AI Strategy Guide
AIcan double the productivity of the people at your company. That is a tremendous prize and a large amount of change. Like anything that big, it requires thoughtful consideration of the effects and sequencing. This guide will take you through how to achieve these results and how to roll out this transformation. Crucially, it is a plan for how to do so while building up the economy and society.
Overview
Most companies use AI to change their business in three ways.
- Research AI, building new models and systems from proprietary data.
- Process AI, optimizing specific tasks to be handled by AI models and agents.
- Workflow AI, quickly creating software to manage day to day tasks.
The first two get the most attention but Workflow level AI is widely applicable and hugely valuable. Rather than requiring hard to find ML engineers, much workflow improvement can be done by staff who currently do the work and by engineering staff you already have or already work with. The frequent complaint, “I wish this task was easier”, can instead become a tool for frequent AI delegation.
This journey is going to get weird; and it will take us to great places, where we have so much capability at our fingertips. Imagine everyone having their own personal construction company. It’s one thing to know that abstractly, it’s another to see the office parking lot when everyone drove an excavator to work. Working for technology companies, our team has been through this transition first hand. The job of software engineers writing code went away last year (even if many don’t know it yet). The new job of software engineers crafting outcomes is fulfilling and wonderful.
Many AI prescriptions suffer from “software brain”, the perspective that everything is work to be automated. Or “business brain”, focusing on short term profits over healthy systems. This guide does focus on automation and creating business value but it only works if we first align on where we are headed. Getting to success all together as companies and societies means talking through, “how to share the value we create”, and “how to avoid externalities”. We can’t lay everyone off then wonder why no one has money to buy our products. We can’t expect our coworkers to drive change unless that change is safe and the incentives work for them instead of against them. We have to purposefully choose paths that lead to growth, broad-based success, and good long-term outcomes.
Dividing up work between AI and people compounds. As tasks get fully or partially automated, new opportunities are revealed. The core work of finding constraints and imagining solutions becomes clearer across roles. This is not just an initial guide but a roadmap covering intermediate and advanced stages: how to drive demand and how to succeed along multiple dimensions. Market value, rewarding jobs, a booming economy, human flourishing; all of these are our goal.
What’s required to move forward? Commitment. Starting the alignment conversations, allocating a relatively small budget for the first project, committing to transforming your company over the next two years.