Feel like you’ve missed the generative AI train? 5 steps to accelerate in 90 days

I spoke to founders across the Global South on Generative AI (GAI) as often as possible since early 2023. Founders in our portfolio of over 350 companies are users of Generative AI, not creators. As with any other disruptive situation, these founders can be divided into three groups:

• Ahead of the Curve: Companies that have already shipped something.
• Fast Followers: Looking and prototyping but haven’t shipped yet.
• Late for the train: you don’t know how to get on the train yet / you don’t have the resources to apply now.

This article is for any founders who are feeling late for the train or are all aboard, but aren’t going fast enough.

Reviewing examples from all three groups will help founders know where they really stand. Those Ahead of the Curve had at least three things going for them: they saw the opportunity ahead of time, they had ready-made situations they could apply Generative AI to, and they had engineering talent available to get something prototyped and into production in a timely manner.

An example is an agricultural ecommerce company that has already deducted 30% of its customer service costs by putting a chatbot that can talk to farmers in front of its customer service agents and expects savings of up to 50% in the next quarter or SO.

A Fast Follower has prototyped means to reduce costs and increase the speed of blue collar recruiting by adding AI-driven generative steps to its interviewing and candidate engagement workflow. Because they have a complex workflow with high throughput, they need to pay attention to how quickly they deploy; initial tests are showing huge improvements in multiple dimensions.

Finally, a Late for the Train startup provides solutions for call centers and has done some initial evaluation and planning, but has not yet determined how/when to best add Generative AI to its product roadmap, which is already stressed by requests from existing customers.

Here are five clear steps to go from being late for your train to speeding in a lot less time than you think:

1. Keep your language simple so everyone can communicate clearly about this disruptive technology.
2. Engage your entire team at a high level (many of them may already be there without your knowledge).
3. Make sure you don’t allow Cloud LLMs to retrieve your data in ways that expose it to competitors or malicious actors.
4. Establish a red team to be internally disruptive.
5. Measure progress in adopting Generative AI and communicate it to the business consistently.

1. Type 1 and Type 2 Generative AI Applications

There are many new words and technical concepts about AI, and many have written about it, so you don’t need more from me except this concept: From an adoption point of view, there are basically two paths you can go down, which are in any exclusive way.

The first is to use AI to improve what you are already doing by increasing the productivity or quality of operations or interactions with existing customers. Let’s call it a type 1 application.

The Ahead of the Curve example cited above is type 1: companies that use generative AI to improve sales communications or help with market research are doing type 1 work. Type 1 projects can be implemented at the individual or departmental level. And most importantly, they are the stakes for every startup these days must-do activities. If you want to get funded and can’t show clear adoption of type 1 applications, you’re in trouble. But Type 1 ventures alone won’t make you an AI company from a venture capital perspective.

Type 2 ventures are bigger, riskier, and far more important to your survival and ability to attract capital. With Type 2, you’re looking to create entirely new ways to approach a vital aspect of your business, or potentially your entire business, relying on Generative AI.

The benefit of Type 1 is lower cost and higher speed/productivity which everyone is doing or soon will be doing. The Type 2 benefit is potentially unlimited, as you are creating new ways to create and deliver value that could gain you access to new customers or gain substantial competitive advantages over others who are not deeply embracing Generative AI.

An example of a type 2 innovation might be a regional B2B marketplace that currently only publishes information in English as it is the common denominator language in the region. That marketplace can now use AI to cost-effectively publish information simultaneously in four local languages ​​and enable their customers to find products/services with a conversational interface (rather than cumbersome search queries and complex filters) using their favourite language. This type 2 innovation opens up the market to countless non-English speaking customers and also makes it faster for all customers to find what they are looking for and seal the deal.