This blog first appeared as Steve Wunker's piece for Forbes
Generative AI has quickly surfaced onto many product strategy agendas. While imperfect, the technology has reached its breakthrough point and offers transformative potential. It’s reminiscent of the first iPhone – a product with plenty of room for improvement, but quite obviously on a short path to revolutionize human-machine interactions.
How should tech product strategy adapt to generative AI? Here are five key undertakings to get you started:
1. Really dig into your customers’ Jobs to be Done
I worked with Harvard’s Clay Christensen on his first Jobs to be Done consulting project about twenty years ago, for a large tech company seeking ways to bring mobile electronics into enterprises. “Jobs” is an inquiry method Clay developed that, essentially, figures out what people are really try to accomplish vs. what they happen to be doing today about it. The electronics firm risked being in a classic case of technology-push, but it wanted to do better by understanding those root motivations. So, we focused on what types of activities mobile electronics could do well, settled on a handful of customer types and use cases, and then went quite deep using Jobs to be Done to discover critical insights that would affect how the technology could have the most impact on those Jobs.
Then, as now, grappling with transformational technology isn’t just a matter of asking customers what they’re trying to get done, or deconstructing activities into tasks. Generative AI can raise new possibilities customers haven’t even considered, and it can totally re-shape the tasks they undertake. Stay open-ended yet highly rigorous in your inquiries, using Jobs to be Done to get specific about how generative AI can re-shape long-standing approaches.
For example, AI currently helps to direct display advertising to the most appropriate digital media. That’s not new. Rather than focus only on how AI can help media planners better accomplish tasks like deciding the split of ad budgets among media properties like Facebook and Google, step back and use Jobs to be Done to explore revolutionary possibilities as well. Can generative AI suggest the creative for ads that would perform best on these different properties, set an appropriate budget, and model the ROI of the ad campaign? It wouldn’t be easy, but likely yes it could. That would lead to a proliferation of distinctive, highly-tailored digital ad creative content.
Think about how changing preferences will affect your business. Your Jobs to be Done analysis can provide direction, because these Jobs probably won’t shift much even as the solution set does. However, preferences exist on a different plane and affect the picture too. People quickly get used to certain forms of interaction with their software. It may be useful to examine analogies and look at what leaders ahead of the curve are doing, e.g. how are companies like Adobe and Shutterstock incorporating generative AI into the experience of using their creative suite products? What has that meant for resulting customer expectations, e.g. that the image run with this article was custom-created by AI for the content (as it was).
3. Understand where generative AI’s advantages intersect with your business
Here you need to look at two sides of the coin. What can generative AI do for you, and what can you do for generative AI. Let’s explain.
Some of generative AI’s advantages are obvious: it can synthesize, personalize, and engage outstandingly well, for instance. You’d want to assess how these advantages can change user experience and even the core functions of your product. But you can also go beyond. Can generative AI suggest new actions the user might not have considered? Can it give a preview of what might result from those actions? Push the envelope.
On the other side of the coin, determine how your systems can make your generative AI even better. AI systems feed on data, and if everyone is using the same data then competitive advantages will be fleeting. But enterprise-grade generative AI systems, feeding on proprietary data, are entering fast. How can you use your systems to obtain and create data that will give you an unfair advantage? For example, can you gain proprietary data that allows you to better personalize experiences, or to optimize problem-solving using more precise information about the value of outcomes? Can you use your systems to label and categorize data so that AI can then better use it? The Data Wars are coming, and the companies with the best data can win.
4. Fundamentally re-think the customer journey and experience
The great potential of generative AI lies not in improving a customer’s interactions with software (though that’s likely to be a first impact), but in transforming them. This is where you want to deploy expertise in design thinking to look afresh. After you map out the quick wins through optimizing the current experience, determine what can be revolutionary.
To get there, go back to your insights about Jobs to be Done. Using a rigorous view of not just the Jobs, but also related factors like triggers and obstacles to adopting new solutions, you can determine detailed design criteria for a solution. How might generative AI offer truly novel ways to accomplish key Jobs? How can it offer different routes to succeed for customers on both an emotional and functional level? Where can it offer moments of delight?
5. Re-evaluate your competitive strategy
Proprietary data will help you retain a competitive edge in an AI-enabled world, but it may not be enough. Given that AI also enables code to be written and debugged much faster and more cheaply than before, we can expect rivalry to heat up. What does this mean for your product strategy?
Competitive strength comes from many sources. Think through all the potential innovation vectors you have available. Can you provide AI-assisted professional services to ensure customer success with your product and link it deeply into a customer’s ways of doing business? Can you be the keystone of an ecosystem of complementary offerings that will be difficult for rivals to uproot? Ask how AI will change not only competitive intensity but also the nature of sustained advantage.
The advent of generative AI has been compared to the dawn of the internet, but there’s a critical difference: this time, it’ll move even faster. You can embrace these five approaches to be on the front foot with your product strategy as change rapidly takes root.
If’ you’d like an example of how a start-up used this approach and just raised $120 million to infuse generative AI into its product suite, check out my interview with the CEO.
By Steve Wunker