When Your Clients Don’t Know What They Want

Steve Jobs did not ask what the customers wanted; he showed it to them. Henry Ford did the same. Every notable innovator in history, Edison to Tesla to Gates to Altman et al., showed something that the world did not know it wanted/needed. All of them did not start with customer requirements but reimagined customer experience.

Emerging technologies provide opportunities to create new business models that weren’t there before. This is how incremental economy gets created as against disruptive economy. GenAI is one such example. When companies don’t know how GenAI can unlock value, reimagining customer experience is the best way. To do that, we need to discover the current and potential future customer experiences with a roadmap to achieve them.

Everyone is exploring with pilots to discover how GenAI can give them a competitive edge. When we are not clear on what we want, proven startup approach of "build-measure-learn" using an MVP is best-suited.? However, the following attributes are absolute necessity, as we get clarity of the GenAI value creation.

1. Applicability: Business leaders should start with the question - “What can GenAI do to my business?” instead of “How can I adapt GenAI?”. It’s very easy to get succumbed to the shiny-object-syndrome. Developing business cases to demonstrate the promise of GenAI is key. 99% of the Fortune-500 are already using AI tools. Every one of them are evaluating the applicability of GenAI and 69% of them believe that they would have their AI-strategy firmed up before end of 2024.
2. Affordability: Even to identify use cases for GenAI, many businesses need help from service providers, mainly because of "skills shortage" in their organizations. 98% of companies have started working with IT services vendors on GenAI projects. Additionally, cost considerations are vital pillars upon which CEOs should built their GenAI strategies.
3. Flexibility: Flexibility in technology means easy adaptation and changes through configuration than re-development. It is important for users to choose a framework and technology that is flexible in the fast maturation of the GenAI. It is important to avoid vendor lock-ins for a prolonged period and have the freedom to explore as the technology evolves.
4. Stability: GenAI does not function like the traditional technologies. Our existing systems, processes and even our IT culture aren't designed to work with GenAI. It is changing too fast and sometimes it feels hard to keep up. Yet, it is not the time to wait and see. 98% of the companies are experimenting with GenAI use cases and some suggests to slow down until we better understand the ramifications. End of the day, stability is a subjective term. Organizations should define it in the way it is appropriate to their culture.
5. Scalability: Launching GenAI pilots is easy but getting the pilots to scale and creating meaningful value are difficult. Trust and the cost of building the data foundation are? the biggest roadblocks for the AI scaling. Additionally, AI cannot operate in a silo, it should work with other corporate solutions to prove its worth. Integrating it with the rest of the corporate string will require serious changes across the board.

It is natural for us to debate the promise of GenAI, as it is only in the "peak of inflated expectations" now. Experts believe that 2024 will start to see the tailwinds of GenAI. Fast adoption of GenAI will create a significant incremental economy through accelerated innovations and applications. In this fast pace of tech, our learning will also be fast, but the core of finding value through reimagining customer experience and driving change always follow certain basic techniques that we should stick to.