AI strategy is a hot topic these days, and everyone’s scrambling to come up with one. But where do you start?
At Hop, we have a comprehensive process for developing an AI strategy that we work through with our clients, but before we even get started, it's helpful to consider some foundational truths underlying our approach. These are some things we believe about AI strategies that are not necessarily widely understood.
1. An AI strategy can be very simple.
This first one may come as a bit of a surprise, but an AI strategy can be very simple. Typically, when we use the word “strategy” in our business, or “strategy” for our team, it conjures visions of McKinsey-style polished decks, or 40-page strategy documents. Those aren’t necessary – when it comes down to it, the key question to answer with an AI strategy (or any strategy, really) is “What are we doing, and why?”
Answering both parts of that question is important because…
2. An AI strategy is primarily a communication device.
We tend to look at a business that has been successful for clues – we study its strategy, and we make the association that the strategy is the key to its success. It's as if there was some deep insight that paved the road to success. That's only true in hindsight.
The forward-looking, in-the-moment lived experience of a strategy is that it's a hypothesis. You don't actually know if it's going to work or not, but it's your chosen perspective on the world. The benefit of articulating the “what” and “why” is so that everyone in your organization, top to bottom, has alignment on that perspective. This doesn't necessarily mean that you have communicated your view as a leader to be adopted by everybody else – it's more about coming up with a shared view that's aligned with and builds off of the views of everybody on your team so that everyone's efforts are coordinated. All the boats are pulling in the same direction.
So when do you need to come up with this shared view?
3. Business needs dictate when you need an AI strategy. (But those might not be market needs.)
You don’t need an AI strategy right away. We believe that business needs should dictate when you develop one. We’ve previously said a much more nuanced thing here, about when your corporate strategy reveals that it’s important for you to develop an AI strategy, or when your competitors are doing something compelling in AI and you want to evaluate that, but the bottom line is: Don't rush to come up with a new strategy until there's a need.
The caveat here is that in the current day and age, especially with the interest in generative AI and large language models, your business needs may be different from market needs. It may be that a lot of people in your organization, who are thoughtful, empowered people, motivated to solve important problems for your business, see this really cool technology and want to try it out. That's not a bad thing – it's behavior you want to incentivize.
But if their efforts are uncoordinated, and they're all individually creating proofs of concept, or dabbling with AI in a way that isn't very thoughtful or strategic for your business, then at best it’s wasted effort. At worst, it can cause frustration and resentment on your team, perhaps leading people to look for other situations in which there might be a more cohesive strategy. In cases like this, there may be organizational business needs that dictate the need for an AI strategy sooner rather than later.
So you may or may not need one right away, but…
4. Everyone needs an AI strategy.
Lastly, in this current day and age, everyone ultimately does need an AI strategy. We're now in a place where not only are a lot of industries being reshaped by AI, we're also seeing a lot of organizational career interest in exploring what AI can and can’t do. It's within reason for an organization to say “we are not doing anything with AI” – your strategy can be as simple as that – but you do need to say why you’re not doing anything with AI, and make sure your team is aligned with the vision around your strategic advantage. If you don’t make this clear, there’s the potential for breeding resentment and causing confusion: for your team members, your stakeholders, your partners, your investors, and so on.
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These four foundational truths are just the starting point for diving into our AI strategy process – we’ll get into some of the building blocks of that framework in future posts.
Where is your business on the path to forming an AI strategy? How do these four points align or contrast with your organization’s thinking? Reach out —we’re always curious to hear how others are approaching this topic.
– Ankur Kalra, Founder/CEO @ Hop