Piloting your agentic future

You don’t need a big bang to get started with AI.

In fact, the best transformations don’t start with strategy decks or system overhauls. They start with a pilot — something small, clear and human-centered. A proof point that shows what’s possible when AI works with people, not just for them. And nowhere is this more achievable than in enterprise content workflows.

Content is a perfect proving ground. It’s where volume meets variability, where creativity meets coordination. It’s also where bottlenecks pile up fast. Planning stalls in meetings. Reviews lag. Personalization gets shelved because no one has time to tailor. But when AI agents enter the workflow — not as replacements, but as collaborators — things move. Briefs get drafted. Variants get tested. Teams spend more time on quality, less on wrangling.

This article explores how digital leaders can design and run their first agentive content pilot. We’ll focus on where to start, how to measure success, and what to watch out for. Most importantly, we’ll keep it real: no sci-fi hypotheticals, just field-tested principles that ambitious teams are using today.

Why content is the right place to start

If you’re looking for fast traction with AI, content isn’t just a good candidate, it’s the best candidate. It’s high-friction, high-volume work that nearly every team touches. And it’s full of repetitive tasks that still require a human touch: research, planning, drafting, QA, personalization.

That makes it a sweet spot for AI collaboration. You’re not delegating decisions; you’re sharing the load. The risk is low, the value is clear, and the feedback loops are fast.

As seen in teams using tools like MarketMuse, Writer, or even internal GPT-based assistants, AI can quietly augment planning and production without disrupting the creative process. What changes isn’t who creates, but how creation happens, and how quickly high-quality content can ship.

What makes it “agentic,” not just automated?

It’s easy to confuse AI automation with AI collaboration. But there’s a crucial difference: Agentive systems don’t just complete tasks, they contribute to outcomes.

In a true human–agent workflow:

• Agents interpret goals and suggest options
• Humans review, refine and steer
• The system learns, adapts and improves over time

As Orium’s Humans + Agents ebook puts it, “We’re no longer building systems solely for human use. We’re building systems where humans and agents actively collaborate.” That shift, from tools that assist to agents that act, isn’t theoretical. It’s already changing how content teams operate.

For example, MarketMuse helps teams like Monday.com scale content strategy by using AI to prioritize topics, generate briefs and identify coverage gaps. Writer embeds brand voice and compliance guidance directly into the drafting process, turning every contributor into an on-brand communicator. Even lightweight GPT-powered Slackbots are helping Hearst journalists generate headlines and summaries while preserving editorial intent.

And on the delivery side, Spotify now uses AI voice cloning to translate podcasts into multiple languages — keeping the host’s tone and cadence intact. That’s not a production tool; it’s an AI teammate making global reach scalable without re-recording.

In all of these cases, AI isn’t a post-production step. It’s embedded in the flow of work. That’s what makes it agentive — and that’s where the future of content collaboration begins.

How to design a high-trust pilot

Here’s the good news: You don’t need to rewire your stack. Start by rewiring your workflow. A successful agentive content pilot starts with a clear use case. Look for:

• Repetitive tasks that slow teams down (e.g. SEO briefs, campaign variants, metadata tagging)
• Human-in-the-loop checkpoints that build trust, not blockers
• Goals that are easy to measure: faster output, better consistency, reduced lag

As the ebook advises, “The best agent use cases aren’t moonshots. They’re high-friction, high-leverage moments — ripe for automation, yet still in need of human oversight.”

Define agent responsibilities clearly. Will it suggest, generate, or route? What does the human review, override, or approve? Who owns the outcome?

Run this like a real initiative: Assign a pilot lead, document learnings and share results visibly. Nothing builds confidence like a teammate saying, “This saved me four hours and improved our output.”

Running the pilot: best practices from the field

Once your agent is live, don’t just measure throughput. Measure feedback. Instrument both the system and the sentiment by capturing both quantitative and qualitative insights. 

Track measurable outcomes like the number of drafts completed and the amount of time saved to understand the operational impact. At the same time, gather feedback on how the team feels about using the tool — where it provided support, and where it may have introduced friction. This dual approach ensures you’re not only assessing performance but also the experience behind it.

Keep humans deliberately in the loop. In early stages, over-collaborate, build shared memory and trust. A “rough draft” bot is better than a black-box bot — transparency accelerates adoption. 

And critically: share wins early. A single demo of how an agent helped draft a 20-page report or surface new insights can shift the tone from “we’ll see” to “what else can we try?”

Scaling what works — without losing the plot

If your pilot worked, great. Now comes the harder part: expanding without overreaching.

Here’s how to do it:

• Move from pilots to playbooks: Codify workflows, prompts, fallback rules and review checkpoints
• Layer in governance: Build in audit logs, role-based permissions and explainability features
• Upskill quickly: Train people as they use the tools, normalize “trying and tweaking,” and most importantly, celebrate small innovations

Create a “center of curiosity,” not just a center of excellence. You don’t need a task force to scale, you need stories. The best next use case often comes from a marketer, editor or designer who asked, “Could an agent help me with this?”

Final takeaway: composable, collaborative, and ready to go

The future of content isn’t fully automated, and it doesn’t need to be. What teams need is speed without burnout, scale without compromise, and personalization without endless labor.

“The best organizations aren’t scaling agents. They’re scaling collaboration." — Humans + Agents eBook

That’s what agentive pilots deliver. They don’t just show what AI can do, they show what human and agent teams can do together. So don’t wait for the perfect model or the AI strategy offsite. Find one workflow, one tool, one team. Give them an agent. Let them run.

And when it works, don’t scale the agent — scale the collaboration.

Everett Zufelt is the VP Strategic Partnerships & Emerging Technology at Orium, a Contentstack partner. Everett leverages his extensive technical background and over a decade of experience in headless and composable commerce to lead the development of Orium’s offerings. He guides the go-to-market strategy and supports his teams in crafting solutions that enhance the digital capabilities and operational efficiency of scaling commerce brands. Connect with Everett on LinkedIn.