in which it is possible to go deep on a wide range of topics. Earlier forms of AI were often the bailiwick of digitally native companies, but GenAI is spreading rapidly through the economy. As of 2024, three in four large companies were using GenAI, though some report it has yet to improve their bottom line.³ Smaller companies have been slower to adopt GenAI, with adoption rates reported in the high single digits, albeit with a high degree of heterogeneity among sectors. Also, one could surmise, based on other surveys of individuals, that work-related use is more widespread among employees than their CEOs realize.⁴

A recent survey by the Federal Reserve Bank of New York showed that firms plan to retrain their workforces to take advantage of AI to enhance productivity, with widespread layoffs limited.⁵ But survey respondents also report that AI has led firms to scale back hiring, a development that may be contributing to the recent low levels of job creation in the U.S. economy, a concern for many workers and particularly for newer entrants to the job market.

Taking a step back, as I have noted in the past, I see two basic scenarios for how AI can transform the economy.⁶ In the first scenario, there is incremental adoption of GenAI that augments existing tasks and jobs. In the second scenario, a revolution occurs. GenAI transforms the nature of work and leisure, boosting the efficiency of research and development, remaking industries, and creating firms with new—perhaps radically new—business models.

Right now, it is difficult to predict which scenario (or perhaps one or more intermediate scenarios) will come to pass.

We can already see incremental change as GenAI is increasingly integrated with standard workplace software. With its natural language interface, GenAI is inherently user friendly, so few workers need special skills or unusually onerous training to use it. At the same time, some start-ups have a more revolutionary flavor because they are centered on AI from the outset. One indicator of how the labor market is evolving toward deeper integration with AI is the skills mentioned in job postings. While overall the share of job listings that mention AI-related skills is small—about 5 percent—in the information sector, it is about 20 percent. The financial sector, where firms are always looking for a technological edge, is not far behind, with 1 in 10 job postings mentioning AI.⁷ So we can see that the skills needed in some key sectors are already changing. The speed of that change is likely to increase. If the AI changes happen gradually, workers and firms will have time to adjust, but if they happen rapidly, there may be significant dislocations in the short term.

A massive wave of data center investment has begun, pointing to signs of confidence among leading AI companies that the use of AI at scale throughout the economy is just around the corner. If they’re right and AI is useful enough to keep what is currently projected to be $3 trillion of new data center capacity utilized effectively, we can expect significant changes in economies. Investment in capital generally raises labor productivity and offers the potential for higher output growth without pressure on inflation over the longer term. As I have discussed in previous remarks, if these changes are significant, they can also affect the conduct of monetary policy.⁸ Of course, it may be the case instead that investment exceeds short-term demand, in which case there may be losses and adjustments to the AI sector.

AI and the Financial Sector

The second key point I would like to make is that the financial sector is adopting AI quickly, and while there are many benefits to this adoption, the risks will need to be managed carefully.

So far, AI adoption in the financial sector appears to be most concentrated in areas that can enhance operational efficiency, including applications that involve text analysis, classification, and information search inside the firm, as well as customer-facing functions. These incremental improvements to common business functions are a key reason to be hopeful about AI raising labor productivity in that sector.

At the same time, there is significant investment in experimentation with AI for core functions for financial services. Data-driven financial-sector-specific tasks, including credit decision support, fraud detection, and trading are using AI-specific tools. Ensuring that AI is used appropriately for these functions faces appreciable challenges.

First, the amount of organizational change needed by financial services firms to utilize GenAI may be substantial. History suggests progress may be slow. Adoption of machine learning, an AI technology that preceded GenAI, was concentrated in firms that were highly digitized from their founding—and even in those cases, adoption was a long process.⁹ Fintech firms organized to exploit AI from their founding can play a key role in driving efficiency forward in the sector, providing services to the incumbent firms.¹⁰ But productivity may even decrease in the short term, as heavy investments in business-process improvements take time to play out to productivity gains.

A second challenge is the practical constraints of rushing into AI for core business activities in the financial sector, as firms need to ensure that the resulting processes and outcomes are consistent with relevant laws and appropriate risk management. Large institutions are exploring the use of GenAI, including agentic AI, in their financial models—but doing so requires care. To successfully leverage the potential of GenAI on a sustainable basis, decisions based on those models must be well controlled, numerically and legally precise, explainable, and replicable. AI developers still struggle to some extent with all of those criteria. We need to reduce the risk that AI reinforces biases in consumer lending. And we also need to guard against the risks that could result from the use of AI in financial markets. For example, profit maximization by AI-powered trading algorithms may result in tacit collusion, market manipulation, or trading strategies that result in significant market volatility or even systemic risk.¹¹

We will need innovation that is responsive to these risks to see additional advances in the use of AI for a broad array of core financial services functions.

