Wishful Thinking Won't Cut It: A 5-Step Framework for Making AI's Potential Tangible
A wish for AI without a plan is unlikely to come true. This article gets your AI dreams out of the clouds and onto solid ground with a practical 5-step plan to stop dreaming and start doing.
"A goal without a plan is just a wish."
Antoine de Saint-Exupéry
The French author Antoine de Saint-Exupéry, best known for his novella The Little Prince, once declared, "A goal without a plan is just a wish." This insightful quote has become a famous motto emphasizing the importance of thoughtful execution to bring a wish to life.
This quote also encapsulates the challenge of integrating AI in today's corporate environment. I've collaborated with teams eager to utilize AI, yet they stumble when determining the initial steps required. In this article, I present a 5-step process designed to transform AI's capabilities into an unfair advantage for your team. My approach anchors AI projects in tangible business objectives, concentrates on high-impact and attainable changes, and underscores the importance of gradually incorporating AI into existing workflows.
1. Clarify your "Why"
As Simon Sinek says, "Start with why." Understand your motivation for pursuing AI. Clarifying why you want to implement AI is crucial for a successful project.
Consider if your interest in AI is truly aligned with concrete business goals or if you are just following the hype. AI as an abstract concept or tech buzzword will not drive meaningful results. You need a strategic purpose grounded in realities, not theoretical possibilities.
2. Identify Key Processes and Constraints
The Theory of Constraints (TOC) provides a useful framework for finding processes ripe for AI optimization. Developed by Eliyahu Goldratt in the 1980s, TOC analyzes how constraints limit a system's overall throughput. TOC says you should improve overall performance not by strengthening everything but by releasing the tightest constraint.
Recently, I've been working with digital marketing agencies that are trying to scale their business. In our sessions, the account management team emerged as the tightest constraint. Taking on additional customers risks overloading the team. Yet, the business lacks the revenue visibility to hire another account manager.
We applied TOC to discover the manual tasks constraining the account managers. We found that using AI to automate the data collection and report generation process could free up time and make this essential task automatic. This became the basis of a pilot to deploy AI.
The continual, incremental improvement of your tightest constraints holds the key to durably scaling your business.
3. Prioritize Potential Projects
Once the motivation is clear and constraints identified, the next step is thoughtfully prioritizing potential projects to focus AI implementation on high-impact areas. Using simple frameworks like t-shirt sizing can be helpful for assessing each potential project based on estimated effort and business impact.
Effort encompasses factors such as required time, resources, and complexity to implement the AI solution. Impact reflects possible benefits like cost savings, revenue growth, or other measurable value.
With these two variables plotted on axes, projects can be mapped into quadrants showing high versus low effort and impact. The top right contains high-impact but highly complex initiatives. The bottom left reflects simpler but lower value changes. The key is identifying "medium" projects in the sweet spot – moderate effort but with meaningful impact.
4. Start Small, But Start Now
When initiating any new technology project, there is wisdom in starting small before scaling up. AI is no different. While having a grand vision sets long-term goals, trying to boil the ocean on day one often ends poorly.
Begin instead with a focused pilot project to limit risk and enable learning-by-doing. As Wright's law shows, costs decrease as experience increases – teams learn through continuous hands-on practice and repetition. Starting small allows for this vital feedback loop of accumulating knowledge. But start now, because experience is the best teacher.
Reduce Friction in Adoption
Rolling out any new technology meets resistance. AI is no exception. While exciting in concept, shifting day-to-day workflows to incorporate AI causes friction. If using AI feels like "more work", people will naturally resist adoption.
Making AI invisible reduces friction. At boxcars.ai, our AI automations (called boxcars) blend seamlessly into existing workflows. You assign tasks to a boxcar directly within your normal project management tools like Trello, ClickUp, or, if email is your jam, we don't judge...okay maybe just a little. But hey, we're here to meet you where you are! The work product from boxcars flows directly into your regular apps whether that's a presentation in Google Slides or a file in Dropbox.
The goal is to make AI feel like your unnoticeable secret assistant, not yet another tool, software, or process.
Achieve the AI Advantage
The future belongs to teams that effectively incorporate AI into scaling their business. They will outcompete teams that don't. History shows each wave of disruption provides an opportunity to gain an unfair advantage. AI is no different.
This article outlined a strategic framework to guide you from inspiration to activation:
Clarify the why to ground projects in business realities
Identify constraints using TOC to find high-impact areas
Prioritize projects based on feasibility and speed
Start small with pilots to build experience
Reduce friction by embedding AI seamlessly
If you're interested in identifying constraints and prioritizing AI projects for your team, I'm offering a 60-minute strategy session. This consultation will assess your processes, find bottlenecks, and build a prioritized list of high-potential AI initiatives. By starting with strategy, you can transform AI's potential into an unfair advantage. Reach out if you'd like to discuss further - let's chat and turn your AI wish into a goal with a concrete plan.