Generative AI took the world by storm in 2023, massively impacting businesses in every industry seemingly overnight. As a result, nearly all venture capital-backed companies (90%) have plans to embed generative AI into their products, according to a Productboard survey from earlier this year.
AI is especially having an impact on informing product designs and taking companies to the next level in meeting customer needs. Business leaders are realizing generative AI is too valuable to fade away, and it is triggering both productive, competitive innovation and a downright scramble to integrate certain AI features and functionalities into products fast. This has become the number one priority of many business leaders, which will extend into 2024 and beyond.
AI has become ingrained in user expectations
Customer expectations are ever evolving, and new advancements in one industry push others to innovate to meet new user needs and demands. As new developments in AI have been incorporated into customer products and enterprise applications, users have become accustomed to new conveniences afforded by these capabilities. Now customers expect the AI features they find most useful to also be integrated across other companies’ applications, and businesses that don’t implement similar updates will find themselves falling behind the competition.
For example, if a user is accustomed to autocorrect on an iPhone but isn’t allowed the same seamless writing and editing experience through their employer’s Outlook email application, there may be some frustration and a point of friction between the product and user. The functionality, user experience and ease-of-use that AI can provide to products is becoming table stakes and expected across tools, and this is true for all types of companies, from tech titan to startup. Organizations must be prepared to keep pace with evolving AI features and capabilities and set a path toward integrating them into products routinely. This will be critical for business leaders and product managers moving forward.
Product teams will take advantage of AI to meet customer needs
As generative AI rapidly moves from a specialist technology into the mainstream, I expect it will also commonly be used as a guide to steer product managers in the right direction, helping them better incorporate customer feedback into their overall strategy. The information generative AI tools can offer goes beyond what one might gather from a text-based format. Rather, precisely structured LLMs, trained on information within a program itself, can be incorporated directly into a product platform’s visual interface. This type of intricate guidance will give product designers easy access to key insights they might not have found otherwise, giving them clear direction on how to build better products for their customers. This will have a transformative impact on how new ideas are developed and designed and will be a crucial area for leaders to consider in their AI and broader tech strategy moving forward.
When these integrations are available, product managers will likely use AI features that filter through all available customer data to only show important details from specific use cases. AI naturally lends itself to synthesizing and summarizing data, and this is crucial as so many companies report being overwhelmed by their data. In this way, product teams have a much better chance when it comes to understanding their data, and they can easily decipher which customer concerns are most important to address in new product updates. Additionally, AI can allow product teams to write feature specs – such as problem summaries, common theme summaries, pain points, desired outcomes – much faster with the help of AI, producing higher-quality work, faster.
Every single company must offer a high-quality product that meets customer needs in order to remain competitive. AI can help companies maintain the highest level of quality at a more rapid pace than ever before.
Generative AI must be supported by humans for successful creative applications
While generative AI can surface valuable and actionable insights for businesses, it does not necessarily offer the best next step or creative idea for businesses to take. For starters, AI’s pool of knowledge is limited, and there may be crucial information known by employees that isn’t captured within an AI’s dataset. It also does not have the ability to proactively disseminate information to parties across the organization who might benefit from it – you must ask for the information you need. Ultimately, the creative decision making and product roadmap design is up to business leaders and project managers.
The good news is that, because AI-summarized findings provide easy access to key customer insights quickly and at scale, product teams spend less time sorting through data in the long run. Important insights are easily accessible, freeing up employee time to brainstorm on creative ways to solve customer concerns. Furthermore, any potential creative ideas presented by generative AI tools should always be thoroughly vetted by a human, and it’s beneficial to bounce ideas off one another to further refine them. An AI model may offer ideas for new innovations, but it may offer solutions that are unrealistic given the real-life circumstances.
Using generative AI in product development allows designers to make better-informed decisions, lower the risk of failures, streamline routine tasks and collaborate more effectively. Easier access to customer data and the simplification of basic tasks allows companies to meet user expectations more quickly and seamlessly, ultimately benefiting customer experience and leading to better business outcomes. I expect generative AI will continue to have a profound impact on companies in 2024 and the years to come as the technology further evolves.