AI and Central Banking

A third and final point I would like to leave you with is that central banks, including the Fed, need to keep up with AI by increasing our speed of adoption for our own operations.

The nature of central banking work is inherently careful, considered, and measured when evaluating anything new. This is particularly true for any new technologies.¹² But it seems clear already that the many advantages offered by AI could assist central banks in at least some of their operations, and the speed at which this technology is moving makes it appropriate to proactively engage in using AI for our own operations. That is why the Federal Reserve is using AI, where appropriate, to increase staff efficiency and effectiveness. My view is that GenAI is a transformative technology that central banks need to remain engaged with to ensure an ability to execute as technology evolves.

As we push ahead on efficiency gains, it is important that we leverage the right tools for the task at hand, recognizing that GenAI is not always the best choice. Some of the challenges that we face can be addressed by robotic process automation or traditional AI methods. These are the same kinds of questions that every business and organization considering AI should be weighing.

At the Federal Reserve, we have focused on ensuring we can leverage AI capabilities by establishing an AI program and governance framework for the use of AI technologies.¹³ We are taking an enterprise-wide approach of learning-by-doing and broadly adopting high-value uses of GenAI, such as writing, coding, and research activities. We have taken a “hands on keys” approach to having staff engage with it. We are identifying the business processes that can be improved and transformed with the technology.

One internal application of GenAI I am particularly excited about that helps us achieve all these goals is technology modernization. We are applying GenAI-enabled tools within clear guardrails to translate legacy code, generate unit tests, and accelerate cloud migration. So far, the result of this usage is faster delivery, improved quality, and enhanced developer experience. And it will likely mean better outcomes in support of the American people.

Given AI’s current and prospective role in economic activity, we are devoting the necessary resources to understanding it, including by analyzing not only AI’s economic and financial implications, but also exploring how AI can enhance our financial stability work, strengthen supervisory and regulatory capabilities, and ensure the smooth functioning of our payment systems.

These are just some of the ways that the Fed, like other organizations, is using AI to make us more productive and capable. These efforts may also help us understand the effect of AI on the economy, the banking system, and the payment system. That task will be a major job for central banks in the years ahead. AI has the potential to fundamentally change the economy and society. And as central bankers, we need to keep up.

Thank you.

1. The views expressed here are my own and are not necessarily those of my colleagues on the Federal Reserve Board or the Federal Open Market Committee. Return to text

2. See Susan M. Phillips (1997), “Risk Management,” speech delivered at the Asset/Liability and Treasury Management Conference of the Bank Administration Institute, Chicago, November 4. Return to text

3. See Aditya Challapally, Chris Pease, Ramesh Raskar, and Pradyumna Chari (2025), “The GenAI Divide: State of AI in Business 2025,” MIT NANDA Report, July, https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Business_2025_Report.pdf. There are a range additional surveys with various results; see, for example, Richard Horton, Jan Michalski, Stacey Winters, Douglas Gunn, and Jennifer Holland (2025), “AI ROI: The Paradox of Rising Investment and Elusive Returns,” October 22, https://www.deloitte.com/uk/en/issues/generative-ai/ai-roi-the-paradox-of-rising-investment-and-elusive-returns.html. Return to text

4. On adoption by large firms, see McKinsey & Company (2025), “The State of AI: Agents, Innovation, and Transformation,” November 5, https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai. On adoption by smaller firms, see the Business Trends and Outlook Survey from the U.S. Census Bureau, which is available on its website at https://www.census.gov/programs-surveys/btos.html. On adoption by individuals, see Alexander Bick, Adam Blandin, and David J. Deming (2024), “The Rapid Adoption of Generative AI,” Working Paper Series 32966 (Cambridge, Mass.: National Bureau of Economic Research, September; revised February 2025). Return to text

5. See Ben Hyman, Jaison R. Abel, Natalia Emanuel, Nick Montalbano, and Richard Deitz (2025), “Are Businesses Scaling Back Hiring Due to AI?” Federal Reserve Bank of New York, Liberty Street Economics (blog), September 4. Other surveys have shown similar results; see, for example, Jeremy Korst, Stefano Puntoni, and Prasanna Tambe (2025), “Accountable Acceleration: Gen AI Fast-Tracks Into the Enterprise (PDF),” 2025 Report, October 29. Return to text

6. See Michael S. Barr (2025), “Artificial Intelligence: Hypothetical Scenarios for the Future,” speech delivered at the Council on Foreign Relations, New York, February 18. Return to text

7. Job-posting statistics are based on the classification by Lightcast and are calculated using the methodology developed in Daron Acemoglu, David Autor, Jonathon Hazell, and Pascual Restrepo, “Artificial Intelligence and Jobs: Evidence from Online Vacancies,” Journal of Labor Economics, vol. 40 (April), pp. S293–340. Data are available by subscription from Lightcast at https://lightcast.io. Return to text

