Three Ways to Failure-Proof Your AI Roadmap

You’ve been tasked with compiling an artificial intelligence (AI) budget.

Now what?

Budgeting for AI is a daunting endeavor. Fortunately, Synaptiq has extensive experience helping organizations do just that. Here's the field-tested, three-step approach we've used to help countless clients budget accurately for AI.

I. Set Goals 

How much will your AI roadmap cost to execute? 

Your AI roadmap starts with a problem and ends with a solution. Setting an accurate budget entails drawing a reasonable path between those points and then quantifying the cost of every step along that path as precisely as possible.

Bottom line: What is needed to travel from A (problem) to B (solution)?

This is a broad question. You can narrow it down by reframing your 'solution' as a goal that you can measure. For example, let's imagine that your problem is low customer satisfaction. Your 'solution' is improving customer satisfaction, which you might reframe as one (or more) of the following quantitative goals:

• Develop a chatbot to increase your customer retention rate by ___%
• Automate quality assurance to reduce quality complaints by ___%
• Enable predictive maintenance to reduce downtime by ___%

II. Identify Viable Use Cases 

AI can solve many problems, but it's not always the best solution. Once you’ve set a goal, really ask yourself, Can AI accomplish this for a reasonable cost?

• Yes → That goal is a “viable” AI use case.
• No → That goal is a “nonviable” AI use case.

Viability is dependent on your organization's resources, like your data and team. We suggest conservatively appraising these resources. Outsourced data and talent are expensive; an unexpected need will blow up an optimistic budget.

Organize your viable use cases in order of priority. Estimate the cost of executing an AI initiative to address each one. Your budget is the sum of those costs.

III. Conduct Feasibility Studies

The best, least-risky way to test your budget against reality is a feasibility study: a low-cost, limited-commitment test run of your AI roadmap. Start by choosing a viable use case that can be addressed with a short, inexpensive AI initiative. Execute each step of your AI roadmap, and note where expectations fail reality.

Conducting a feasibility study will expose missteps in the budgeting process. Questions that keep you up at night, like "Are your resource estimates accurate?" and "Is your team capable of executing on schedule?" will be answered.

Image by Wolfgang Hasselmann on Unsplash

About Synaptiq

Synaptiq is an AI and data science consultancy based in Portland, Oregon. We collaborate with our clients to develop human-centered products and solutions. We uphold a strong commitment to ethics and innovation. 

Contact us if you have a problem to solve, a process to refine, or a question to ask.

You can learn more about our story through our past projects, blog, or podcast.