Rolling Out Assist

Strategies for Success

A practical playbook based on real-world implementations across hundreds of users and dozens of marketing teams worldwide

After working with hundreds of users across diverse marketing organisations, we've identified a clear pattern:

Teams that start small, solve specific problems well, and scale methodically achieve 3x higher adoption rates and 60% faster time-to-value.

Assist is built for marketing teams to power your team with AI agents, tools, and workflows that scale creativity and productivity.

The Golden Rule to a successful rollout is: Slow is steady, steady is fast.

Why Most AI Rollouts Fail (And How to Avoid It)

Common Pitfalls:

Trying to solve everything at once
Building solutions without clear problems
Skipping quality control in the rush to deploy
Treating AI as a technology project instead of a change management initiative

The Winning Formula:

Focus: 1-2 high-value use cases maximum
Quality: Establish excellence before scaling
Social Proof: Let success stories drive adoption
Iteration: Perfect the process, then replicate

The Strategic Rollout Framework

Phase 1: Foundation (Weeks 1-4)

Objective: Establish infrastructure and identify your first success story

Phase 2: Prove Value (Weeks 5-8)

Objective: Deliver measurable wins with your first use case

Phase 3: Scale Smartly (Weeks 9-16)

Objective: Expand to additional use cases and teams

Phase 4: Enterprise Integration (Weeks 17+)

Objective: Embed AI workflows into standard operations

The Six-Step Success Loop

Step one is to find your first use case once you have this process down

You'll accelerate every subsequent rollout.

1. Define the Problem Crystal Clear

The One-Page Problem Statement:

Who: Specific role/team affected
What: Exact pain point (with current time/cost)
Why: Business impact of solving it
Success: Specific metrics you'll track

Example:"Creative Directors spend 3 hours per campaign manually converting client calls into briefs, leading to 24-hour delays and inconsistent information capture. Success = 80% time reduction with 95% accuracy."

2. Gather Your Data Arsenal

You'll Need:

10-15 examples of current inputs
5-10 examples of "perfect" outputs
Access to authoritative sources (brand guides, templates)
Permission mapping (who can see what)

Pro Tip: Involve your best performers in defining "good" outputs—their expertise becomes your AI's training foundation.

3. Agree the Assist Outcome

Create a detailed specification:

Input format and sources
Agent or Output - what's the best path to success
Required structure
Quality thresholds (accuracy, completeness, style)
Review and approval process
Integration points with existing workflows

4. Build with Precision

Start Simple, Build Right:

Build your own output or
Work with your Account Manager to configure custom agents and outputs

Agent Selection Strategy:

Begin with out-of-the-box agents that match your use case
Leverage specialist agents for industry-specific tasks
Scale to custom agents as your confidence and needs grow

5. Test Ruthlessly

The 10-Test Rule: Run 10 real-world scenarios through your system before wider release.

Track:

Accuracy against your quality rubric
Edge cases and failure modes

6. Refine and Perfect

Feedback

Refine your templates or ask your account manager to hone your outputs and agents
You achieve 2 consecutive perfect runs.
Users can operate independently.

Change Management: The Human Side of AI

Rolling out any new technology is mych about the humans as it is the platform. Assist is not different. Below is a sample plan for how you might think about a structured approach to your roll out.

Week 1-2: Set the Stage

Announce the pilot (not full rollout) to the selected team
Share the problem you're solving, not the technology
Set expectations: "We're experimenting to make your lives easier"

Week 3-4: Show, Don't Tell

Run live demos with real examples
Share time-saving metrics from early tests
Collect feedback in a dedicated Slack/Teams channel

Week 5-8: Create Champions

Identify power users who see the value
Document success stories with specific metrics
Train these champions to help colleagues

Week 9+: Scale Through Stories

Regular showcases of wins and learnings
Peer-to-peer training rather than a top-down mandate
Celebrate early adopters and their achievements

Conclusion: Your Path to AI Success

Rolling out Assist isn't just about implementing technology—it's about transforming how your teams work. The organisations that succeed follow a disciplined approach: they start small, prove value, and scale systematically.

Remember the fundamentals:

Quality over speed: Perfect one use case before adding another
People over process: Invest in change management and training
Iteration over implementation: Continuous improvement beats one-time deployment

Your journey to AI-powered productivity starts with a single step. Choose your first use case, apply this framework, and build the foundation for transformative change.