Agentic AI: Meet Your New Business Partner

When Generative AI entered our lives in late 2022, it impressed us with its ability to create content, perform data analysis, and generate visuals. But it had a major limitation: it could only respond to user prompts - it couldn’t take initiative on its own.

That changed in 2024 with the rise of Agentic AI, introducing a brand-new paradigm in artificial intelligence. Unlike its predecessors, Agentic AI doesn’t just wait for commands - it can autonomously plan multi-step tasks, switch between tools to execute them, and adapt its actions based on feedback. Think of it not as a tool, but as a digital co-worker capable of driving outcomes - across platforms and systems.

What Makes It Different?

The core distinction of Agentic AI lies in its ability to independently plan and execute the steps required to reach a goal - and to do so across multiple applications. Traditional automation was limited to fixed workflows, and Generative AI could only produce responses. Agentic AI goes much further:

• Plans complex, multi-step workflows: Say “Analyze our new customers and create a proposal for our 2024 campaign.” It collects the data, performs the analysis, drafts the proposal - and can even email it to stakeholders.

• Integrates across systems: It moves seamlessly between CRM, ERP, email clients, browsers, and office apps - just like a human would.

• Learns and adapts: It evaluates its outputs, changes methods if something fails, and tries again.

• Goal-oriented, not rule-based: It’s driven by outcomes, not pre-written scripts.

Put simply: Generative AI writes the email- Agentic AI sends the whole campaign.

Why is it Possible Now?

The rise of Agentic AI has been made possible by three key advances:

• Tool use: Large Language Models (LLMs) can now interface with and operate external tools.

• Execution environments: New workspaces like OpenAI’s Agents can access their own browsers, terminals, and virtual machines to perform actions.

• Cross-platform integration standards: Protocols like Anthropic’s Model Context Protocol (MCP) enable seamless communication across different systems.

Thanks to this ecosystem, Agentic AI is becoming enterprise-ready.

Real-World Applications of Agentic AI

While many companies claim to "automate with AI," most are simply enhancing workflows with LLMs. True Agentic AI systems go beyond this:

OpenAI – ChatGPT Agents: Now equipped with a browser, code editor, and file manager, ChatGPT can autonomously complete tasks like booking a hotel, analyzing data, or writing research summaries.

Microsoft Copilot Studio: Agents now mimic human actions - clicking, filling forms, navigating interfaces - and multiple agents can collaborate on a single workflow.

Amazon Bedrock AgentCore: AWS provides the infrastructure for secure, transparent, and scalable Agentic AI integration - handling even mission-critical workflows.

Salesforce Agentforce: Within the CRM, it doesn’t just suggest - it acts. When a customer query comes in, it can respond and trigger a relevant campaign.

What they all have in common: They autonomously access resources and carry out multi-step processes when given a goal.

How Can Companies Get Started?

The transformative power of Agentic AI lies in its ability to execute entire workflows autonomously. Here’s how your organization can begin adopting it:

1. Set Goals, Not Tasks

Move away from rigid step-by-step instructions like “Clean and analyze the data.” Instead, define outcome-driven goals such as “Identify our top customer complaint and suggest a fix.” This unleashes the full potential of Agentic AI.

2. Design Cross-Platform Workflows

Don’t limit yourself to one platform. Apply Agentic AI to chain workflows like:

• New customer onboarding → CRM registration → Welcome email

• Competitor research → Summary report → Executive presentation

• Meeting transcript → Task assignments → Calendar updates

3. Use Agent Development Frameworks

Create your own agents with open-source tools like CrewAI, LangGraph, Autogen, OpenAgents, or use enterprise-grade platforms like Copilot Studio and Bedrock AgentCore.

4. Define Access and Safety Policies

Since agents perform actions like humans, errors can be costly. Ask:

• What actions require approval?

• What systems should agents access?

• How frequently should they be audited?

Establish clear governance policies from the start.

5. Monitor and Optimize

Agents improve over time through feedback. It’s essential to track outcomes, analyze failures, and continuously fine-tune agent behavior.

What’s Next?

Agentic AI is just getting started, but the direction is clear. In the future, apps will evolve for agent-first interaction, not human interfaces. Even systems without APIs will be automatad via screen-based agents. Companies will delegate some roles to permanent digital workers (agents). As standards evolve, human + agent teams will become the new operating model. Humans will focus on strategy, and agents will handle execution. Together, they’ll deliver results as true collaborators.

Agentic AI is more than the next step after Generative AI - it’s a leap forward. It doesn’t just create content; it takes action, uses tools, and drives results. Companies ready to embrace this shift will gain not just productivity, but also speed, agility, and innovation capacity. Those who lag behind may mistake simple automation for true intelligence, while others are already transforming how work gets done. Now is the time to act -  not just with AI, but with Agentic AI.

Mustafa İÇİL