Keep pulling the thread on Gartner.
AI-native development platforms are expected to enable a 10-person development team to be restructured into five smaller teams of two developers partnered with AI, increasing project output fivefold.
The advancement of multi-agent systems is expected to drive the creation of cross-platform standards, such as model context protocols and agent-to-agent protocols, potentially leading to an 'internet of agents'.
Gartner's 2026 strategic trends forecast contains no trends with a maturity horizon beyond five years, a change attributed to accelerated investment in AI.
AI-native development platforms will facilitate the inclusion of non-technical business users in development teams for creating custom applications.
Biotechnology companies are utilizing AI supercomputing platforms to accelerate the modeling of vaccines and therapies, reducing timelines from years to weeks.
Financial services firms are employing AI supercomputing platforms to model risk portfolios and enhance their portfolio management processes.
Energy companies are leveraging AI supercomputing platforms to model extreme weather events for the purpose of optimizing grid performance and reliability.
Building multi-agent systems with small, specialized agents, rather than large monolithic ones, reduces hallucinations and improves support for complex workflows.
More than 50,000 clinical studies were produced in the last year.
Organizations implementing domain-specific large language models will need to establish new roles, including 'context engineer' for data curation and 'machine learning specialist' to prevent 'catastrophic forgetting'.
Energy companies are deploying drones equipped with physical AI to distinguish between power lines and tree branches for automated vegetation management.
Approximately 80% of the current cybersecurity market is comprised of tools that are reactive, rather than proactive.