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AI’s Economic Benefits Surpass Emissions Concerns According to IMF

The International Monetary Fund (IMF) has recently highlighted the potential economic benefits of artificial intelligence (AI), projecting a global output boost of approximately 0.5% per year from 2025 to 2030. This growth is expected to surpass the environmental costs associated with higher carbon emissions from AI-driven data centers.

The report, showcased at the IMF’s spring meeting, emphasizes the need for equitable distribution of these economic gains while managing the adverse effects on our climate. The forecast indicates that AI’s contribution to GDP growth will outweigh the financial impacts of emissions, though it points out the necessity for policymakers and businesses to mitigate societal costs.

Energy Demands and Environmental Footprint

AI is set to escalate global electricity demand, potentially reaching 1,500 terawatt-hours (TWh) by 2030, mirroring the energy consumption of countries like India today.

The increasing demand for data processing capacity could result in higher greenhouse gas emissions, but the AI industry aims to offset these with advancements in renewable energy technologies.

AI: A Driver for Energy Efficiency?

Analysts suggest that AI could potentially reduce carbon emissions through improved energy efficiency, fostering advancements in low-carbon technologies across sectors such as power, food, and transport. Grantham Research Institute stresses the significance of strategic action from governments and industries to facilitate this transition.

The role of AI in the global economy continues to evolve, stirring debates not only about its economic potential but also its environmental impact.

Retail’s AI Push Faces A Cybersecurity And Regulatory Reality Check

Artificial intelligence is becoming a strategic priority for retailers, with 80% of retail leaders planning to increase investment in the technology, according to EY’s latest CEO Outlook Survey. However, growing concerns over cybersecurity, customer privacy and regulation could complicate adoption across an industry already facing inflation, geopolitical uncertainty and changing consumer expectations.

Confidence In AI Comes With Risks

The survey found that 80% of retail leaders are confident in their ability to expand the responsible use of AI and customer data. Retailers are increasingly applying the technology to demand forecasting, inventory management, customer service and personalised marketing, seeking to improve efficiency and respond more quickly to market changes.

Yet adoption brings new vulnerabilities. EY found that 24% of retail leaders identified cybersecurity and data privacy as a leading business risk for the year ahead. Retailers manage sensitive customer information, payment systems and complex supply chains, making effective security and governance essential as AI becomes more deeply embedded in their operations.

The World Economic Forum’s Global Cybersecurity Outlook 2026 highlights the wider challenge: 87% of organisations reported rising cyber risks linked to AI vulnerabilities, while 94% expected malicious AI to have a significant impact on cybersecurity in 2026.

Regulation Will Shape AI Adoption

Regulatory frameworks are also influencing how quickly retailers can expand their use of AI. The European Union’s AI Act, China’s state-led governance model and measures introduced by individual US states are shaping the rules around the technology.

For retailers, compliance is becoming a strategic consideration, particularly for customer-facing applications that use personal data to personalise offers, automate interactions or analyse consumer behaviour. Regulatory missteps could carry significant costs in a sector where customer trust is critical.

EY Outlines Four Possible Futures

EY recommends that retailers plan for multiple outcomes rather than assume the current investment boom will continue uninterrupted. Its analysis draws on a four-scenario framework developed by Jim Dator of the University of Hawaii.

One scenario envisages constrained AI adoption as economic pressures, regulation, cyberattacks, legacy systems and poor data quality limit progress. Retailers in this environment may prioritise lower-risk back-office applications, such as finance, procurement, inventory and logistics, while customer-facing tools face resistance.

A second scenario anticipates continued growth, with sustained investment and widespread adoption. A third envisages deeper economic and social transformation as technology reshapes business operations. The fourth considers systemic breakdown, in which a small number of technology platforms control access to AI models and charge premium prices, potentially making advanced capabilities less accessible even to large retailers.

Governance Will Determine Competitive Advantage

EY’s findings suggest that investment alone will not determine which retailers benefit most from AI. Companies will also need robust cybersecurity, effective governance and strategies that can adapt to different economic, technological and regulatory conditions.

For a sector operating on tight margins, the challenge is to turn AI investment into lasting business value while managing the risks that come with greater dependence on the technology.

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