E-Business
IDC Predicts Artificial Intelligence to Contribute $19.9 Trillion to the Global Economy through 2030

New research from IDC entitled, The Global Impact of Artificial Intelligence on the Economy and Jobs, predicts that business spending to adopt artificial intelligence (AI), to use AI in existing business operations, and to deliver better products/services to business and consumer customers will have a cumulative global economic impact of $19.9 trillion through 2030 and drive 3.5% of global GDP in 2030.

As a result, AI will affect jobs across every region of the world, impacting industries like contact center operations, translation, accounting, and machinery inspection. Helping to trigger this shift are business leaders who almost unanimously, 98%, view AI as a priority for their organizations.
AI’s Net Positive Global Economic Impact
According to the research, in 2030, every new dollar spent on business-related AI solutions and services will generate $4.60 into the global economy, in terms of indirect and induced effects. This is determined by:
- Increased spending on AI solutions and services driven by accelerated AI adoption
- Economic stimulus among AI adopters, seeing benefits in terms of increased production and new revenue streams
- Impact along the whole AI providers supply chain, increasing revenue for the providers of essential supplies to AI solutions and services providers
“In 2024, AI entered a phase of accelerated development and deployment defined by widespread integration that’s led to a surge in enterprise investments aimed at significantly optimizing operational costs and timelines,” said Lapo Fioretti, Senior Research Analyst, Emerging Technologies and Macroeconomics, IDC. “By automating routine tasks and unlocking new efficiencies, AI will have profound economic consequences, reshaping industries, creating new markets, and altering the competitive landscape.”
Impact on Employment — New Roles Emerge While Others Remain Resilient
The majority of respondents to IDC’s Future of Work Employees Survey expect some (48%) or most (15%) parts of their work to be automated by AI and other tech over the next two years, while only a minority (3%) of employees expect their jobs to be fully automated by AI.
While some work will be negatively impacted by the proliferation of AI, new positions such as AI Ethics Specialists and AI Prompt Engineers will emerge as dedicated roles within global organizations.
The research further indicates that a ‘human touch intensity,’ combined with the level of ‘task repetitiveness’ by which each job is characterized, will inform organizations about roles that are subject to a full AI and automation replacement, versus those where tech’s role will be to augment human capabilities. As such, positions where human social and emotional capabilities are critical, such as nursing and roles where decision-making encompasses ethics and comprehension beyond numbers will remain robust.
“Understandably, we’re all curious to know if AI will replace our jobs,” said Rick Villars, Group Vice President, Worldwide Research, IDC. “As a CEO interviewed by IDC’s Andrea Siviero said, ‘Based on this research it’s clear that we should be asking ourselves how our jobs can be made easier and better by AI. AI will not replace your job but someone who knows how to use AI better than you will.’”
Research Methodology
To estimate the overall economic impact of a technology or a service, IDC developed an economic impact methodology that combines IDC knowledge of the market and internal data with a standard analytical framework, known as an Economic Impact Analysis.
It leverages an input-output (I/O) framework, using the most updated input-output official tables of a specific economy: through I/O tables, specific multipliers are determined and applied to the specific technologies to calculate the related effect.
This IDC Economic Impact Analysis evaluates three types of impact on the economy. In this AI-specific model, these are:
Direct Effect — Includes revenues from artificial intelligence business solutions/services providers directly selling their products to end users.
Indirect Effect — Refers to the economic impact related to the AI supply chain and AI adopters’ benefits. It includes the effects that organizations/tech providers have on the region or country due to their operations related to AI provision.
Backward indirect effects refer to the economic effects on supply chains and industries that provide inputs to AI-driven sectors — in other words, revenues generated in local industries impacted by AI.
Forward indirect effects refer to the effects on AI adopters, excluding consumers, that benefit from the adoption of AI technology, in terms of productivity, revenue growth, and other business parameters.
Induced Effect — These are effects induced by the increase in production. It refers to the impact, due to economic stimulus, from an increase in household income, including existing and new employees linked to the AI value chain across direct and indirect effects layers. People will spend part of their wages in the economy, thus generating additional economic impact.
“The importance of economic impact models is increasing. This type of analysis can be of importance for any vendor who wants to understand the impact of its specific products or services in a short or medium-term period.
“It helps not only businesses but also governments and other stakeholders make informed decisions by evaluating the potential benefits of a technology investment, for example, to the economy,” said Carla La Croce, Research Manager, Data and Analytics, IDC.
The IDC report, The Global Impact of Artificial Intelligence on the Economy and Jobs: AI will Steer 3.5% of GDP in 2030 (Doc #US51057924), assesses the impact of artificial intelligence in terms of economic output and employment.
This assessment leverages IDC’s knowledge of the market and internal data, as well as IDC’s Economic Impact model, which considers the direct, indirect, and induced effects of AI in the economy.
“The study delves into the global impact of AI on the economy, diving deep into specific regions, technology layers, and industries. The goal is to assess AI’s cumulative contributions to the economy with respect to the forecast global GDP in 2030.
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E-Business
What the Retail and E-commerce Sector Should Expect in 2026 in Era of AI-driven Shopping and Privacy

In 2025, the retail and e-commerce sector continued to face intense pressure from cybercriminals. According to Kaspersky data, 14,41%* of users in the global retail sector encountered web-based threats, while 22,20% were affected by on-device attacks.

