Consumers expecting smartphone, laptop, tablet, and gaming device prices to drop may have to wait much longer. The main reason behind the rising costs is the increasing price of memory components, driven largely by the explosive growth of artificial intelligence infrastructure. The huge demand for DRAM and NAND memory from AI data centres has created supply pressure, pushing up costs across the consumer electronics industry for more than a year.

Earlier estimates suggested that prices could begin improving by 2027, but recent developments indicate that the situation may remain challenging for several more years. Memory manufacturers appear to be preparing for a prolonged period of high demand, which could keep prices elevated well into the end of the decade.

Micron Technology, one of the world’s largest memory chip makers, recently revealed that it had signed 16 major supply agreements with customers across data centres, consumer electronics, and automotive industries. Most of these deals will run from 2026 through 2030 and follow take-or-pay contracts, meaning customers commit to buying certain quantities of DRAM and NAND at agreed price ranges. Micron said these agreements could help maintain stronger profit margins than it has achieved in previous memory cycles.

The current shortage began gaining momentum in 2024 when AI investment accelerated globally. Data centres running advanced AI models started consuming massive amounts of high-bandwidth memory (HBM), a specialised form of DRAM. Companies such as Samsung and SK Hynix shifted more production capacity toward HBM because it offers higher returns compared with traditional memory products.

This shift affected the supply of memory used in everyday consumer devices. Smartphone manufacturers rely on LPDDR memory, laptops and PCs require DDR5, and most electronics depend on NAND storage. With more production focused on AI-related demand, regular consumer products began facing higher component costs.

By 2026, the impact had become visible in the market. Indian smartphone company Lava told Business Standard that memory, which previously accounted for around 15 to 20 percent of a phone’s total manufacturing cost, had grown to nearly match the cost of all other components combined. Smartphone brands including OnePlus, Vivo, Samsung, and Nothing responded by adjusting prices across different product segments. Apple also began feeling the pressure. Several Mac Studio, Mac mini, and MacBook models became harder to find in India, especially higher-memory versions, with some facing extended delivery timelines. The situation became more serious when Apple CEO Tim Cook acknowledged that rising costs were becoming difficult to absorb. Cook said the company had tried to protect customers from price increases but had reached a point where passing on some costs had become unavoidable.

Following this, Apple increased prices for several products, including iPads, Macs, MacBooks, and Home devices. In India, some premium MacBook Pro models saw significant price increases, while the entry-level iPad also became more expensive. Microsoft also announced higher prices for Xbox consoles, blaming a sharp rise in memory and storage costs.

Apple’s decision is important because the company is one of the biggest buyers of smartphone memory globally. With its enormous purchasing power and strong supplier relationships, Apple usually has the ability to negotiate better prices. Therefore, when Apple itself starts transferring higher costs to customers, it indicates that the broader industry is facing serious pressure.

Smaller brands are experiencing similar challenges. Nothing co-founder Akis Evangelidis reacted to reports of Apple’s price increases by saying, “Even Apple.” The company had already decided not to introduce a budget CMF phone model because pricing conditions made it difficult to justify, while existing products also saw price adjustments. To reduce costs, some electronics companies started using older memory technologies such as DDR2 and DDR3. However, even these older components began becoming more expensive as demand spread throughout the market. The temporary solution did not solve the larger supply problem.

The biggest concern now is that this pressure could continue until 2030. Microsoft recently indicated that memory and storage costs for consoles had increased significantly and warned that prices could rise further in the coming years. Micron’s long-term agreements also suggest that supply constraints for DRAM and NAND may continue beyond 2027.

The transition to newer technologies such as DDR6 and future generations of HBM is another factor driving costs higher. Although production capacity may improve over time, the cost of advanced memory technology is expected to keep increasing. Industry analysts believe this memory cycle is different from previous ones because AI is permanently changing how manufacturing capacity is allocated. IDC’s Singh explained that memory has traditionally followed a repeating cycle, but the current situation is different because a large portion of capacity is being redirected toward AI infrastructure.

