Agentic AI in Applications – When Software Starts Acting on Its Own

Agentic AI in Applications – When Software Starts Acting on Its Own

From chatbots to agents

Not long ago, AI in applications mostly meant chatbots and product recommendations. Today, a new trend is emerging – Agentic AI. These are systems that don’t just respond to user commands but take initiative and perform tasks autonomously.

Example: instead of asking an AI assistant for cheap flights, an agent continuously monitors prices, compares options, and books the best deal according to your preferences.

How does Agentic AI work?

Agentic AI combines several elements:

• Large Language Models (LLMs) – understanding natural language, context, and intent,
• tools and APIs – enabling the agent to take real actions across systems,
• memory and planning – learning from past interactions and executing long-term goals,
• autonomy – working in the background without constantly asking for permission.

Use cases in applications

• E-commerce – the agent reaches out to a customer, offers a discount, and completes the sale.
• Finance – monitors accounts, pays invoices, and detects suspicious transactions.
• HR and admin – schedules meetings, sends contracts, and reminds about deadlines.
• Marketing – runs ad campaigns, tests variations, and optimizes budgets.

Opportunities and risks

Opportunity: businesses can save massive amounts of time and scale operations without hiring more staff.

Risk: too much autonomy could lead to errors, misuse, or data security issues.

That’s why Agentic AI requires regulatory frameworks and oversight mechanisms – much like an autopilot in an airplane.

What does this mean for business?

• New competitive edge – companies that first deploy AI agents in customer service, marketing, or logistics will gain a huge advantage.
• Changing employee roles – from operators to supervisors and process designers.
• New business models – applications and SaaS won’t be sold as “tools” but as digital employees.

Agentic AI is not science fiction – early implementations are already here. Within the next 3–5 years, it could become the standard in both business and consumer applications.