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Being Al-first means doing Al last. Doing Al means doing it last or not doing it at all. The reason is rather simple: Solution-focused strategies are more complex than problem-focused strategies; and solution-focused thinking ignores the most important part of business, which is the problems they solve and the customers they create.
Keep in mind that solution-centric thinking results from the following:
Focusing on what our solutions ought to be rather than what they are.
Focusing on the impact of future solutions rather than the future impact of today's solutions.
Conflating our goals with the goals of others.
Focusing too much on abstract problems with some arbitrary solution or focusing too much on someone else's problem and ignore your problems. The former is solution solving and the latter often means we are working problem solving backward and finding problems to solve in the context of someone else's solution.
Do not define your solution. The search for analytical exactitude in verbal definition will not lead to economic progress. Ignore recycling glib, textbook definitions of artificial intelligence mainly because consumers don't care about textbook definitions. Customers care about themselves. If you want to make your life better, make their lives better. Help them accomplish their goals in a better, faster, safer, or cheaper way. They're generally interested in a value proposition that contains problem-specific information, not in a definition of intelligence. Your journey starts with more comprehension of problems, not the names or definitions of solutions. Besides, creating definitions for our solutions means we are creating external goals for them, which is nonsense.

Remember that insiders seek epistemological discoveries, not economic ones. The more epistemological a pursuit is, the less likely it is to become something that could be turned into a business. Entrepreneur, venture capitalist, and author Paul Graham discusses the value of problems at length and explains that good business ideas are unlikely to come from scholars who write and defend dissertations.
The reason is that the subset of ideas that count as "research" is so narrow that it's unlikely to satisfy academic constraints and also satisfy the orthogonal constraints of business. The incentives for success in the academic world are not consistent with what it takes to start and grow a business. Ultimately, business pursuits are much more complicated than academic ones. Managers ought to acknowledge that solving intelligence is not likely your goal, and in many ways it's oppressive to problem solving. AGI may be possible, but it is not desirable as a business goal.

There is something magical about writing down a problem. It's almost as though by writing about what is wrong, we start to discover new ways of making it right. Writing things down will also remind oneself and our teams of the problem and the goal. Once a problem is written down, don't forget to come back to the problem statement. It is a guide. Problem solving often starts with great intentions and alignment, but when it counts most-when the work is actually being done-we often don't hold on to the problem we set out to solve, and that's the most important part of problem solving: what the problem is and why we are solving it to begin with.
Furthermore, do not needlessly seek out complexity by making larger solutions to solve needlessly bigger problems. Complexity bias is the logical fallacy where we find it easier to seek out complex solutions rather than a simple one. Without a problem statement, solutions tend to become more complex and expand to fill in the available time we've allocated for problem solving. Parkinson's law, named after Cyril Northcote Parkinson, states that "work expands so as to fill the time available for its completion." This is a sort of solution sprawl, similar to the urban sprawl that expands to fill in geographic spaces immaterial to how well the urban landscape serves it citizenry.

Always start small and take small steps to ensure that performance is what you want. Don't try to boil the ocean with the whole of a problem. With smaller steps almost everything can be reduced to something more manageable. Working in smaller sizes and smaller steps goes for your team as well. Rather than having your whole team work on something for six months, think about what one person can do in six weeks. The Basecamp team uses six weeks, which I think is a good size. If you are an Agile team, you may have batches of two weeks.75 That is fine, too. The point is that constraining batch size will force everyone to find the best bad solution, rather than working into the abyss of perfection.
Of course, simple problems are different. Simple problems can often be solved by applying a single solution to the whole of the problem. In practice you may not know the best solution a priori. One strategy to find the best solution for a simple problem may be to simply guess. Guessing, however, will have a high error rate in the face of increasing complexity.