8. See Michael S. Barr (2025), “Artificial Intelligence and the Labor Market: A Scenario-Based Approach,” speech delivered at the Reykjavík Economic Conference 2025, Central Bank of Iceland, Reykjavík, Iceland, May 9. Return to text

9. See Timothy Bresnahan (2024), “What Innovation Paths for AI to Become a GPT?” Journal of Economics & Management Strategy, vol. 33 (Summer), pp. 305–16. Return to text

10. See Michael S. Barr (2025), “AI, Fintechs, and Banks,” speech delivered at the Federal Reserve Bank of San Francisco, San Francisco, April 4. Return to text

11. The most recent Financial Stability Report is available on the Federal Reserve Board’s website at https://www.federalreserve.gov/publications/files/financial-stability-report-20251107.pdf. Return to text

12. A report from the Bank of International Settlements notes that central bankers have the prospect of improving data quality, enhancing operations, and improving decisionmaking with the use of AI and provides a framework for considering questions of governance and risk management when doing so; see Bank of International Settlements (2025), “Governance of AI Adoption at Central Banks (PDF),” January. Return to text

13. See the “Board of Governors of the Federal Reserve System Compliance Plan for OMB Memorandum M-25-21,” which is available on the Federal Reserve’s website at https://www.federalreserve.gov/publications/compliance-plan-for-OMB-memorandum-m-25-21.htm. Return to text

Beginning on January 1, Lilly employees covered by the company’s medical plan will be automatically enrolled with pharmacy benefit coverage through pharmacy benefit manager Rightway, according to a document viewed by Bloomberg.

Sign up here.

CVS spokesperson David Whitrap told Reuters that while the company won’t comment on specific clients, Caremark’s overall client retention remains in the high 90% range year after year, adding that it offers options that covers both Zepbound and Wegovy, but “this option is costlier for plan sponsors than our standard commercial formulary that excludes Zepbound.”

“Our move earlier this year to negotiate Lilly and Novo against one another drove significant savings for our clients,” Whitrap added.

Eli Lilly and Rightway did not immediately respond to Reuters’ requests for comment. Reuters could not immediately verify the Bloomberg report.

Novo faces increasing competition from Lilly’s Zepbound and compounded copycat drugs in the weight-loss drug market.

Wegovy and Zepbound are the only highly effective GLP-1 weight-loss drugs sold mainly in the U.S. as weekly injections.

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There could be tug of war under the Christmas tree this year owing to the growing trend of adult toy collectors, a rundown of the season’s must-haves suggests.

Singing Wicked 2 dolls, manga-themed Lego, a Pokémon game and a mini-fridge playset are among the items on the annual DreamToys selection that experts say are as likely to feature on the wishlists of adults as children.

In recent years, the industry has been bolstered by the passions of “kidults” (buyers aged 12 and over) who spend their spare cash on expensive Lego sets and collectible figurines. This group is behind £1 in every £3 spent on toys in the UK.

Almost half of adults (43%) have bought a toy for themselves or another adult this year – a figure that rises to 76% among gen Z (aged 18 to 28) shoppers, according to figures from the data company Circana.

After several difficult years, encouragingly, data from January to the end of June showed that toys for children grew 6%, the strongest performance in years.

“It’s a double success story,” said Melissa Symonds, the UK toys director at Circana. “We’re seeing children rediscover the joy of play while adults are embracing it as a form of self-care, nostalgia and fandom. That combination is keeping the market vibrant and relevant.”

Given the recent strong run, gift retailers were feeling optimistic about the all-important Christmas period but there is now concern that tax rises in the autumn budget could hit spending.

However, Symonds argued the toy market was different: “Toys don’t always follow the general economic trends because they are part of the joy economy.”

Toys are also relatively affordable, she said. Last December, the average selling price for a toy was £13.43, with the £10-20 range accounting for a third of sales.

Paul Reader, the chair of the DreamToys selection panel at the Toy Retailers Association, said it had been an “incredible” year for the sector. “We are in seriously positive territory … and optimistic that the momentum is going to follow into Christmas.”

“There is a strong sense that we are going to have less disposable income coming out of the budget,” he said, adding that the list could help consumers “make informed decisions about what we believe are the best toys this Christmas”.

People were starting to think about how much they would spend and it was “too early” to tell what impact the budget would have. “The magic of Christmas is always going to be there and parents and grandparents all work hard to make sure it is enjoyable for the whole family,” said Reader.

The cheapest toy on the DreamToys list is a £13 Dress to Impress doll spun out of the hit fashion game on Roblox. The most expensive is a £120 Lego ship inspired by the Japanese anime series One Piece.

With the highly anticipated sequel out next week, there is expected to be feverish demand for all things Wicked including the £35 singing Elphaba and Glinda dolls that make the list.

