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“What Are the Best (and Easiest) Platforms to Build AI Agents?”

AI agents have the potential to transform how marketing teams operate - automating repetitive tasks, analyzing customer data in real time, and ensuring consistent brand interactions. The good news? You don’t need advanced programming skills to get started. No-code and low-code platforms now make it easier than ever to explore AI agents quickly and cost-effectively.

But… What Is an AI Agent, Really?

One of the biggest challenges in discussing AI agents is the lack of standardized industry terminology. Depending on the context, an AI agent could refer to anything from a simple automated chatbot to a sophisticated system capable of multi-step reasoning, task execution, and even web browsing. Given this fluid definition, we take a broader perspective in this article - focusing on AI-powered tools that can execute tasks independently, enhance marketing workflows, and improve customer experiences. If you're looking for a deeper dive into AI agent fundamentals, check out my 'AI Agents 101' article.

Why You Should Start Now

AI agents are evolving rapidly, but waiting for a “perfect” solution means falling behind. Early adoption gives marketing teams an edge by allowing them to:

• Build foundational AI capabilities before technology becomes mainstream.

• Optimize workflows incrementally, rather than undergoing a massive transformation later.

• Understand AI’s limitations firsthand and adjust strategies accordingly.

• Stay ahead of competitors who delay implementation.

When (and When Not) to Use AI Agents

While AI agents offer significant benefits - automation at scale, data-driven insights, and reduced manual workload - they aren’t a universal solution.

When AI Agents Make Sense:
✅ Repetitive, time-consuming tasks (e.g., email categorization, social media responses)
✅ High-volume, data-driven workflows (e.g., personalization, predictive analytics)
✅ Multi-step, automated processes (e.g., lead nurturing sequences)

When to Hold Off:
❌ Tasks requiring deep domain expertise and nuanced decision-making (e.g., legal compliance, medical decisions)
❌ High-stakes creative or emotional work (e.g., brand storytelling, therapy)
❌ Environments with strict regulations or privacy concerns (e.g., finance, healthcare)

10 Key Questions to Ask Before Implementing an AI Agent

Before deploying an AI agent, assess its impact using these questions (plus this guide):

1. What is the complexity of the task?

2. How frequently does the task occur?

3. What is the expected volume of data or queries?

4. How would be the impact on the human workforce?

5. What level of accuracy is required?

6. Is human expertise or emotional intelligence essential?

7. What are the privacy and security implications?

8. What are the regulatory and compliance requirements?

9. What is the cost-benefit analysis?

10. What does “hiring" and “onboarding” look like? (See example below)

Solutions to Consider

1. What You Already Have in Your Tech Stack

If you're using OpenAI, you already have access to Custom GPTs and, if you're a Pro user, Operator - with Deep Research expected to roll out soon. Microsoft users can tap into Copilot and Copilot Studio, which integrate seamlessly across their ecosystem. Google users, however, may need to wait for broader access to Project Mariner or Agentspace - or apply for early access through experimental programs here and here.

These are just a few options. The best starting point? Look at the AI tools you already have access to and explore their agent-like capabilities - you might be surprised by what they can do.

2. Custom GPTs and Operator (OpenAI)

Custom GPTs make it easy to tailor AI to your specific needs, whether that’s refining your content creation process, incorporating proprietary knowledge, or optimizing workflows. Operator, OpenAI’s more advanced AI agent, can autonomously complete multi-step tasks.

3. Copilot (Microsoft)

Microsoft’s Copilot and Copilot Studio are already embedded in its ecosystem, helping businesses automate internal processes, analyze data, and manage marketing content. For organizations already using Microsoft products, this is a seamless way to integrate AI agents into existing workflows.

4. Agent.ai

Agent.ai describes itself as a "marketplace and professional network for AI agents and the people who love them." Users can create, share, and discover AI agents designed for various tasks - ranging from company research to optimizing landing pages for better conversion rates.

5. Taskade

Originally a productivity and collaboration tool, Taskade now supports AI-driven automation. Users can build AI-powered workflows for task management, team communication, and custom automation needs - all in one streamlined platform.

6. Zapier

Zapier has rebranded Zapier Central to Agents, introducing AI teammates that can be equipped with company knowledge and integrated across 7,000+ apps. If you're already familiar with Zapier’s automation tools, this could be a natural next step.

7. Relevance AI

Relevance AI helps users build an "AI workforce" without coding. It offers semi-ready templates and customization tools for creating AI agents that automate tasks, analyze data, and streamline workflows.

Final Thoughts

No-code and low-code AI platforms make adoption more accessible, but implementation should be strategic. By evaluating your existing tech stack, identifying key workflows, human workforce impact, and weighing costs against benefits, you can ensure that AI agents enhance your operations - without introducing unnecessary complexity.