AI

AI is no longer a tool bolted onto business software; it's starting to run the workflow itself. Gartner forecasts that worldwide AI spending will reach $2.59 trillion in 2026, a 47% increase year-over-year, and a growing share of that spend is going toward AI agents: systems that plan, decide, and act across a business process with only as much human oversight as a company builds in. For operations, IT, and finance leaders, the question isn't whether to explore agents; it's how fast the rest of the market is already moving.

Identity and access management for AI agents governs what autonomous software can access, and it's fast becoming a significant blind spot in enterprise security. Businesses are deploying agents faster than they can govern them, and the identity layer is where that gap turns into real risk

AI Agents don't wait for instructions. They plan a task, decide the next step, and execute it inside your existing systems, then escalate only when something falls outside their scope. That shift, from responding to prompts to owning outcomes, is what separates an AI agent from a chatbot or a generic AI assistant.

Generative AI can do more than generate replies. When connected to business systems, it can help coordinate multi-step support tasks, retrieve information, summarize customer history, and trigger follow-up actions. This is where agentic workflow engineering becomes relevant, helping businesses design AI-powered workflows that can reason through tasks and coordinate actions across different systems.

Every enterprise buying AI right now is really asking one question, whether they realize it or not: are we purchasing a conversation, or a worker? Chatbots and AI agents get pitched under the same banner, but they are built to do fundamentally different jobs. Confusing the two is an expensive mistake to make at scale.

AI Automation is rewiring how manufacturers hit uptime, quality, and delivery targets and the plants that adopt it first are pulling away from the rest. The pressure to cut downtime, reduce waste, and outpace the next production cycle isn't coming; it's already here. Every quarter a manufacturer waits is a quarter a competitor spends closing the gap.

AI Trends Every Business Should Watch in 2026 start with one signal every leader needs to see clearly: the AI conversation has moved from experimentation to execution. Enterprises that treated 2025 as a pilot year are now under pressure to prove returns, govern their agents, and lock down where their data lives.

According to Gartner's 2025 enterprise AI forecast, 40% of enterprise applications will embed task-specific AI agents by the end of 2026, up from less than 5% in 2025 and many enterprise AI agents require a secure way to reach CRM, ERP, database, and SaaS systems that already run the business.

Businesses are under pressure to improve efficiency, control operating costs, and deliver faster customer experiences. Automation can support these goals, but choosing the wrong technology may create unnecessary complexity, maintenance work, and implementation costs.

Agentic Workflow Engineering enables AI agents to support multi-step business processes by planning, deciding, and acting across connected systems under defined permissions and human oversight.