What are the five pros and cons of artificial intelligence?

Artificial intelligence has moved from research labs into everyday tools that can generate text and images, write code and carry out data-heavy analyses. Supporters point to measurable gains: a UK government report says almost one billion people use AI, and the Bank for International Settlements found in September 2025 that generative AI delivered productivity improvements of between 10 and 65 percent for some tasks, with time savings of roughly 20 to 50 percent. Companies such as Wipro report that AI deployment has freed capacity roughly equal to 20,000 employees.

Beyond immediate time savings, AI is creating demand for new skills and roles. Employers increasingly seek machine-learning programmers, chatbot developers and engineers comfortable integrating AI into workflows; software developers are using AI to draft code that they then validate and debug. Wipro, for example, is training over 100,000 staff as it adopts a "human-AI" operating model, illustrating how firms are reskilling workforces around these tools.

At the same time, the technology poses clear risks to employment and job quality. The 2026 International AI Safety Report estimates that some 60 percent of jobs in advanced economies and 40 percent in emerging economies could be vulnerable depending on adoption patterns. Large tech employers have already shifted head counts as they invest in automation—Amazon announced cuts of 16,000 roles and Pinterest cut about 780—while researchers note early-career workers in AI-exposed occupations may face greater difficulty entering the labour market.

Generative AI’s ability to produce convincing text, images and synthetic voices also opens avenues for misuse. Deepfakes have been deployed to impersonate senior officials and executives and to execute scams and cyberattacks, with criminals leveraging synthetic audio and video to extract sensitive information or authorize fraudulent transactions. These abuses contribute to concerns about misinformation and security.

Infrastructure and environmental costs add another layer of trade-offs. Large AI models run in energy- and water-intensive data centres that require powerful chips and extensive cooling. Proposed projects have raised local and national debates: one suggested data centre in Utah would consume more electricity than the entire state if built, and a proposed $1 billion facility in Kenya involving Microsoft and G42 prompted warnings from President William Ruto about extra power needs. Public opposition is notable—71 percent of Americans told Gallup in March they opposed establishing AI data centres in their areas—while researchers and industry voices such as Anthropic’s CEO Dario Amodei have urged slowing capability growth so regulation and safeguards can catch up.