While smartphone prices may eventually stabilise as consumers adjust to the new reality, other electronics categories could face longer-term pressure. People may start using laptops, tablets, and gaming devices for longer periods instead of upgrading frequently. The result is that the era of constantly falling electronics prices may be coming to an end. AI-driven demand and memory shortages could reshape the consumer technology market, keeping device prices higher for years to come.
Disclaimer: This image is taken from Business Standard.

Artificial intelligence is significantly boosting productivity at Deutsche Bank, with work that previously required years now being completed in just a few months, according to a senior executive. Denis Roux, Chief Information Officer for the investment bank at Deutsche Bank, said on the sidelines of the company’s Bank on Tech event in Bengaluru that AI is helping speed up technology initiatives and reduce long-standing internal backlogs. However, he noted that the bank is also closely monitoring the rising cost of computing resources.

Roux explained that timelines have shortened dramatically, with projects that earlier took around two years now being delivered in three to six months. He added that internal backlogs that once took months are now being cleared within weeks, emphasizing the goal of using AI tools to improve efficiency, though he did not provide specific figures on the impact.

Deutsche Bank has around 9,000 technology employees in India, which makes up about 45% of its global tech workforce. The bank, like many multinational firms, is increasingly relying on its Indian operations for higher-value functions such as software development, finance, and research work.

At the same time, Roux highlighted that managing AI-related costs is becoming important as providers shift toward usage-based pricing models. Companies like Anthropic and OpenAI are moving to token-based billing, where customers are charged based on how much they use the service. At Deutsche Bank, engineers are given token usage limits but can request more capacity if they can justify the business value, with insights shared across teams. The bank tracks usage patterns carefully to balance efficiency and cost control.

Deutsche Bank is also building AI systems to automate tasks like financial data extraction and analysis, as well as tools that connect external events—such as geopolitical or market changes—to portfolio exposure. Roux added that the bank is still cautious, using simpler AI models for routine tasks and evaluating where traditional methods may still be more effective.
Disclaimer: This image is taken from Reuters.

Known primarily for its AI-powered image generation platform, Midjourney Inc. has unveiled a surprising new direction: healthcare technology. During a recent event in San Francisco, the company introduced its first major hardware initiative, a device called the Midjourney Scanner, designed to perform full-body ultrasound imaging.

Speaking at the event, CEO David Holz described the scanner as a groundbreaking innovation, claiming that nothing comparable currently exists. He suggested the technology could offer several advantages over traditional MRI scans and outlined an ambitious plan to deploy approximately 50,000 units in the future. Holz emphasized that the project is currently driven by advanced engineering rather than artificial intelligence. According to him, the scanner relies on sophisticated hardware and software systems, with AI integration potentially coming later.

The company also revealed a unique business model for the technology. Instead of placing the scanners in conventional medical facilities, Midjourney plans to install them in specialized wellness centers called Midjourney Spas. Users will undergo scans while partially immersed in water. The first location, planned for San Francisco, is expected to occupy around 25,000 square feet and include wellness amenities such as hot tubs, saunas, cold-plunge pools, and a fitness center.

The scanner represents just one part of Midjourney's broader innovation roadmap. The company is currently working on eight separate projects, evenly divided between hardware and software. Holz indicated that at least two of the hardware initiatives could reach the market relatively soon. When discussing regulatory considerations, he acknowledged that medical approvals will be an important part of the process. The company intends to begin with simpler, easier-to-approve capabilities before gradually expanding the scanner's medical functions. Over time, Holz envisions the technology evolving beyond imaging into areas that could potentially support therapeutic applications as well.