Ransomware remains a serious concern for the industry. Last year, 8,25% of retail and e-commerce companies experienced ransomware incidents, and the number of unique B2B users in the sector affected by ransomware detections rose by 152% compared to 2023, signalling a sharp escalation in targeted attacks.
Phishing also continues to be a major threat vector. Kaspersky identified 6.7 million phishing attacks targeting users of online stores, delivery services, and payment systems in 2025. More than half of these attacks (50,58%) were aimed specifically at online stores, underscoring cybercriminals’ focus on e-commerce platforms as high-value targets for fraud and data theft.
A look at 2025 cybersecurity for retail & e-commerce: Trends and what happened
A stealer with a taste for pizza delivery. Shopping and food ordering via mobile apps are routine user behaviours. However, 2025 demonstrated that even downloading a seemingly legitimate app from an official app store does not guarantee safety, nor does it ensure that user data and financial credentials will not be compromised.
Ransomware detections in the B2B sector increased due to a single dominant actor. The number of unique users in the Retail & E-commerce sector who encountered ransomware detections increased by 152% in 2025 compared to 2023 (Nov 2024 – Oct 2025 vs. Nov 2022 – Oct 2023).
The most significant growth occurred during the 2024-2025 period and is largely attributable to the rapid spread of the Trojan-Ransom.Win32. Dcryptor family, which became highly prevalent across the retail and e-commerce sector in some of the analysed markets. This malware is a trojanised ransomware variant that leverages the legitimate DiskCryptor utility to encrypt disk partitions on victim systems.
Phishing activity in the online retail segment stood out. Despite being a long-established attack technique, phishing remains highly prevalent in the context of online purchasing.
From November 2024 through to October 2025, Kaspersky products blocked 6,651,955 attempts to access phishing links targeting users of online stores, payment systems, and delivery services. Of these attempts, 50.58% targeted online shoppers, 27.3% impersonated payment systems, and 22.12% targeted users of delivery companies.
Sales seasons continue to do the work for attackers. Seasonal peaks in online shopping consistently provide attackers with predictable opportunities to scale user-focused attacks.
Periods of heightened promotional activity lower user vigilance and allow familiar phishing and spam scenarios to blend into legitimate marketing traffic, increasing their overall effectiveness.
Predictions: What retail & e-commerce cybersecurity might face in 2026
Chatbots are likely to become a common product discovery tool across online marketplaces. Unlike traditional search, conversational interfaces encourage users to share more detailed, natural-language requests, revealing preferences, constraints, and contextual information.
This shift expands the privacy attack surface, as platforms accumulate richer user profiles through chat interactions. As a result, chatbot logs may become as sensitive as transactional data, increasing the risks of over-collection, misuse, or exposure of personal information.
“Search itself is changing, including how people look for products online. In 2025, there was a gradual shift from simple keyword queries to more conversational and visual ways of finding what to buy. As these models rely on broader user input, careful handling of the data involved will remain an important consideration for maintaining user trust,” comments Anna Larkina, Web data and privacy analysis expert at Kaspersky.
Changes in taxes and trade rules might be exploited in online fraud. Modifications in taxes, import duties, and cross-border trade rules are likely to be used as lures in phishing campaigns and fraudulent online stores, promoting unrealistically cheap offers or claims of avoided fees.
As pricing and fee rules continue to evolve across markets, it may lower vigilance, increasing the effectiveness of such schemes, particularly against small and mid-sized retailers.
AI-powered shopping assistants are expected to increasingly operate outside retail platforms, embedding themselves into browsers, mobile apps, and third-party services. While designed to simplify navigation and price discovery, these tools shift data collection beyond the retailer’s perimeter, creating new and less visible privacy risks.
To function effectively, external AI shopping agents require continuous access to user behaviour, including browsing activity, search intent, location context and product interactions across multiple sites.
This enables the aggregation of detailed behavioural profiles outside the direct control of both users and retail platforms, increasing the risks of over-collection, opaque data usage, and unintended exposure.
Image-based product search might become a new challenge in privacy risks. Previously, the main privacy concern around user images in e-commerce was limited to photos voluntarily shared in product reviews.
However, image-based product search is expected to make photo uploads a routine part of the shopping experience across major retail platforms. While this feature improves product discovery, it also increases the risk of unintended exposure of personal data.
User-submitted images may contain faces, home environments, or sensitive details, such as names, phone numbers, or addresses visible on shipping labels or packaging, making secure processing, data minimisation, and limited retention critical requirements for retailers.
E-Business
Elon Musk Seeks $134Bn from OpenAI, Microsoft for ‘Wrongful Gains’

Elon Musk, billionaire Tesla owner, has asked a United States (US) federal court to award him up to $134 billion in damages from OpenAI and Microsoft, stating that the companies earned “wrongful gains” from his early support of the artificial intelligence startup.

