AI

What to watch in AGI during 2027: interactive benchmarks, long-horizon agents, automated AI R&D, continual learning, safety thresholds and definitions.

AGI progress in 2026 is being measured through interactive reasoning benchmarks, longer agent tasks and frontier safety thresholds rather than one universal test.

AGI could bring major scientific and economic benefits, but the risks are unusually high. Here is a grounded look at artificial general intelligence benefits, risks and limits entering 2027.

Businesses cannot buy a universally accepted AGI product entering 2027, but they can prepare for more capable AI. Here is what leaders should do now around data, permissions, governance, skills and frontier-risk monitoring.

There is no universally accepted AGI product for workers entering 2027, but frontier AI already changes knowledge work. Here is what current systems can do, what remains difficult and what AGI would change.

Ten capabilities a credible AGI would need to demonstrate, from transfer and unfamiliar-task learning to planning, correction and reliable performance.

How do researchers measure progress toward AGI? A guide to AGI levels, ARC-AGI-3, long-horizon task tests, benchmarks, autonomy and why no single score can prove general intelligence.

AGI vs today’s AI explained: the capabilities frontier models already have, the gaps that remain, and why artificial general intelligence is not simply a bigger chatbot.

AGI, narrow AI, generative AI and superintelligence are not interchangeable. This guide explains the differences and shows where today’s frontier systems fit.

Artificial general intelligence explained: what AGI means, how it differs from frontier AI, why no single test settles it and what evidence matters.