AI agent crossroads & why your best strategy is one you don’t own alone

Your marketing platform has one. Your CRM has another. We’re building them at DEPT®, and you’re likely exploring how to build them for your own brand.

And while we might not be in chaotic AI land yet, it is creating a critical crossroads. 

With so many options, which path do you choose? Do you rely solely on platform agents? Do you build everything in-house? This landscape feels less like a collaborative future and more like the browser wars of the ’90s, where making the right strategic bet is everything. The most important question is no longer whether you’ll use AI agents, but how you’ll orchestrate them to achieve success.

As brands navigate this new territory, two seemingly safe paths have emerged. 

• The platform path: The first path is to rely solely on the agents being built into the major platforms you already use. The appeal is obvious: it’s simple, scalable, and requires minimal heavy lifting. But this path leads to a locked-down ecosystem. Platform agents lack the crucial context of your first-party enterprise data and cannot be customized for your unique workflows or creative needs. (It’s like having chocolate without the peanut butter.)
• The In-house path: The second path is to build everything yourself. The desire to own your technology and protect your data is understandable, but it’s a slow and expensive route. You’ll struggle to keep pace with the innovation of the major platforms, essentially trying to invent chocolate from scratch, while Hershey’s operates at a global scale. 

Both, however, lead to a dead end.

There is a third path, one that recognizes that the best outcomes are not found in silos but in synthesis. The greatest value emerges when you combine distinct ingredients to create something better than the sum of its parts.

This is the “Reese’s Cup” model for AI.

• Platforms deliver the powerful, scalable, and secure core AI functionality that serves as the foundation.
• Brands provide the most essential ingredient: context. Your first-party data, your unique customer use cases, and your creative and strategic insights are what make AI relevant and effective.
• Agencies are the orchestrators who design the ecosystem, build the connective tissue for data and workflows, and customize the tooling in ways platforms can’t.

It won’t be a single piece of software you buy, but a bespoke solution, combining API integrations with a managed service model where a team of experts operates the system. 

This “connective tissue” is built on emerging, open industry standards, like the Model Context Protocol (MCP). This universal language enables different models, platforms, and data sources to communicate. This means that as you build your agentic ecosystem, you’re not locking yourself into another proprietary system; instead, you’re architecting for an open, flexible future.

Getting this right is the key to unlocking the next level of performance: true personalization at scale, unprecedented operational efficiency, and a creative engine that can finally operate at the speed of culture.

While the technology is evolving and the route is murky, the steps you can take to prepare are clear and actionable.

Start with low-risk experimentation on partner platforms 

Before you architect a grand strategy, you need to understand the tools already at your fingertips. Your major platforms are your safest and fastest place to learn what agents can (and can’t) do. This discovery phase is critical for identifying the gaps that your unique data and custom orchestration will eventually fill.

Task a small team with activating the native AI agents within one of your core platforms (like your CRM or Marketing Cloud). The goal is to document three things:

• What worked well “out of the box”?
• What were the agent’s limitations?
• Where did it lack the brand or customer context to be truly effective?

Focus on the workflow, not just the technology

The insights from your experiments will illuminate where the real opportunities are. The most significant value comes from reimagining how work gets done to solve a specific business problem, not just plugging in new tech. 

Armed with your learnings, identify one significant point of friction in a key customer workflow. Map it from end to end and build a human-in-the-loop system around the agentic tasks. This allows your team to guide and verify the agent’s work, ensuring quality and building trust as you prove the value.

Connect your data to fill the gaps

Your initial experiments will inevitably reveal the limitations of generic platform agents. The most common finding is a lack of context. In other words, they don’t know your customers, your brand voice, or your unique business rules. 

Focus your data strategy on solving the specific context gaps you identified in your experiments. Instead of a generic “data cleanup,” you now have a targeted mandate: prepare and connect the specific data sets (e.g., product catalogs, brand guidelines, customer segments) that your agents need to be more intelligent and effective.

Build for an open, interconnected future

Your agentic ecosystem will consist of platform agents, custom-built agents, and your teams. The value lies in making them all work together seamlessly.

Start conversations with your technology partners about their roadmap for open standards like the Model Context Protocol (MCP). Prioritize vendors who are building for an interconnected ecosystem, not a walled garden. Your ability to connect disparate systems and create reusable agent components will be a critical capability that prevents redundancy and accelerates future projects.

The future of agentic AI won’t be won by those who try to protect old boundaries. It will be won by the brands, platforms, and agencies willing to combine their strengths to create something new.

The winner will not be the one with the single “best” agent, but the one with the best-orchestrated system. The most important question needs to become, “How do we build together?” Because in the age of agents, no one wins alone.