Before this announcement, Midjourney had built its reputation largely on generative AI tools that allow users to create images and videos through subscription plans ranging from budget-friendly options to premium tiers. The company has also been involved in ongoing legal disputes with major entertainment firms, including Warner Bros. Discovery and The Walt Disney Company. The lawsuits center on allegations that Midjourney's AI-generated content incorporates copyrighted characters and intellectual property without authorization. With its unexpected entry into health technology, Midjourney is signaling ambitions that extend far beyond generative AI, potentially positioning itself as a player in both the wellness and medical-device industries in the years ahead.

Disclaimer: This image is taken from Midjourney.

Morgan Stanley expects that global debt issuance linked to AI companies will exceed $500 billion in 2026, driven by aggressive capital expenditure plans from major hyperscalers such as Amazon, Google, and Meta. The bank projects this issuance could rise to around $570 billion as AI firms increasingly turn to alternative funding sources to support expansion.

Recent large-scale financing efforts underline this trend. Alphabet, the parent of Google, recently launched an $85 billion fundraising plan aimed at expanding AI infrastructure such as data centres and computing facilities, and earlier issued a rare 100-year bond to support its AI investments. According to estimates cited by Reuters, AI-related global debt issuance had already reached nearly $236 billion by the end of May 2026, marking a fourfold increase from the previous year.

Strong demand for advanced AI models and the rapid development of agentic AI systems have also prompted companies like Anthropic and OpenAI to scale up spending significantly, with both reportedly preparing for potential public market listings. Their valuations are estimated at about $965 billion and $852 billion respectively.

The heavy computing requirements needed to train and deploy these models are pushing hyperscalers to expand data centre capacity and increase capital spending, with Morgan Stanley forecasting hyperscaler capex could exceed $1 trillion by 2027. It also notes that these firms are diversifying funding sources, including issuing more non-US dollar debt. Amazon recently raised C$14 billion through Canadian dollar-denominated notes and also secured €14.5 billion in one of the largest euro corporate bond deals, highlighting how hyperscalers are tapping global debt markets to finance large-scale AI infrastructure expansion.
Disclaimer: This image is taken from ANI.

As AI continues to evolve, cyber risks are becoming a major business challenge rather than just a technical problem. The Five Eyes alliance warns that advanced AI models could transform the cyber threat landscape faster than anticipated. With AI being used for both attacks and defense, the question remains: who is ahead in this new automated cyber battle? Andrea Heng and Hairianto Diman explore this with Jayant Dave, Chief Information Security Officer at Check Point Software Technologies.

Disclaimer: This podcast is taken from CNA.

A prolonged and heated courtroom dispute between tech billionaires Elon Musk and Sam Altman has ended in a win for OpenAI’s CEO. Musk says he plans to challenge the decision. The case has raised wider questions about Big Tech influence and the worldwide competition in artificial intelligence. Lucy Hough discusses the outcome with Guardian US tech and power reporter Nick Robins-Early in a YouTube interview.
Disclaimer: This image is taken from The Guardian.

This discussion reviews the 32 final recommendations from Singapore’s Economic Strategy Review aimed at safeguarding workers from AI-driven disruption through measures like career transition pathways and earlier retrenchment assistance. Andrea Heng and Elakeyaa Selvaraji explore how these proposals seek to raise wages in people-focused sectors such as healthcare and education, while building a more proactive system for lifelong learning, featuring insights from Desmond Choo, Minister of State, MINDEF and Deputy Secretary-General of NTUC.

Disclaimer: This podcast is taken from CNA.

In Singapore, bots account for about 58 percent of total internet traffic, with over half classified as malicious. As AI-powered bots become more advanced and harder to distinguish from real users, organizations now face the challenge of not just detecting bots but also interpreting their intent. With AI increasingly blurring the boundary between human and automated activity, businesses are under pressure to adapt. Andrea Heng and Hairianto Diman discuss the implications for online security, trust, and the internet’s future with Garen Ling, Area Vice President of Sales, ASEAN, App Security and Data Security at Thales.
Disclaimer: This podcast is taken from CNA.