Core AI will soon be embedded in core business platforms, making complex custom projects redundant and shifting ICT strategy focus to vendor roadmaps.
StarCoder2, an open-access code LLM, offers customisation for enterprise development, but requires governance for DevOps integration.
Lately, the big questions for CIOs have revolved around strategic ICT challenges, ensuring proper governance and maximum value from IT investments. The key trend is artificial intelligence (AI), with senior leaders keen to understand the AI landscape, including practical uses for generative AI, to guide investment decisions and ensure the new tools align with established principles
CustomGPT.ai’s new visual processing allows AI agents to incorporate images (diagrams, screenshots) as visual citations into responses, leveraging existing multimodal large language model (LLM) technology.
Oracle streamlines OCI and embeds AI across all products, enabling hybrid cloud options and unlocking data-driven business intelligence for users.
Google Cloud’s Gemini Enterprise elevates existing Gemini capabilities, moving beyond basic prompt-based AI to focus on agentic AI for measurable business value. This shift is Google’s strategy to monetise AI by enabling semi-autonomous services that directly leverage business data, overcoming initial market resistance to proving productivity gains from simple AI adoption
Salesforce’s Agentforce signals conversational AI is the ‘final mile’ in IT support automation, freeing up human staff for complex work.
Model context protocol (MCP) is a vital standard enabling AI agents to automate tasks in core enterprise systems, but requires immediate, strong governance for safe adoption.
End-user testing is crucial; it guarantees new systems truly meet user needs, enabling a smoother operational handover via service desk and project team collaboration.
