The normal trend in the global business scenario is that only larger firms explore with Artificial Intelligence projects and firms under $1 billion in revenue do not have the ability to buy AI products and services or having strong in-house AI initiatives.
Let us see how is selling Artificial Intelligence to firms under $1B in revenue is done:
On a normal basis, Artificial Intelligence is sold to clients with having a definite amount of in-house data, science talent, a definite amount of Research and development budget, and a stomach for risk. In order to offer services and ascertaining the first step for companies under1 billion in revenue, we have to consider some important factors.
- Lack of In-house Data Science Talent: One main problem firms under 1 billion revenue is that they do not have authentic in-house data science talent. These companies usually claim that they do have but they generally have none at all. Real in-house data science means academically credentialed or business experienced people doing Artificial Intelligence. In smaller firms, they are not going to have this talent. Therefore, we need to prepare to educate leadership on fundamental concepts of Artificial Intelligence. We must also aim at projects that won’t require in-house data science talent.
- Very Little Executive Understanding of AI: Generally smaller firms tend to have very little understanding of Artificial Intelligence and of AI use cases. The executives rarely focus on AI fluency education on their own. Instead, they gain this fluency only with real-world enterprises. Conversations with vendors, feedback on real projects in their business, and conversations with other in-house talent working on real problems make the executives fluent in AI. Basic AI concepts and fundamentals deployment considerations will need to be translated into leadership prior to significant AI projects that should be commenced.
- Very Little R&D Budget to Test or Deploy AI Solutions: Generally there is little budget for R&D at small firms. Executive education must be given at most importance to solve this problem.
Selling Artificial Intelligence to smaller firms will definitely involve leading with executive education. It is quite inevitable. The education involves (1) familiarizing the client with the working of AI and the relevance of AI, (2) Making the clients understands the potential of valuable projects themselves. Only when the leadership has an authentic intuition on AI and when they cannot relate what AI to benefit their business, their initial AI projects can be brainstormed and be executed.
The main benefit of educational function and technical leaders in Artificial Intelligence is that it serves as a platform to sell services to smaller firms.
Smaller enterprises will begin with simpler projects than radical changes to regular workflows or data infrastructure. They have to focus on smaller-capability oriented projects that allow the smaller firms to learn more about how AI works, build team skills, data infrastructure understanding and helps them in gradually grow in-house data science talent at a rational pace.
