Bridging the AI Gap: How businesses can get results by adopting generative AI

It’s no secret that AI has gotten tons of hype over the last year or so. Large language models, or LLMs, have become available to the public via tools like ChatGPT and Bard. These models represent a groundbreaking innovation, yet very few businesses are actually using them.

Disruptive technologies take time to be adopted by the majority of the population. Geoffrey Moore gives a fantastic analysis of this phenomenon with several examples in his 1991 book, Crossing the Chasm. One of my personal favorites is the world wide web, the greatest invention most people alive today have lived through and which some companies still aren’t effectively leveraging.

It’s obvious that we haven’t crossed the chasm Moore mentions with generative AI. Despite its potential to revolutionize the way we work, almost all of the economic benefit is being captured by individuals with coding skills or a new class of “prompt engineers,” people who’ve studied or trial-and-error’d their way into being better than average at prompting models.

Despite their massive value across all industries, the benefits of generative AI have yet to reach the majority of businesses and people due to the lack of accessible application layers. Technology as we consumers know it is powered by protocols and applications. Protocols are basically rulebooks for how different systems and computers communicate and collaborate to accomplish a task. You may not have heard of popular protocols such as TCP/IP, HTTP, and FTP, but they are the underlying infrastructure that allow you to connect to the internet, load websites, and transfer files.

Most of the stuff you’ve heard of is at the application layer. Apps are what you interact with, whether it’s your Google Maps iPhone app or the Spotify desktop app on your laptop. Right now, the majority of the economic benefit of new technology such as AI  is being captured by large companies such as Microsoft and Google, along with a small number of prompt engineers and coders. Those who aren’t technically savvy don’t get the benefits of everything language models like GPT-4 can offer.

This problem is what Writerly is dedicated to solving - our mission is to enable businesses with and without technical staff members to leverage advanced features such as training your own model with your brand voice – all in a no-code environment that is accessible to every team.

We need more applications designed with human workflows and the organizational structures of businesses in mind. This human-centred design thinking is crucial when it comes to making generative AI accessible to everyone. Human-centred design/UI is about designing interfaces that are intuitive and easy to use, allowing regular people to make use of new technologies without the need for extensive technical expertise.

Writerly’s new smart brand persona interface, for example, allows users to effectively fine-tune their own custom language models by dragging and dropping PDFs and tagging them with a simple drop-down. Users can then use their custom models to generate content in their own brand voice and according to their own brand guidelines. By applying human-centered design principles to generative AI, we can make the technology easy for teams to implement and leverage.

Generative AI has the potential to radically reduce costs and time-to-market but only when it stops being a dev project or a low-code tool requiring technical expertise. Only when generative AI solutions start to more closely resemble google drive, canva, and calendly will the market be able to correct the current inefficiency of latent adoption. By embracing human-centered design and making the technology more accessible and intuitive, Writerly hopes to empower businesses of all sizes to harness the power of generative AI.