Artificial Intelligence and Facilitation of New Business Ideas in a Crisis
Using Advanced Analytics in Startup Communities
There are a variety of actors working in the startup community or with small companies, although one would like to have an easy definition of this space there can be a drift between the two.
“A startup or start-up is a company or project initiated by an entrepreneur to seek, effectively develop, and validate a scalable business model.”
“Small and medium-sized enterprises or small and medium-sized businesses are businesses whose personnel numbers fall below certain limits.”
What company is scalable? Well, anything could scale at least to a certain extent. Is McDonalds scalable — yes, but it needs stores. Is an Internet company scalable, yes, however it needs there to be an Internet connection and digital infrastructure.
“Scalability is the property of a system to handle a growing amount of work by adding resources to the system. In an economic context, a scalable business model implies that a company can increase sales given increased resources.”
There is a system whereas companies seek to increase their size and seek investment. It is within this process that a series of investment firms and/or accelerators, ecosystems etc. begins to get involved.
The question is raised in a time of crisis who would take the responsibility to map out approaches that are being taken to assist startups in this time of crisis. There may be a variety of initiatives locally and at regional or national level.
Of course machine learning applied does not immediately mean a deep understanding of the problems. One could find possible trends with a limited dataset that does not present reality and then attempt to generalise this largely for a bigger population. Yet there is something to be said for at least trying to get a grasp of the qualitative as well as the quantified.
Actors are likely using machine learning techniques or simply advanced form of analytics to better understand small businesses.
Some attempt to map the startup ecosystem such as Blink.
Then again there is Crunchbase.
“Crunchbase is the leading platform for professionals to discover innovative companies, connect with the people behind them, and pursue new opportunities. Over 55 million professionals — including entrepreneurs, investors, market researchers, and salespeople — trust Crunchbase to inform their business decisions. And companies all over the world rely on us to power their applications, making over a billion calls to our API each year.”
They are likely to already be using machine learning.
Yet in a time of crisis what could they do to help?
They have posted about tips on their blog.
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Others who work as accelerators or within the communities have approaches too. Who would be the actor to take on this sort of approach?
There has been advice posted by some.
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It remains to be seen if anyone can create a comprehensive map and what tools can be used to do so. How will small businesses receive help in this time? Both approaches from private companies and government is important to consider.
Could advanced machine learning or at least mapping out what is being done be of service to the community at large? That question comes to mind, and I think the answer might be close too.
This is #500daysofAI and you are reading article 298. I am writing one new article about or related to artificial intelligence every day for 500 days. My current focus for 100 days 200–300 is national and international strategies for artificial intelligence. I have decided to spend the last 25 days of my AI strategy writing to focus mainly on the climate crisis.