Characters from film and TV loom large. There is a £30 interactive Evie Pig (baby sister to Peppa) and an £80 Stitch soft toy that has 100 sounds and reactions.

One of the most unusual entries is the £20 Fill the Fridge playset. However, it ticks two boxes: it taps into the viral “fridge restocking” trend as well as the popularity of collectibles that make up just over a fifth of all toys sold.

DreamToys list 2025

• Dress to Impress Mystery Model Dolls – £12.99

• Gui Gui Shimmer deluxe pack – £19.99

• Hot Wheels Racing F1 Grand Prix circuit – £79.99

• Human Controller – £34.99

• Jurassic World Primal Hatch T-Rex – £64.99

• Marshmallow Madness – £19.99

• Fill the Fridge playset – £19.99

• Monster Jam Smash & Bash Grave Digger – £49.99

• Lego One Piece: the Going Merry Pirate Ship – £119.99

• Peppa Pig Oinks & Snuggles Evie doll – £29.99

• Pokémon Trading Card: Mega Evolution Elite Trainer Box – £54.99

• Lego Speed Champions F1® racing cars – £22.99

• Sticki Rolls Sticki Rolluxe – £39.99

• Disney Ultimate Stitch interactive plush – £79.99

• Wicked: For Good singing dolls – £34.99

TOKYO, Japan ― Renesas Electronics Corporation (TSE: 6723), a premier supplier of advanced semiconductor solutions, today announced that it has delivered the industry’s first sixth-generation Registered Clock Driver (RCD) for DDR5 Registered Dual In-line Memory Modules (RDIMMs). The new RCD is the first to achieve a data rate of 9600 Mega Transfers Per Second (MT/s), surpassing the industry standard. This breakthrough marks a significant leap from the 8800 MT/s performance of Renesas’ Gen5 RCD, setting a new standard for memory interface performance in data center servers.

Key Features of Renesas’ Gen6 DDR5 RCD

• 10% Bandwidth Increase over Renesas’ Gen5 RCD (9600 MT/s versus 8800 MT/s)
• Backward Compatibility with Gen5 Platforms: Provides seamless upgrade path
• Enhanced Signal Integrity and Power Efficiency: Enables AI, HPC, and LLM workloads
• Expanded Decision Feedback Equalization Architecture: Offers eight taps and 1.5mV granularity for superior margin tuning
• Decision Engine Signal Telemetry and Margining (DESTM): Improved system-level diagnostics provides real-time signal quality indication, margin visibility, and diagnostic feedback for higher speeds

The new DDR5 RDIMMs are needed to keep pace with the ever-increasing memory bandwidth demands of Artificial Intelligence (AI), High-Performance Compute (HPC) and other data center applications. Renesas has been instrumental in the design, development and deployment of the new RDIMMs, collaborating with industry leaders including CPU and memory providers, along with end customers. Renesas is the leader in DDR5 RCDs, building on its legacy of signal integrity and power optimization expertise.

“Explosive growth of generative AI is fueling higher SoC core count. This is driving unprecedented demand for memory bandwidth and capacity as a critical enabler of data center performance,” said Sameer Kuppahalli, Vice President of Memory Interface Division at Renesas. “Our sixth generation DDR5 Registered Clock Driver demonstrates Renesas’ continued commitment to memory interface innovation, path-finding and delivering solutions to stay ahead of market demand.”

“Samsung has collaborated with Renesas across multiple generations of memory interface components, including the successful qualification of Gen5 DDR5 RCD and PMIC5030,” said Indong Kim, VP of DRAM Product Planning, Samsung Electronics. “We are now excited to integrate Gen6 RCD into our DDR5 DIMMs, across multiple SoC platforms to support the growing demands of AI, HPC, and other memory-intensive workloads.”

Availability

The RRG5006x Gen6 RCD is designed to meet the stringent requirements of next-generation server platforms, offering robust performance, reliability, and scalability. Renesas is sampling the new RRG5006x RCD to select customers today, including all major DRAM suppliers. Production availability is expected in the first half of 2027. More information about Renesas’ memory Interface solutions is available at www.renesas.com/ddr5. To request additional details about the new RCD, please send an email to [email protected].

Renesas at SC25

Renesas will showcase its memory interface solutions at the SC25 conference in St. Louis from November 16 through November 21 at booth #4101.

About Renesas Electronics Corporation

Renesas Electronics Corporation (TSE: 6723) empowers a safer, smarter and more sustainable future where technology helps make our lives easier. A leading global provider of microcontrollers, Renesas combines our expertise in embedded processing, analog, power and connectivity to deliver complete semiconductor solutions. These Winning Combinations accelerate time to market for automotive, industrial, infrastructure and IoT applications, enabling billions of connected, intelligent devices that enhance the way people work and live. Learn more at renesas.com. Follow us on LinkedIn, Facebook, X, YouTube, and Instagram.

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