Elon Musk,
This is according to a court filing, reported by Reuters.
In filings ahead of a trial expected to start in April in Oakland, California, Musk stated that OpenAI benefited between $65.5 billion and $109.4 billion from his contributions when he helped co-found the organisation in 2015, and Microsoft gained between $13.3 billion and $25.1 billion through its involvement.
He has asked a United States (US) federal court to award him up to $134 billion in damages from OpenAI and Microsoft, stating that the companies earned “wrongful gains” from his early support of the artificial intelligence startup.
This is according to a court filing, reported by Reuters.
In filings ahead of a trial expected to start in April in Oakland, California, Musk stated that OpenAI benefited between $65.5 billion and $109.4 billion from his contributions when he helped co-found the organisation in 2015, and Microsoft gained between $13.3 billion and $25.1 billion through its involvement.
Musk’s legal team argues that his early financial and strategic contributions, including approximately $38 million in seed funding, the recruitment of key personnel, and assistance in connecting founders with contacts, laid the foundation for the later success of OpenAI and Microsoft’s commercial AI efforts.
“Without Elon Musk, there’d be no OpenAI. He provided the bulk of the seed funding, lent his reputation, and taught them all he knew about scaling a business. A pre-eminent expert quantified the value of that,” Musk’s lead trial lawyer Steven Molo told Reuters.
“Just as an early investor in a startup company may realise gains many orders of magnitude greater than the investor’s initial investment, the wrongful gains that OpenAI and Microsoft have earned—and which Mr Musk is now entitled to disgorge—are much larger than Mr Musk’s initial contributions,” the filing said.
Musk, who left OpenAI’s board in 2018 and now leads AI company xAI, alleges that OpenAI violated its founding non-profit mission when it restructured to include a for-profit arm tied to Microsoft’s investment and commercial strategy.
Meanwhile, OpenAI has labelled the lawsuit “baseless” and part of a “harassment campaign” by Musk, and Microsoft’s legal team has said there is no evidence the company “aided and abetted” OpenAI in any wrongdoing.
Both companies have asked the judge to limit what Musk’s expert witness may present at trial, arguing that the damages calculations are unreliable and could mislead a jury.
According to Reuters, Musk’s filing says he may pursue punitive damages and other penalties, including a possible injunction, if the jury finds the companies liable, though it did not specify what form any injunction would take.
E-Business
Nigeria Targeted with 4,622 Cyber-attacks Per Week in December 2025

In December 2025, organisations globally faced sustained cyber pressure, as the average number of cyber-attacks per organisation per week reached 2 027, a 1% increase from the previous month and a 9% increase from December 2024.

This is according to December 2025 Global Cyber Attack Statistics by Check Point Research, the threat intelligence arm of Check Point Software Technologies.
According to the statistics, Latin America was the hardest hit, with companies experiencing an average of 3 065 cyber-attacks per week, a 26% year-over-year increase.
In contrast, Africa saw a decline in attacks, with Nigeria (4 622 attacks per week) and Angola (4 002 attacks per week) being the most targeted countries on the continent.
The report’s findings highlight the evolving cyber threat landscape, with ransomware and GenAI-driven data risks posing significant challenges to companies worldwide.
Ransomware attacks jumped 60% year over year, with 945 publicly reported incidents in December. Qilin was the most active ransomware operator, responsible for 18% of publicly disclosed attacks.
“Ransomware continues to scale through industrialised operations, while unmanaged GenAI usage is creating widespread data exposure at enterprise level,” said Omer Dembinsky, data research manager at Check Point Research.
The report noted the education sector was the most targeted industry globally, with 4 349 cyber attacks per week; followed by government (2 666 attacks per week); and associations and non-profits (2 509 attacks per week).
The widespread adoption of GenAI tools has introduced new cyber security risks, with one in 27 GenAI prompts posing a high risk of sensitive data leakage.
Experts warn that companies must prioritise prevention-first security, real-time AI threat intelligence and strong governance over AI tools to mitigate these risks.
Hendrik de Bruin, head of security consulting at Check Point Software, added: “Strengthening ransomware resilience, deploying AI-powered prevention and enforcing clear GenAI governance will be critical to reducing cyber risk in the year ahead.”
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