Make Your First 90 Days with AI Automations & Agents a Success

A simple, repeatable plan to pick wins, launch pilots and measure impact

You don’t need a lab or a giant budget to start. You need a clear why, a short list of high-impact problems, and a fast way to test. Here’s the formula I’ve used for my company and clients that you can run as a visionary founder or owner to build your “getting started” roadmap.

Step 1: Start with business goals, not tech

Open with the targets that matter. If you run EOS, pull your 3-Year Vision and 1-Year targets. Decide what you’re actually optimizing for right now: revenue growth, profit, team capacity, or new capabilities. Keep the list short and specific. Starting with tech is how AI projects fail. Starting with business results is how they work. All successful tech implementations start with Why.

Now, shine a spotlight. If the push is new logos and expansion in existing accounts, name the roles that carry that outcome and the processes they run every week.

Step 2: Find the friction

Ask one survey question to the people in those roles:

“What are you doing today that is not the ideal use of your time, and how much time does it take per month?”

Important: this is not “where do you want AI.” It is “where are we losing time against our goals.” Stay out of tool talk for now.

Your leaders have ideas, but go to the edge to get the real details on where the friction lives. Going to the folks who live it is really important to find the real opportunities as well as identify possible champions and early adopters who can help build meaningful adoption of AI.

Step 3: Turn friction into “what if” ideas

With the friction list in hand, run a short ideation pass:

• What if we applied AI here?
• What would success look like in business terms and how would we measure it?

You’re building a list of AI ideas that attack specific friction or unlock clear upside. They must tie back to the why.

Two paths usually show up:

1. Automations: remove repetitive steps like moving data, basic document checks, or form handling.
2. Agents: chase a goal and make choices along the way to support the team, not just run a single step.

Concrete examples you can model:

• Automation example: Reviewing legal docs posted to Slack channel takes a key team member 1-2 hours per day. By flagging the core dozen or so topics with green and red flags (and why) we can cut 80 percent of the human review time, which saves time and shortens sales cycles.
• Agent example: A sales team struggled with inconsistent calls and processes. Immediate post-call coaching for sales reps from an AI agent using the call transcripts checks against a sales playbook, core messaging and best practices to provide coaching on what resonated, what fell flat, and what to improve for the next call.

Step 4: Score by impact and speed, then plot the matrix

Ditch complexity. Score every idea on two numbers:

• Impact: on the business, 1 to 10 (whether time saved, new revenue – however you want to measure it)
• Speed: to roll out, 1 to 10, where 10 is fastest

Plot them on a simple 2x2 and then talk them through with your team. Move things around to get a relative score like “this one is definitely more impact than that one”. This is a great opportunity to bring clarity to what friction will be solved, and talk about success metrics.

Step 5: Build the short, rolling roadmap

Use the overlay in the diagram to pick your opportunities.

The top portion shows your #1 Quick Start opportunities, the right place to start.

Below that on the right side are #2 Next Step opportunities that have high value and can be achieved reasonably quickly. Under those are the #3 Deep Wins. These are going to take more work to get to the result. Anything below that is worth putting on a long-term road map of real business value but require lots of work to achieve so definitely not the place to start.

Anything outside these areas is the Danger Zone where the business value isn’t worth the investment or you’ll end up automating things that just don’t matter.

Aim for 2 to 4 Quick Starts in the first 60 days, with several more initiatives finished inside 6 months.

That 6-month window should get your organization comfortable with AI, focused on business metrics, and ready to refresh the plan. Recheck friction and reprioritize quarterly. We are starting with 90-day decisions, not multi-year bets.

Pitfalls to avoid

• Starting with tools instead of outcomes. Resist the itch to “try AI somewhere.” Start from goals and friction.
• Picking “easy, no impact” work. It ships fast, but no one cares and momentum dies. Prioritize fast and meaningful.
• Overstuffed lists. If you have more than 10 to 15 ideas, trim.
• Piloting without real data. Always use real samples.
• Automating a fuzzy process. Lock the process in first and then automate.

Wrap up

Your roadmap is powered by a clear why, a tight friction list, and a simple impact-speed matrix. Keep it short, score it honestly, and ship fast. Then review every quarter and repeat. That is how you get real results from AI automations and agents, without spinning your wheels.

Let me know if you try this process yourself, I’d love to hear about your results. And if you get stuck, please reach out, I’m happy to see if I can help you get on the right path.

Take Action

• Get practical, real world AI insights: Connect with me on LinkedIn - https://www.linkedin.com/in/alexbratton/

About the Author

Alex Bratton is the author Practical AI for Leaders and Billion Dollar Apps, an adjunct professor of computer science and the CEO & Chief Geek of Lextech, an Apple enterprise partner that applies cutting edge tech to drive employee efficiency for teams through tech powered experiences people love.

Alex is an applied technologist who leads Lextech’s AIWhy efforts to bring practical AI to the mid market, https://aiwhy.io .