ibl.ai Agentic AI Blog

Insights on building and deploying agentic AI systems. Our blog covers AI agent architectures, LLM infrastructure, MCP servers, enterprise deployment strategies, and real-world implementation guides. Whether you are a developer building AI agents, a CTO evaluating agentic platforms, or a technical leader driving AI adoption, you will find practical guidance here.

Topics We Cover

Featured Research and Reports

We analyze key research from leading institutions and labs including Google DeepMind, Anthropic, OpenAI, Meta AI, McKinsey, and the World Economic Forum. Our content includes detailed analysis of reports on AI agents, foundation models, and enterprise AI strategy.

For Technical Leaders

CTOs, engineering leads, and AI architects turn to our blog for guidance on agent orchestration, model evaluation, infrastructure planning, and building production-ready AI systems. We provide frameworks for responsible AI deployment that balance capability with safety and reliability.

Back to Blog

Deloitte: Tech Trends 2025

Jeremy WeaverDecember 13, 2024
Premium

Deloitte's Tech Trends 2025 report forecasts a future where AI seamlessly underpins all aspects of business and technology, influencing everything from hardware and cybersecurity to core system modernization.

Deloitte: Tech Trends 2025



Summary of Read Full Report (PDF)

This excerpt from Deloitte's 16th annual Tech Trends report, "Tech Trends 2025," forecasts the pervasive influence of artificial intelligence (AI) across various technological domains by 2025. The report structures its analysis around six macro forces: interaction, information, computation, business of technology, cyber and trust, and core modernization.

A key theme is the ubiquity of AI, becoming so integrated that it's largely invisible yet foundational to all aspects of business and personal life, impacting everything from hardware design and cybersecurity to core systems modernization and IT operations.

The report's purpose is to anticipate and analyze these trends, providing insights to help organizations strategically adapt to this AI-driven future.

Related Articles

SaaS Fragmentation Is the Hidden Cost of Enterprise AI

Enterprises run six or seven per-seat tools that each hold a partial copy of the same customer. That fragmentation, not model capability, is what stalls AI deployment — and it carries a per-seat bill that grows with headcount. This post itemizes the fragmentation tax and shows the MCP-based orchestration layer that reads across every system instead of adding another one.

Miguel AmigotJuly 31, 2026

AI Budgets Are Growing 40% a Year. Deployment Isn't.

Enterprise AI investment is compounding near 40% a year — roughly double cloud and mobile at the same stage — yet most of it never reaches production. This post introduces deployment yield, the ratio of AI budget attached to systems real users touch, and shows why the missing control plane, not model capability, is what security and compliance actually block on.

Miguel AmigotJuly 31, 2026

The AI Harness Thesis: Orchestration Beats Model Selection

Enterprises spend their AI strategy debating which model to buy. The model is the commodity — it is replaced every few months and its price falls. The harness around it (retrieval, validation, routing, memory) is the durable asset, and it only compounds if you own it.

ibl.ai EngineeringJuly 29, 2026

Self-Hosted Voice AI Agents for Hospital Health Systems

What it actually costs to run outbound voice AI agents on hospital-owned infrastructure, which BAAs you still need, and where PHI travels during an AI phone call.

ibl.ai EngineeringJuly 28, 2026

See the ibl.ai AI Operating System in Action

Discover how leading universities and organizations are transforming education with the ibl.ai AI Operating System. Explore real-world implementations from Harvard, MIT, Stanford, and users from 400+ institutions worldwide.

View Case Studies

Get Started with ibl.ai

Choose the plan that fits your needs and start transforming your educational experience today.